1. Customer Description Card
Minta Aluminum Technology (Taicang) Co., Ltd. was established in 1953 and has firmly established itself in the metal manufacturing industry for over half a century through continuous efforts, starting with providing customers with post-processing services for steel pipes. With the trends of the times, aluminum has gradually replaced steel and chromium-molybdenum steel due to its material advantages. In order to provide customers with more comprehensive services, Mindar officially transitioned to the aluminum profile industry in 2000. In the past decade, it has successfully conducted vertical integration in the aluminum profile industry, focusing on the mobility sector, and is a supplier of "dominant" market shares for electric scooter brands in Europe. In the four-wheeled sector, it also provides aluminum profile solutions to high-end automotive brands both domestically and internationally, making it an absolute leader in the niche industry. Current services include aluminum ingot casting, mold design and manufacturing, aluminum profile extrusion, CNC milling and turning, cutting, bending and stamping, surface anodizing and internal high-pressure forming, with a total investment reaching 30 million dollars.
Main Products: Automotive collision beams and spare parts, bicycle/scooter frames
Employee Scale: 500
Production Value: 600-700 million
Industry Position: Deeply engaged in the aluminum products industry, holding authoritative certifications such as ISO9001 and IATF16949. With advanced technology and equipment, it provides high-quality products such as aluminum scooters and automotive collision beams for key industries such as medical, electronics, and transportation, leading the aluminum products subsector in mobility.
Application Industry: Automotive spare parts
Main Markets: Domestic
Downstream Customers: Volvo, Audi, Xiaomi
Production Process: Extrusion / Machining / Aging / Painting / Anodizing
Mindar Product Applications - Automotive
Mindar Product Applications - Bicycle
Showcase of Some Other Products
2. Project Background Introduction
Currently, achieving carbon neutrality has become a global consensus, and major global automobile manufacturers have successively released long-term plans aimed at achieving "decarbonization." According to statistics, there is an urgent demand for lightweight new energy vehicles. For every 10kg reduction in the weight of a pure electric vehicle, the cruising range can increase by 2.5km. The China Society of Automotive Engineering predicts that the aluminum consumption per vehicle will rise from 190kg in 2020 to 350kg in 2030. In addition to the widely used aluminum engine components and aluminum alloys in luxury car bodies, the application rate of aluminum alloys in components such as wheels, bumpers, and hoods is also expanding. In the next decade, the aluminum penetration rate of various automotive components will significantly increase.
Situated in this promising market environment, Mindar Aluminum Technology (Taicang) Co., Ltd., as a leader in the aluminum profiles industry for new energy vehicles, precisely grasps the pulse of the times and boldly sets a strategic goal of "tenfold growth in five years." The arrival of the Internet of Things era has made the transition from digital factories to intelligent factories an irreversible industrial development direction. The three major links of factory operations QCD are particularly important. More and more companies are beginning to explore and attempt to establish intelligent factories to maintain future competitiveness.
The company currently has a wide variety of products, complex processes, and strict requirements for delivery, quality, and cost management. Currently, various process management nodes within the enterprise heavily rely on manual and offline documents, lacking necessary process fail-safes, tracing, and data management:
As business expands, the existing management system struggles to cope with complex business processes. For example, business data and financial data operate independently, creating information silos, resulting in inaccurate cost accounting and decision-making that lacks support. In cooperation projects with important customers, financial data often delays and inaccuracies affect cost control and quoting decisions.
On the other hand, the demand for quality control is urgent, lacking an effective traceability system. In the supply of automotive spare parts, once quality issues arise, it is not possible to quickly locate the source, seriously damaging the company's reputation and customer trust.
Additionally, the execution of processes is chaotic, lacking effective monitoring and standardization mechanisms. Difficulties in departmental coordination lead to low production efficiency and severe resource waste, greatly restricting the company's further development.
💪 To break through the predicament and enhance competitiveness, Mindar Aluminum is initiating a digital transformation project aiming at integrated business finance, precise quality traceability, and standardized process execution.
3. Current Situation
3.1 Workshop Business Process
Information Technology Status
4. Project Blueprint
Optimized Business Process
Full Process Traceability
5. Solution Details
5.1. System Integration
5.1.1 SAP System Integration
Solution Introduction:
The SAP system manages financial data and supply chain, while the new core cloud system focuses on production/quality/equipment/mold and other business data. Through system integration, the goal of integrated and standardized management operations is achieved.
Before Application (BEFORE)
Pain Point 1: No standardized and regulated process management, numerous operational systems, employees repeatedly operate systems, working on multiple accounts, leading to duplicate work and low personnel efficiency.
Pain Point 2: Business data and financial data disjointed, cost data accounting is inaccurate with information silos.
After Application (AFTER)
Value 1: Establish standard management processes with clear workflows, solving the multiple accounts issue, ensuring data is transparent and traceable. Reducing duplicate work greatly improves efficiency.
Value 2: Detailed responsibilities among systems, achieved through interface integration, realizes business-finance integration. Cost and financial accounting data are clear, effectively providing data support for management decisions.
SAP Integration Plan
5.1.2 Weighbridge Integration Plan
Solution Introduction:
Mindar Aluminum integrates the weighbridge system deeply into the production management system through hardware connections and software interactions, ensuring that weight data can be automatically collected and stably transmitted to the management system, achieving efficient data circulation and centralized management.
In the raw material warehousing process, once the vehicle is loaded and weighs on the weighbridge, the system immediately acquires the weight information and records it; during waste material processing, the weighbridge also weighs, strictly standardizing operational processes to ensure data consistency and reliability.
The system is equipped with powerful data storage and convenient query functions, allowing precise tracing of historical weight details for each batch of raw materials and waste material, laying a solid data foundation for enterprise production management and cost accounting.
Before Application (BEFORE)
Manual operation is inefficient and prone to errors: ** Previously, Mindar Aluminum completely relied on manual filling of weighing data, which was cumbersome and extremely inefficient, leading to numerous data errors due to human negligence or fatigue.
Lack of supervision leads to poor data quality: ** Due to lack of effective supervision and verification mechanisms, the reported weighing amounts are severely at risk regarding accuracy and authenticity, making it difficult to control data quality effectively.
Cost accounting chaos from inaccurate data: ** This puts immense risk on the company's cost accounting, as incorrect data can distort the calculations of raw material procurement costs or waste handling revenues, severely interfering with profit assessment and decision-making, affecting the healthy development of the company.
After Application (AFTER)
Automated collection ensures data accuracy: ** After introducing the weighbridge integration system, weighing data is automatically collected. Sensors detect the weight in real-time and transmit it to the system, eliminating the need for manual input, avoiding human errors.
Accurate data enhances cost accounting optimization: ** The precise weighing records generated by the system provide a solid and reliable data foundation for cost accounting, enabling financial personnel to conduct accurate cost calculations and significantly improving the accuracy and scientific nature of cost accounting.
Simplified processes promote efficiency improvements: ** Overall work efficiency sees significant improvements, reducing manual intervention, and making the raw material warehousing and waste processing processes more efficient and smooth, effectively enhancing the level of enterprise operation management.
Scene/Image
Weighbridge Integration
Weight Difference Data
APP Side "Weighbridge"
Weighbridge Business
5.2 Energy Consumption Management
Solution Introduction:
Manually entering equipment production time and output information, collecting electricity meter and gas meter data, calculating daily consumption and equipment unit consumption.
Before Application (BEFORE)
Difficulties in data collection and statistics: The production time and output information of the equipment need to be entered manually, which not only consumes a lot of labor and time but also easily leads to errors, making it difficult to ensure the accuracy and timeliness of data. The data collection of electricity meters and gas meters may lack systematic operation, making it difficult to obtain comprehensive and accurate energy consumption information.
Unclear unit consumption situation: Due to the lack of effective data integration and analysis methods, it is impossible to calculate the unit consumption situation of devices based on production time and output data, making it difficult for the enterprise to understand energy consumption efficiency at each production link and implement energy-saving optimizations.
After Application (AFTER)
Accurate data statistics and analysis: By standardizing the data collection process, it is possible to accurately obtain the production time, output information, as well as electricity meter and gas meter data, and to statistically summarize consumption statistics for day shifts/evening shifts and full days. Combined with production data, calculating equipment unit consumption provides detailed and accurate energy consumption data for enterprises.
Energy-saving optimization decision support: Based on precise energy consumption data and unit consumption analysis, enterprises can identify production links and devices with higher energy consumption, thus formulating targeted energy-saving measures such as equipment upgrades, process improvements, or production scheduling optimizations to reduce production costs and improve energy utilization efficiency, enhancing competitiveness in the market.
Scene/Image
Energy Consumption Data Entry
Energy Consumption Statistics
Production Unit Energy Consumption Data
5.3 Workshop Planning
Solution Introduction:
Enhance extrusion and post-processing workshop planning scheduling efficiency, reduce communication costs between departments, and achieve online office collaboration among relevant business departments;
Daily scheduling data for precise display, multi-material process one-click scheduling, data visualization, effectively tracking planning progress.
Before Application (BEFORE)
Pain Point 1: There are many business units, and different planning basis and standards exist between business units, making it difficult to synchronize information in the scheduling process, causing deviations in planning execution.
Pain Point 2: A wide variety of products and models lead to scattered scheduling data; personnel rely on spreadsheets for statistics, which is time-consuming and labor-intensive, needing to manually transcribe data to create production planning documents for issuing to the workshop.
After Application (AFTER)
Value 1: Advanced workshop planning defines different scheduling rules according to the needs of different business units. For example, extrusion scheduling resources use extrusion equipment as a bottleneck for scheduling, while the post-processing workshop uses either equipment or group as a scheduling basis, effectively displaying the production situation of various processes, facilitating planning execution.
Value 2: The system automatically calculates material requirements based on the process maintained, BOM, standard working hours, etc., to obtain net demand for parts and split daily production numbers. The page content includes: gross demand, inventory, production amounts, net demand, cumulative material gaps, dates; the net demand calculation supports customization, effectively reducing scheduling time. The scheduling plan document is quickly generated and printed with one click, saving time.
Scene/Image
Scheduling Settings
Work Order Planning Document
Planning Scheduling Interface
Transformation Effect: Planning completion rate stabilizes above 98%
🚀 Product material package link:S|Workshop Planning - Professional Version
5.4 Sales Consolidation Management
Solution Introduction:
Production management consolidates small batch scattered orders, stipulating that work orders with the same process route or set within deadline ranges can be consolidated; after consolidation, the original work orders are nullified, and production quantities are accumulated. When distributing work orders, the "Plan Material Area Rounding" function is set to check planned materials, rounding decimals up. At the same time, consolidated report statistics the number of consolidations, process rates, and raw material savings, while displaying the production progress of consolidated orders distributed.
Before Application (BEFORE)
High risk of inventory backlog: The presence of numerous small batch scattered orders can easily lead to inventory accumulation if not consolidated, occupying large amounts of capital and storage space, and increasing inventory management costs and liquidity pressures.
Complex production plans: Numerous small batch scattered orders complicate the production plan, making resource coordination challenging and easily leading to disorganized production arrangements, affecting production efficiency and delivery timelines.
After Application (AFTER)
Reducing inventory pressure: By consolidating small batch scattered orders, effectively avoiding inventory accumulation. Consolidating work orders with the same process route or set within the deadline reduces unnecessary inventory storage, freeing up capital and warehouse space, and lowering inventory management costs.
Simplifying production plans and resource coordination: Consolidation operations simplify production plans, facilitating central resource production and achieving scale; reducing switching times and improving efficiency, equipment utilization, and customer satisfaction. The rounding function and report optimize material provision and assist management decisions.
Image
Production Order Consolidation
Select Consolidation
Consolidation Report
5.5 Full-Process Scanning Management
Solution Introduction:
1. Solving production site transparency through information management MES software that connects various operating environments, for example: the production of extruded semi-finished products; inspection data of aging performance, production preparation, supplementary materials, returning materials, etc.;
2. Production execution control based on processes/models, utilizing technologies like barcodes; accomplishing product process flow record through scanning materials, scanning production orders/flow cards for reporting, scanning for warehousing, binding and printing batch codes for key batches, ensuring products follow established process paths, achieving data collection recording, and process traceability, making the workshop production more transparent and efficient.
3. Ensuring accurate tracing of product information by scanning materials on-site, implementing anti-error management for actual input materials, enhancing the flow efficiency of materials and standardizing material flows.
Before Application (BEFORE)
Pain Point 1: Preparation work before production and inter-departmental coordination rely entirely on offline communications, leading to low efficiency and difficulty in ensuring timeliness and process records.
Pain Point 2: Production reporting relies on offline work cards and is collected by designated personnel, which is time-consuming and labor-intensive.
Pain Point 3: The production process is fragmented, with long production sequences and many types of work in progress, making it challenging to manage the flow of work in progress.
Pain Point 4: Many batches make error-proofing difficult.
After Application (AFTER)
Value 1: Online generation of related documents for production preparation, allowing tighter coordination between departmental work.
Value 2: Employees can report work in real-time by scanning, eliminating traditional work cards, improving reporting efficiency.
Value 3: MES provides reports on work in progress, accurately displaying the quantities and locations of work in progress in each segment. During production, flow receipt functionality is provided, ensuring consistent upstream and downstream transfer and reception quantities, avoiding discrepancies.
Value 4: MES offers full-process scanning support, ensuring first-in-first-out for outbound, proper on-site material input, and clear identification of materials in the workshop.
Image
Production Order
🚀 Product material package link:S | Production Management - Professional Version
5.6 Process Quality Management
5.6.1 IPQC
Solution Introduction:
IPQC focuses on key quality control points in the production process, conducting regular inspections and sampling based on predetermined inspection standards and specifications to monitor processes such as extrusion, aging, stamping, and anodic cleaning in aluminum profile production. It aims to detect and correct any factors that may affect product quality in a timely manner to prevent unqualified products from entering the next process.
Before Application (BEFORE)
Detection lacks standardization: Previously, quality inspections relied on human experience and simple tools for irregular sampling, with limited and non-standard testing items, making it difficult to fully control product quality and resulting in frequent potential quality issues, with defective products flowing into subsequent processes at high risk, seriously impacting overall product quality and corporate reputation.
Difficulties in tracing information chaos: Lack of barcode management leads to scattered paper records of product information, requiring time and effort to organize and search. In responding to customer feedback or factory audits, it is difficult to quickly provide production details and quality data, failing to meet traceability and compliance requirements, leading to customer dissatisfaction and reputational risk.
After Application (AFTER)
Strict testing improves quality: After implementing the IPQC plan, each process test is strictly conducted according to regulations, using advanced inspection equipment and scientific methods, achieving deep control over product quality. It can timely intercept unqualified products, effectively reducing scrap rates and rework rates, significantly enhancing the stability and consistency of product quality, and strengthening the company's market competitiveness.
Convenient tracing enhances credibility: A comprehensive barcode management system enables efficient and accurate product traceability; through scanning or system retrieval, it allows for quick access to complete production information, enabling rapid localization of problem sources during customer feedback and audits, facilitating timely improvements and optimizations, significantly improving customer trust and corporate brand image, promoting sustained and healthy enterprise development.
Production Inspection Standards
Product Inspection Scheme
🚀 Product material package link:S | IPQC
5.6.2 End-to-End Traceability
Solution Introduction:
At Mindar Aluminum, by setting a unique code for each production step and utilizing information technology such as scanning and database storage, the operation information, equipment parameters, operators, timestamps, etc., for processes such as aluminum rod material receipt, extrusion, aging, stamping, and anodized cleaning are recorded in detail and established in relation to each other, achieving precise traceability of the product's entire lifecycle.
Before Application (BEFORE)
Tracing without a way data chaos: Previously, Mindar Aluminum did not have a unified traceability system; the data from the production process was scattered across various departments and paper records, lacking effective integration and management. This led to an inability to quickly and accurately provide relevant information when responding to the traceability demands of automotive customers, severely affecting customer satisfaction and enterprise reputation.
Management is crude and inefficient: Due to non-standard onsite management, the flow of materials and processes lacked strict recording mechanisms, easily leading to production chaos and errors, which not only increased production costs but also reduced production efficiency, hindering the enterprise's development.
After Application (AFTER)
Precision traceability enables quick responses: By scanning the product barcode, the complete production history, including raw material sources and processing details of each process, can be quickly queried in the system, significantly improving the accuracy and timeliness of traceability, effectively meeting the strict requirements of automotive customers for batch traceability and enhancing customer trust in the enterprise.
Standardized management improves efficiency: Standardized onsite management and data recording make the production process more orderly, reducing material waste and production errors. Quality analysis and production optimization are based on accurate traceability data, enhancing production efficiency, lowering costs, and boosting the competitiveness of the enterprise.
Material Tracing by Module
Tracing - Tree Structure Details
🚀 Product material package link:A | Full Process Traceability
5.7 Equipment Management
5.7.1 Equipment Data Collection
Solution Introduction:
1. List the types of data collection devices for machinery and the types of data.
2. Key equipment collects production process parameters, monitors parameter changes in real-time, alarms when out of limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large equipment quantity, there is no unified platform for management, and data maintenance is difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure the timeliness of employee execution; data storage and querying are cumbersome.
Pain Point 3: Employees need to periodically transcribe the production parameters and inspect for anomalies, increasing unnecessary work volume.
Pain Point 4: When anomalies occur on-site, communication happens through offline phone or WeChat, resulting in high communication costs and inaccurate task assignment, leading to chaotic management without data to assess equipment maintenance efficiency.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system automatically generates corresponding reports based on completed inspections and maintenance, providing a basis for data analysis for managers.
Value 3: Real-time collection of production parameter information from equipment, setting parameter upper and lower limits, with automatic alarms for exceeding limits to relevant personnel for timely processing, enhancing problem handling efficiency.
Value 4: Establishing an anomaly reporting mechanism allows frontline employees to quickly report problems when they occur, the system automatically assigning corresponding personnel for timely handling, and automatically collecting data to statistically assess equipment failure indicators, evaluating the efficiency and capability of maintenance personnel.
Equipment Status Monitoring
Equipment Parameter Monitoring
Equipment Status Dashboard
5.7.2 Preventive Maintenance of Equipment
Solution Introduction:
1. Establish a complete inspection/maintenance plan for equipment, achieving task formulation, distribution, reminders, and execution of inspections/maintenance. Effectively preventing anomalies during processing and ensuring equipment stability.
2. Key equipment collects production process parameters and monitors parameter changes in real-time, with alarms for exceeding limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large quantity of equipment, there is no unified platform for management, making data maintenance difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure timeliness; data storage and querying are inconvenient.
Pain Point 3: Employees need to periodically transcribe production process parameters and inspect for anomalies, raising unnecessary work volume.
Pain Point 4: Anomalies occurring on-site result in high communication costs without a structured method for proper task assignment; management is chaotic, lacking data to assess equipment maintenance effectiveness.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system generates corresponding reports based on completed inspections and maintenance, providing data analysis support for managers.
Value 3: Real-time collection of production parameters from equipment, establishing upper and lower limits, with automatic alarms for exceeding limits to deal promptly with issues.
Value 4: An anomaly reporting mechanism is established, allowing frontline employees to quickly report when problems occur and automatically assigning corresponding personnel to address issues, while collecting and statistically analyzing equipment failure information for efficiency assessments.
Equipment Log
Daily Equipment Inspection
Equipment Parameters
Equipment Alerts
Equipment Anomaly Handling
APP Execution of Inspection Operations
🚀 Product material package link:A | Preventive Maintenance of Equipment
5.7.3 Equipment OEE
Solution Introduction:
1. Based on management operation indicators set by the enterprise, decompose from top to bottom, completing business processes for data collection, with automatic generation of KPI management reports by the system.
2. Analyze the issues based on KPI results, implement improvements on-site, confirm improvement effects, completing PDCA cycle improvements.
Before Application (BEFORE)
Pain Point 1: Basic data collection is manually compiled with low value and high workload.
Pain Point 2: Manual data collection cannot guarantee data authenticity and timeliness.
After Application (AFTER)
Value 1: Real-time collection of real accurate data through business processes, eliminating manual recording methods.
Value 2: The system automatically generates performance management reports.
Process Parameters
KPI Management Reports
🚀 Product material package link:A | OEE of Equipment Analysis
5.7.4 Task Management
Solution Introduction:
Assisting in arranging labor hours: Display "Labor Hours" in the task order and production order operation view, calculated by the formula "Labor Hours = Task Order Planned Quantity × CT," providing a reference for on-site personnel resource allocation to ensure labor input matches production tasks.
Verification for personnel assignment and machine approval: During secondary assignments, check the number of personnel at workstations, ensuring it does not exceed the process set value, prioritizing personnel or groups maintained by the process work center, to ensure reasonable and efficient personnel allocation and avoid waste. Additionally clarifying operating processes under different allocation scenarios, such as direct assignment without splitting sub-tasks and simultaneous assignment of split sub-tasks.
Before Application (BEFORE)
Personnel allocation is chaotic: On-site personnel distribution lacks effective standards and verification mechanisms, easily leading to over or under allocation in certain processes, resulting in wasted human resources or delays in production tasks, reducing production efficiency.
Low production efficiency: As ineffective matching of personnel and processes may lead to slow progress in some processes due to insufficient personnel while others are underutilized, disrupting the overall production rhythm and affecting product output speed and enterprise benefits.
After Application (AFTER)
Optimizing resource utilization: Accurate personnel and equipment allocation based on process requirements and production tasks avoids wastage of human resources, increasing equipment utilization, leading to more scientifically rational resource allocation in the production process.
Enhancing production efficiency: Ensuring an appropriate number of personnel operate at each process, guaranteeing smooth production flow and decreasing production interruptions and delays caused by personnel issues, effectively improving overall production efficiency and helping the enterprise meet production tasks on time, enhancing market competitiveness.
Arranging Human Resources
Labor Hours = Planned Quantity of Task Order M * CT
🚀 Product material package link:Secondary Assignment
5.7.5 Workstation OEE
Solution Introduction:
Calculating OEE at the workstation level to assist on-site management and increase production efficiency.
OEE = (Net Production Time / Actual Production Time) * (UPH(a) / UPH(p)) * (Qualified Count / Total Reporting Count)
Actual Production Time: Manually clicking start to completion of task reporting
Net Production Time: Actual Production Time - Planned Losses - Equipment Anomaly Losses - Waiting Material Anomalies - Others (e.g., quality pulls or material defects)
UPH(a) = Total Reporting Count / Net Production Time
UPH(p) = Standard Working Time (Processing time maintained within process routes)
Qualified Count: Qualified items within Total Reporting Count, defaults to qualified if inspection results are not available
Total Reporting Count: Total reporting count within the Actual Production Time range
Before Application (BEFORE)
Missing efficiency assessments: Enterprises find it difficult to accurately measure each workstation's actual efficiency performance during production, making it challenging to identify sources of time waste, speed discrepancies, and quality issues during production processes, leading to ineffective improvements.
Management decisions lack scientific basis: Due to the absence of accurate efficiency data, adjustments to production plans, resource allocations, and equipment maintenance often lack well-founded evidence, resulting in resource waste and delays in production.
After Application (AFTER)
Precise efficiency analysis: OEE calculations provide clear insights into utilization of time, production speed, and product quality at each workstation, helping enterprises accurately identify production bottlenecks and inefficient segments.
Optimizing production management: Based on OEE data, targeted improvement measures can be established, such as optimizing equipment maintenance plans, adjusting personnel allocations, and improving production processes, thereby enhancing overall production efficiency, reducing production costs, and increasing enterprise competitiveness.
Details of Equipment OEE
🚀 Product material package link:Equipment OEE Optimization
5.8 KPI Management
5.8.1 Production Plan Achievement Rate
Report/Dashboard Introduction
Visually presents the completion progress of production plans, allowing management to quickly understand whether production tasks are proceeding as planned, for instance, a 70.66% achievement rate can directly reflect the current execution status of production plans and adjust production strategies timely, ensuring the achievement of production goals.
Production Plan Achievement Rate
🚀 Product material package link:B | Production Achievement Rate
5.8.2 Production Process PPM
Report/Dashboard Introduction
The production process PPM report measures quality levels in production processes by displaying PPM report numbers, trends, and summaries, based on the quantity of defects per million products, helping enterprises identify high-frequency quality issues in production segments and provide direction for quality improvements.
Production Process PPM
🚀 Product material package link:B | Production Process Defective PPM
5.8.3 First Pass Yield
Report/Dashboard Introduction
Displays first pass rates from multiple dimensions such as inspection dates, business units, workshops, etc. Detailed inspection and testing data enables enterprises to analyze the stability of production quality across different segments and departments, taking targeted measures to improve the overall yield.
First Pass Yield
🚀 Product material package link:B | FPY First Pass Yield
5.8.4 Quality Defect Analysis
Report/Dashboard Introduction
Lists failure counts, times, defect rates, etc., aiding enterprises in thoroughly analyzing the sources of quality defects, such as equipment failures, process issues, or human factors, thus effectively guiding enterprises in quality improvements and equipment maintenance to enhance product quality.
Quality Defect Analysis
🚀 Product material package link:A | Equipment OEE Analysis
5.8.5 Management Dashboard
Report/Dashboard Introduction
The management dashboard displays daily and next day's planned tasks, quality anomalies, personnel status (red idle, yellow slow, green normal), with functions for prior work warning (10 minutes early) and alarms (15 minutes delayed reporting), helping managers control production progress, quality, and personnel efficiency.
OEE Management Console Dashboard
1. Customer Description Card
Minta Aluminum Technology (Taicang) Co., Ltd. was established in 1953 and has firmly established itself in the metal manufacturing industry for over half a century through continuous efforts, starting with providing customers with post-processing services for steel pipes. With the trends of the times, aluminum has gradually replaced steel and chromium-molybdenum steel due to its material advantages. In order to provide customers with more comprehensive services, Mindar officially transitioned to the aluminum profile industry in 2000. In the past decade, it has successfully conducted vertical integration in the aluminum profile industry, focusing on the mobility sector, and is a supplier of "dominant" market shares for electric scooter brands in Europe. In the four-wheeled sector, it also provides aluminum profile solutions to high-end automotive brands both domestically and internationally, making it an absolute leader in the niche industry. Current services include aluminum ingot casting, mold design and manufacturing, aluminum profile extrusion, CNC milling and turning, cutting, bending and stamping, surface anodizing and internal high-pressure forming, with a total investment reaching 30 million dollars.
Main Products: Automotive collision beams and spare parts, bicycle/scooter frames
Employee Scale: 500
Production Value: 600-700 million
Industry Position: Deeply engaged in the aluminum products industry, holding authoritative certifications such as ISO9001 and IATF16949. With advanced technology and equipment, it provides high-quality products such as aluminum scooters and automotive collision beams for key industries such as medical, electronics, and transportation, leading the aluminum products subsector in mobility.
Application Industry: Automotive spare parts
Main Markets: Domestic
Downstream Customers: Volvo, Audi, Xiaomi
Production Process: Extrusion / Machining / Aging / Painting / Anodizing
Mindar Product Applications - Automotive
Mindar Product Applications - Bicycle
Showcase of Some Other Products
2. Project Background Introduction
Currently, achieving carbon neutrality has become a global consensus, and major global automobile manufacturers have successively released long-term plans aimed at achieving "decarbonization." According to statistics, there is an urgent demand for lightweight new energy vehicles. For every 10kg reduction in the weight of a pure electric vehicle, the cruising range can increase by 2.5km. The China Society of Automotive Engineering predicts that the aluminum consumption per vehicle will rise from 190kg in 2020 to 350kg in 2030. In addition to the widely used aluminum engine components and aluminum alloys in luxury car bodies, the application rate of aluminum alloys in components such as wheels, bumpers, and hoods is also expanding. In the next decade, the aluminum penetration rate of various automotive components will significantly increase.
Situated in this promising market environment, Mindar Aluminum Technology (Taicang) Co., Ltd., as a leader in the aluminum profiles industry for new energy vehicles, precisely grasps the pulse of the times and boldly sets a strategic goal of "tenfold growth in five years." The arrival of the Internet of Things era has made the transition from digital factories to intelligent factories an irreversible industrial development direction. The three major links of factory operations QCD are particularly important. More and more companies are beginning to explore and attempt to establish intelligent factories to maintain future competitiveness.
The company currently has a wide variety of products, complex processes, and strict requirements for delivery, quality, and cost management. Currently, various process management nodes within the enterprise heavily rely on manual and offline documents, lacking necessary process fail-safes, tracing, and data management:
As business expands, the existing management system struggles to cope with complex business processes. For example, business data and financial data operate independently, creating information silos, resulting in inaccurate cost accounting and decision-making that lacks support. In cooperation projects with important customers, financial data often delays and inaccuracies affect cost control and quoting decisions.
On the other hand, the demand for quality control is urgent, lacking an effective traceability system. In the supply of automotive spare parts, once quality issues arise, it is not possible to quickly locate the source, seriously damaging the company's reputation and customer trust.
Additionally, the execution of processes is chaotic, lacking effective monitoring and standardization mechanisms. Difficulties in departmental coordination lead to low production efficiency and severe resource waste, greatly restricting the company's further development.
💪 To break through the predicament and enhance competitiveness, Mindar Aluminum is initiating a digital transformation project aiming at integrated business finance, precise quality traceability, and standardized process execution.
3. Current Situation
3.1 Workshop Business Process
Information Technology Status
4. Project Blueprint
Optimized Business Process
Full Process Traceability
5. Solution Details
5.1. System Integration
5.1.1 SAP System Integration
Solution Introduction:
The SAP system manages financial data and supply chain, while the new core cloud system focuses on production/quality/equipment/mold and other business data. Through system integration, the goal of integrated and standardized management operations is achieved.
Before Application (BEFORE)
Pain Point 1: No standardized and regulated process management, numerous operational systems, employees repeatedly operate systems, working on multiple accounts, leading to duplicate work and low personnel efficiency.
Pain Point 2: Business data and financial data disjointed, cost data accounting is inaccurate with information silos.
After Application (AFTER)
Value 1: Establish standard management processes with clear workflows, solving the multiple accounts issue, ensuring data is transparent and traceable. Reducing duplicate work greatly improves efficiency.
Value 2: Detailed responsibilities among systems, achieved through interface integration, realizes business-finance integration. Cost and financial accounting data are clear, effectively providing data support for management decisions.
SAP Integration Plan
5.1.2 Weighbridge Integration Plan
Solution Introduction:
Mindar Aluminum integrates the weighbridge system deeply into the production management system through hardware connections and software interactions, ensuring that weight data can be automatically collected and stably transmitted to the management system, achieving efficient data circulation and centralized management.
In the raw material warehousing process, once the vehicle is loaded and weighs on the weighbridge, the system immediately acquires the weight information and records it; during waste material processing, the weighbridge also weighs, strictly standardizing operational processes to ensure data consistency and reliability.
The system is equipped with powerful data storage and convenient query functions, allowing precise tracing of historical weight details for each batch of raw materials and waste material, laying a solid data foundation for enterprise production management and cost accounting.
Before Application (BEFORE)
Manual operation is inefficient and prone to errors: ** Previously, Mindar Aluminum completely relied on manual filling of weighing data, which was cumbersome and extremely inefficient, leading to numerous data errors due to human negligence or fatigue.
Lack of supervision leads to poor data quality: ** Due to lack of effective supervision and verification mechanisms, the reported weighing amounts are severely at risk regarding accuracy and authenticity, making it difficult to control data quality effectively.
Cost accounting chaos from inaccurate data: ** This puts immense risk on the company's cost accounting, as incorrect data can distort the calculations of raw material procurement costs or waste handling revenues, severely interfering with profit assessment and decision-making, affecting the healthy development of the company.
After Application (AFTER)
Automated collection ensures data accuracy: ** After introducing the weighbridge integration system, weighing data is automatically collected. Sensors detect the weight in real-time and transmit it to the system, eliminating the need for manual input, avoiding human errors.
Accurate data enhances cost accounting optimization: ** The precise weighing records generated by the system provide a solid and reliable data foundation for cost accounting, enabling financial personnel to conduct accurate cost calculations and significantly improving the accuracy and scientific nature of cost accounting.
Simplified processes promote efficiency improvements: ** Overall work efficiency sees significant improvements, reducing manual intervention, and making the raw material warehousing and waste processing processes more efficient and smooth, effectively enhancing the level of enterprise operation management.
Scene/Image
Weighbridge Integration
Weight Difference Data
APP Side "Weighbridge"
Weighbridge Business
5.2 Energy Consumption Management
Solution Introduction:
Manually entering equipment production time and output information, collecting electricity meter and gas meter data, calculating daily consumption and equipment unit consumption.
Before Application (BEFORE)
Difficulties in data collection and statistics: The production time and output information of the equipment need to be entered manually, which not only consumes a lot of labor and time but also easily leads to errors, making it difficult to ensure the accuracy and timeliness of data. The data collection of electricity meters and gas meters may lack systematic operation, making it difficult to obtain comprehensive and accurate energy consumption information.
Unclear unit consumption situation: Due to the lack of effective data integration and analysis methods, it is impossible to calculate the unit consumption situation of devices based on production time and output data, making it difficult for the enterprise to understand energy consumption efficiency at each production link and implement energy-saving optimizations.
After Application (AFTER)
Accurate data statistics and analysis: By standardizing the data collection process, it is possible to accurately obtain the production time, output information, as well as electricity meter and gas meter data, and to statistically summarize consumption statistics for day shifts/evening shifts and full days. Combined with production data, calculating equipment unit consumption provides detailed and accurate energy consumption data for enterprises.
Energy-saving optimization decision support: Based on precise energy consumption data and unit consumption analysis, enterprises can identify production links and devices with higher energy consumption, thus formulating targeted energy-saving measures such as equipment upgrades, process improvements, or production scheduling optimizations to reduce production costs and improve energy utilization efficiency, enhancing competitiveness in the market.
Scene/Image
Energy Consumption Data Entry
Energy Consumption Statistics
Production Unit Energy Consumption Data
5.3 Workshop Planning
Solution Introduction:
Enhance extrusion and post-processing workshop planning scheduling efficiency, reduce communication costs between departments, and achieve online office collaboration among relevant business departments;
Daily scheduling data for precise display, multi-material process one-click scheduling, data visualization, effectively tracking planning progress.
Before Application (BEFORE)
Pain Point 1: There are many business units, and different planning basis and standards exist between business units, making it difficult to synchronize information in the scheduling process, causing deviations in planning execution.
Pain Point 2: A wide variety of products and models lead to scattered scheduling data; personnel rely on spreadsheets for statistics, which is time-consuming and labor-intensive, needing to manually transcribe data to create production planning documents for issuing to the workshop.
After Application (AFTER)
Value 1: Advanced workshop planning defines different scheduling rules according to the needs of different business units. For example, extrusion scheduling resources use extrusion equipment as a bottleneck for scheduling, while the post-processing workshop uses either equipment or group as a scheduling basis, effectively displaying the production situation of various processes, facilitating planning execution.
Value 2: The system automatically calculates material requirements based on the process maintained, BOM, standard working hours, etc., to obtain net demand for parts and split daily production numbers. The page content includes: gross demand, inventory, production amounts, net demand, cumulative material gaps, dates; the net demand calculation supports customization, effectively reducing scheduling time. The scheduling plan document is quickly generated and printed with one click, saving time.
Scene/Image
Scheduling Settings
Work Order Planning Document
Planning Scheduling Interface
Transformation Effect: Planning completion rate stabilizes above 98%
🚀 Product material package link:S|Workshop Planning - Professional Version
5.4 Sales Consolidation Management
Solution Introduction:
Production management consolidates small batch scattered orders, stipulating that work orders with the same process route or set within deadline ranges can be consolidated; after consolidation, the original work orders are nullified, and production quantities are accumulated. When distributing work orders, the "Plan Material Area Rounding" function is set to check planned materials, rounding decimals up. At the same time, consolidated report statistics the number of consolidations, process rates, and raw material savings, while displaying the production progress of consolidated orders distributed.
Before Application (BEFORE)
High risk of inventory backlog: The presence of numerous small batch scattered orders can easily lead to inventory accumulation if not consolidated, occupying large amounts of capital and storage space, and increasing inventory management costs and liquidity pressures.
Complex production plans: Numerous small batch scattered orders complicate the production plan, making resource coordination challenging and easily leading to disorganized production arrangements, affecting production efficiency and delivery timelines.
After Application (AFTER)
Reducing inventory pressure: By consolidating small batch scattered orders, effectively avoiding inventory accumulation. Consolidating work orders with the same process route or set within the deadline reduces unnecessary inventory storage, freeing up capital and warehouse space, and lowering inventory management costs.
Simplifying production plans and resource coordination: Consolidation operations simplify production plans, facilitating central resource production and achieving scale; reducing switching times and improving efficiency, equipment utilization, and customer satisfaction. The rounding function and report optimize material provision and assist management decisions.
Image
Production Order Consolidation
Select Consolidation
Consolidation Report
5.5 Full-Process Scanning Management
Solution Introduction:
1. Solving production site transparency through information management MES software that connects various operating environments, for example: the production of extruded semi-finished products; inspection data of aging performance, production preparation, supplementary materials, returning materials, etc.;
2. Production execution control based on processes/models, utilizing technologies like barcodes; accomplishing product process flow record through scanning materials, scanning production orders/flow cards for reporting, scanning for warehousing, binding and printing batch codes for key batches, ensuring products follow established process paths, achieving data collection recording, and process traceability, making the workshop production more transparent and efficient.
3. Ensuring accurate tracing of product information by scanning materials on-site, implementing anti-error management for actual input materials, enhancing the flow efficiency of materials and standardizing material flows.
Before Application (BEFORE)
Pain Point 1: Preparation work before production and inter-departmental coordination rely entirely on offline communications, leading to low efficiency and difficulty in ensuring timeliness and process records.
Pain Point 2: Production reporting relies on offline work cards and is collected by designated personnel, which is time-consuming and labor-intensive.
Pain Point 3: The production process is fragmented, with long production sequences and many types of work in progress, making it challenging to manage the flow of work in progress.
Pain Point 4: Many batches make error-proofing difficult.
After Application (AFTER)
Value 1: Online generation of related documents for production preparation, allowing tighter coordination between departmental work.
Value 2: Employees can report work in real-time by scanning, eliminating traditional work cards, improving reporting efficiency.
Value 3: MES provides reports on work in progress, accurately displaying the quantities and locations of work in progress in each segment. During production, flow receipt functionality is provided, ensuring consistent upstream and downstream transfer and reception quantities, avoiding discrepancies.
Value 4: MES offers full-process scanning support, ensuring first-in-first-out for outbound, proper on-site material input, and clear identification of materials in the workshop.
Image
Production Order
🚀 Product material package link:S | Production Management - Professional Version
5.6 Process Quality Management
5.6.1 IPQC
Solution Introduction:
IPQC focuses on key quality control points in the production process, conducting regular inspections and sampling based on predetermined inspection standards and specifications to monitor processes such as extrusion, aging, stamping, and anodic cleaning in aluminum profile production. It aims to detect and correct any factors that may affect product quality in a timely manner to prevent unqualified products from entering the next process.
Before Application (BEFORE)
Detection lacks standardization: Previously, quality inspections relied on human experience and simple tools for irregular sampling, with limited and non-standard testing items, making it difficult to fully control product quality and resulting in frequent potential quality issues, with defective products flowing into subsequent processes at high risk, seriously impacting overall product quality and corporate reputation.
Difficulties in tracing information chaos: Lack of barcode management leads to scattered paper records of product information, requiring time and effort to organize and search. In responding to customer feedback or factory audits, it is difficult to quickly provide production details and quality data, failing to meet traceability and compliance requirements, leading to customer dissatisfaction and reputational risk.
After Application (AFTER)
Strict testing improves quality: After implementing the IPQC plan, each process test is strictly conducted according to regulations, using advanced inspection equipment and scientific methods, achieving deep control over product quality. It can timely intercept unqualified products, effectively reducing scrap rates and rework rates, significantly enhancing the stability and consistency of product quality, and strengthening the company's market competitiveness.
Convenient tracing enhances credibility: A comprehensive barcode management system enables efficient and accurate product traceability; through scanning or system retrieval, it allows for quick access to complete production information, enabling rapid localization of problem sources during customer feedback and audits, facilitating timely improvements and optimizations, significantly improving customer trust and corporate brand image, promoting sustained and healthy enterprise development.
Production Inspection Standards
Product Inspection Scheme
🚀 Product material package link:S | IPQC
5.6.2 End-to-End Traceability
Solution Introduction:
At Mindar Aluminum, by setting a unique code for each production step and utilizing information technology such as scanning and database storage, the operation information, equipment parameters, operators, timestamps, etc., for processes such as aluminum rod material receipt, extrusion, aging, stamping, and anodized cleaning are recorded in detail and established in relation to each other, achieving precise traceability of the product's entire lifecycle.
Before Application (BEFORE)
Tracing without a way data chaos: Previously, Mindar Aluminum did not have a unified traceability system; the data from the production process was scattered across various departments and paper records, lacking effective integration and management. This led to an inability to quickly and accurately provide relevant information when responding to the traceability demands of automotive customers, severely affecting customer satisfaction and enterprise reputation.
Management is crude and inefficient: Due to non-standard onsite management, the flow of materials and processes lacked strict recording mechanisms, easily leading to production chaos and errors, which not only increased production costs but also reduced production efficiency, hindering the enterprise's development.
After Application (AFTER)
Precision traceability enables quick responses: By scanning the product barcode, the complete production history, including raw material sources and processing details of each process, can be quickly queried in the system, significantly improving the accuracy and timeliness of traceability, effectively meeting the strict requirements of automotive customers for batch traceability and enhancing customer trust in the enterprise.
Standardized management improves efficiency: Standardized onsite management and data recording make the production process more orderly, reducing material waste and production errors. Quality analysis and production optimization are based on accurate traceability data, enhancing production efficiency, lowering costs, and boosting the competitiveness of the enterprise.
Material Tracing by Module
Tracing - Tree Structure Details
🚀 Product material package link:A | Full Process Traceability
5.7 Equipment Management
5.7.1 Equipment Data Collection
Solution Introduction:
1. List the types of data collection devices for machinery and the types of data.
2. Key equipment collects production process parameters, monitors parameter changes in real-time, alarms when out of limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large equipment quantity, there is no unified platform for management, and data maintenance is difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure the timeliness of employee execution; data storage and querying are cumbersome.
Pain Point 3: Employees need to periodically transcribe the production parameters and inspect for anomalies, increasing unnecessary work volume.
Pain Point 4: When anomalies occur on-site, communication happens through offline phone or WeChat, resulting in high communication costs and inaccurate task assignment, leading to chaotic management without data to assess equipment maintenance efficiency.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system automatically generates corresponding reports based on completed inspections and maintenance, providing a basis for data analysis for managers.
Value 3: Real-time collection of production parameter information from equipment, setting parameter upper and lower limits, with automatic alarms for exceeding limits to relevant personnel for timely processing, enhancing problem handling efficiency.
Value 4: Establishing an anomaly reporting mechanism allows frontline employees to quickly report problems when they occur, the system automatically assigning corresponding personnel for timely handling, and automatically collecting data to statistically assess equipment failure indicators, evaluating the efficiency and capability of maintenance personnel.
Equipment Status Monitoring
Equipment Parameter Monitoring
Equipment Status Dashboard
5.7.2 Preventive Maintenance of Equipment
Solution Introduction:
1. Establish a complete inspection/maintenance plan for equipment, achieving task formulation, distribution, reminders, and execution of inspections/maintenance. Effectively preventing anomalies during processing and ensuring equipment stability.
2. Key equipment collects production process parameters and monitors parameter changes in real-time, with alarms for exceeding limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large quantity of equipment, there is no unified platform for management, making data maintenance difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure timeliness; data storage and querying are inconvenient.
Pain Point 3: Employees need to periodically transcribe production process parameters and inspect for anomalies, raising unnecessary work volume.
Pain Point 4: Anomalies occurring on-site result in high communication costs without a structured method for proper task assignment; management is chaotic, lacking data to assess equipment maintenance effectiveness.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system generates corresponding reports based on completed inspections and maintenance, providing data analysis support for managers.
Value 3: Real-time collection of production parameters from equipment, establishing upper and lower limits, with automatic alarms for exceeding limits to deal promptly with issues.
Value 4: An anomaly reporting mechanism is established, allowing frontline employees to quickly report when problems occur and automatically assigning corresponding personnel to address issues, while collecting and statistically analyzing equipment failure information for efficiency assessments.
Equipment Log
Daily Equipment Inspection
Equipment Parameters
Equipment Alerts
Equipment Anomaly Handling
APP Execution of Inspection Operations
🚀 Product material package link:A | Preventive Maintenance of Equipment
5.7.3 Equipment OEE
Solution Introduction:
1. Based on management operation indicators set by the enterprise, decompose from top to bottom, completing business processes for data collection, with automatic generation of KPI management reports by the system.
2. Analyze the issues based on KPI results, implement improvements on-site, confirm improvement effects, completing PDCA cycle improvements.
Before Application (BEFORE)
Pain Point 1: Basic data collection is manually compiled with low value and high workload.
Pain Point 2: Manual data collection cannot guarantee data authenticity and timeliness.
After Application (AFTER)
Value 1: Real-time collection of real accurate data through business processes, eliminating manual recording methods.
Value 2: The system automatically generates performance management reports.
Process Parameters
KPI Management Reports
🚀 Product material package link:A | OEE of Equipment Analysis
5.7.4 Task Management
Solution Introduction:
Assisting in arranging labor hours: Display "Labor Hours" in the task order and production order operation view, calculated by the formula "Labor Hours = Task Order Planned Quantity × CT," providing a reference for on-site personnel resource allocation to ensure labor input matches production tasks.
Verification for personnel assignment and machine approval: During secondary assignments, check the number of personnel at workstations, ensuring it does not exceed the process set value, prioritizing personnel or groups maintained by the process work center, to ensure reasonable and efficient personnel allocation and avoid waste. Additionally clarifying operating processes under different allocation scenarios, such as direct assignment without splitting sub-tasks and simultaneous assignment of split sub-tasks.
Before Application (BEFORE)
Personnel allocation is chaotic: On-site personnel distribution lacks effective standards and verification mechanisms, easily leading to over or under allocation in certain processes, resulting in wasted human resources or delays in production tasks, reducing production efficiency.
Low production efficiency: As ineffective matching of personnel and processes may lead to slow progress in some processes due to insufficient personnel while others are underutilized, disrupting the overall production rhythm and affecting product output speed and enterprise benefits.
After Application (AFTER)
Optimizing resource utilization: Accurate personnel and equipment allocation based on process requirements and production tasks avoids wastage of human resources, increasing equipment utilization, leading to more scientifically rational resource allocation in the production process.
Enhancing production efficiency: Ensuring an appropriate number of personnel operate at each process, guaranteeing smooth production flow and decreasing production interruptions and delays caused by personnel issues, effectively improving overall production efficiency and helping the enterprise meet production tasks on time, enhancing market competitiveness.
Arranging Human Resources
Labor Hours = Planned Quantity of Task Order M * CT
🚀 Product material package link:Secondary Assignment
5.7.5 Workstation OEE
Solution Introduction:
Calculating OEE at the workstation level to assist on-site management and increase production efficiency.
OEE = (Net Production Time / Actual Production Time) * (UPH(a) / UPH(p)) * (Qualified Count / Total Reporting Count)
Actual Production Time: Manually clicking start to completion of task reporting
Net Production Time: Actual Production Time - Planned Losses - Equipment Anomaly Losses - Waiting Material Anomalies - Others (e.g., quality pulls or material defects)
UPH(a) = Total Reporting Count / Net Production Time
UPH(p) = Standard Working Time (Processing time maintained within process routes)
Qualified Count: Qualified items within Total Reporting Count, defaults to qualified if inspection results are not available
Total Reporting Count: Total reporting count within the Actual Production Time range
Before Application (BEFORE)
Missing efficiency assessments: Enterprises find it difficult to accurately measure each workstation's actual efficiency performance during production, making it challenging to identify sources of time waste, speed discrepancies, and quality issues during production processes, leading to ineffective improvements.
Management decisions lack scientific basis: Due to the absence of accurate efficiency data, adjustments to production plans, resource allocations, and equipment maintenance often lack well-founded evidence, resulting in resource waste and delays in production.
After Application (AFTER)
Precise efficiency analysis: OEE calculations provide clear insights into utilization of time, production speed, and product quality at each workstation, helping enterprises accurately identify production bottlenecks and inefficient segments.
Optimizing production management: Based on OEE data, targeted improvement measures can be established, such as optimizing equipment maintenance plans, adjusting personnel allocations, and improving production processes, thereby enhancing overall production efficiency, reducing production costs, and increasing enterprise competitiveness.
Details of Equipment OEE
🚀 Product material package link:Equipment OEE Optimization
5.8 KPI Management
5.8.1 Production Plan Achievement Rate
Report/Dashboard Introduction
Visually presents the completion progress of production plans, allowing management to quickly understand whether production tasks are proceeding as planned, for instance, a 70.66% achievement rate can directly reflect the current execution status of production plans and adjust production strategies timely, ensuring the achievement of production goals.
Production Plan Achievement Rate
🚀 Product material package link:B | Production Achievement Rate
5.8.2 Production Process PPM
Report/Dashboard Introduction
The production process PPM report measures quality levels in production processes by displaying PPM report numbers, trends, and summaries, based on the quantity of defects per million products, helping enterprises identify high-frequency quality issues in production segments and provide direction for quality improvements.
Production Process PPM
🚀 Product material package link:B | Production Process Defective PPM
5.8.3 First Pass Yield
Report/Dashboard Introduction
Displays first pass rates from multiple dimensions such as inspection dates, business units, workshops, etc. Detailed inspection and testing data enables enterprises to analyze the stability of production quality across different segments and departments, taking targeted measures to improve the overall yield.
First Pass Yield
🚀 Product material package link:B | FPY First Pass Yield
5.8.4 Quality Defect Analysis
Report/Dashboard Introduction
Lists failure counts, times, defect rates, etc., aiding enterprises in thoroughly analyzing the sources of quality defects, such as equipment failures, process issues, or human factors, thus effectively guiding enterprises in quality improvements and equipment maintenance to enhance product quality.
Quality Defect Analysis
🚀 Product material package link:A | Equipment OEE Analysis
5.8.5 Management Dashboard
Report/Dashboard Introduction
The management dashboard displays daily and next day's planned tasks, quality anomalies, personnel status (red idle, yellow slow, green normal), with functions for prior work warning (10 minutes early) and alarms (15 minutes delayed reporting), helping managers control production progress, quality, and personnel efficiency.
OEE Management Console Dashboard
1. Customer Description Card
Minta Aluminum Technology (Taicang) Co., Ltd. was established in 1953 and has firmly established itself in the metal manufacturing industry for over half a century through continuous efforts, starting with providing customers with post-processing services for steel pipes. With the trends of the times, aluminum has gradually replaced steel and chromium-molybdenum steel due to its material advantages. In order to provide customers with more comprehensive services, Mindar officially transitioned to the aluminum profile industry in 2000. In the past decade, it has successfully conducted vertical integration in the aluminum profile industry, focusing on the mobility sector, and is a supplier of "dominant" market shares for electric scooter brands in Europe. In the four-wheeled sector, it also provides aluminum profile solutions to high-end automotive brands both domestically and internationally, making it an absolute leader in the niche industry. Current services include aluminum ingot casting, mold design and manufacturing, aluminum profile extrusion, CNC milling and turning, cutting, bending and stamping, surface anodizing and internal high-pressure forming, with a total investment reaching 30 million dollars.
Main Products: Automotive collision beams and spare parts, bicycle/scooter frames
Employee Scale: 500
Production Value: 600-700 million
Industry Position: Deeply engaged in the aluminum products industry, holding authoritative certifications such as ISO9001 and IATF16949. With advanced technology and equipment, it provides high-quality products such as aluminum scooters and automotive collision beams for key industries such as medical, electronics, and transportation, leading the aluminum products subsector in mobility.
Application Industry: Automotive spare parts
Main Markets: Domestic
Downstream Customers: Volvo, Audi, Xiaomi
Production Process: Extrusion / Machining / Aging / Painting / Anodizing
Mindar Product Applications - Automotive
Mindar Product Applications - Bicycle
Showcase of Some Other Products
2. Project Background Introduction
Currently, achieving carbon neutrality has become a global consensus, and major global automobile manufacturers have successively released long-term plans aimed at achieving "decarbonization." According to statistics, there is an urgent demand for lightweight new energy vehicles. For every 10kg reduction in the weight of a pure electric vehicle, the cruising range can increase by 2.5km. The China Society of Automotive Engineering predicts that the aluminum consumption per vehicle will rise from 190kg in 2020 to 350kg in 2030. In addition to the widely used aluminum engine components and aluminum alloys in luxury car bodies, the application rate of aluminum alloys in components such as wheels, bumpers, and hoods is also expanding. In the next decade, the aluminum penetration rate of various automotive components will significantly increase.
Situated in this promising market environment, Mindar Aluminum Technology (Taicang) Co., Ltd., as a leader in the aluminum profiles industry for new energy vehicles, precisely grasps the pulse of the times and boldly sets a strategic goal of "tenfold growth in five years." The arrival of the Internet of Things era has made the transition from digital factories to intelligent factories an irreversible industrial development direction. The three major links of factory operations QCD are particularly important. More and more companies are beginning to explore and attempt to establish intelligent factories to maintain future competitiveness.
The company currently has a wide variety of products, complex processes, and strict requirements for delivery, quality, and cost management. Currently, various process management nodes within the enterprise heavily rely on manual and offline documents, lacking necessary process fail-safes, tracing, and data management:
As business expands, the existing management system struggles to cope with complex business processes. For example, business data and financial data operate independently, creating information silos, resulting in inaccurate cost accounting and decision-making that lacks support. In cooperation projects with important customers, financial data often delays and inaccuracies affect cost control and quoting decisions.
On the other hand, the demand for quality control is urgent, lacking an effective traceability system. In the supply of automotive spare parts, once quality issues arise, it is not possible to quickly locate the source, seriously damaging the company's reputation and customer trust.
Additionally, the execution of processes is chaotic, lacking effective monitoring and standardization mechanisms. Difficulties in departmental coordination lead to low production efficiency and severe resource waste, greatly restricting the company's further development.
💪 To break through the predicament and enhance competitiveness, Mindar Aluminum is initiating a digital transformation project aiming at integrated business finance, precise quality traceability, and standardized process execution.
3. Current Situation
3.1 Workshop Business Process
Information Technology Status
4. Project Blueprint
Optimized Business Process
Full Process Traceability
5. Solution Details
5.1. System Integration
5.1.1 SAP System Integration
Solution Introduction:
The SAP system manages financial data and supply chain, while the new core cloud system focuses on production/quality/equipment/mold and other business data. Through system integration, the goal of integrated and standardized management operations is achieved.
Before Application (BEFORE)
Pain Point 1: No standardized and regulated process management, numerous operational systems, employees repeatedly operate systems, working on multiple accounts, leading to duplicate work and low personnel efficiency.
Pain Point 2: Business data and financial data disjointed, cost data accounting is inaccurate with information silos.
After Application (AFTER)
Value 1: Establish standard management processes with clear workflows, solving the multiple accounts issue, ensuring data is transparent and traceable. Reducing duplicate work greatly improves efficiency.
Value 2: Detailed responsibilities among systems, achieved through interface integration, realizes business-finance integration. Cost and financial accounting data are clear, effectively providing data support for management decisions.
SAP Integration Plan
5.1.2 Weighbridge Integration Plan
Solution Introduction:
Mindar Aluminum integrates the weighbridge system deeply into the production management system through hardware connections and software interactions, ensuring that weight data can be automatically collected and stably transmitted to the management system, achieving efficient data circulation and centralized management.
In the raw material warehousing process, once the vehicle is loaded and weighs on the weighbridge, the system immediately acquires the weight information and records it; during waste material processing, the weighbridge also weighs, strictly standardizing operational processes to ensure data consistency and reliability.
The system is equipped with powerful data storage and convenient query functions, allowing precise tracing of historical weight details for each batch of raw materials and waste material, laying a solid data foundation for enterprise production management and cost accounting.
Before Application (BEFORE)
Manual operation is inefficient and prone to errors: ** Previously, Mindar Aluminum completely relied on manual filling of weighing data, which was cumbersome and extremely inefficient, leading to numerous data errors due to human negligence or fatigue.
Lack of supervision leads to poor data quality: ** Due to lack of effective supervision and verification mechanisms, the reported weighing amounts are severely at risk regarding accuracy and authenticity, making it difficult to control data quality effectively.
Cost accounting chaos from inaccurate data: ** This puts immense risk on the company's cost accounting, as incorrect data can distort the calculations of raw material procurement costs or waste handling revenues, severely interfering with profit assessment and decision-making, affecting the healthy development of the company.
After Application (AFTER)
Automated collection ensures data accuracy: ** After introducing the weighbridge integration system, weighing data is automatically collected. Sensors detect the weight in real-time and transmit it to the system, eliminating the need for manual input, avoiding human errors.
Accurate data enhances cost accounting optimization: ** The precise weighing records generated by the system provide a solid and reliable data foundation for cost accounting, enabling financial personnel to conduct accurate cost calculations and significantly improving the accuracy and scientific nature of cost accounting.
Simplified processes promote efficiency improvements: ** Overall work efficiency sees significant improvements, reducing manual intervention, and making the raw material warehousing and waste processing processes more efficient and smooth, effectively enhancing the level of enterprise operation management.
Scene/Image
Weighbridge Integration
Weight Difference Data
APP Side "Weighbridge"
Weighbridge Business
5.2 Energy Consumption Management
Solution Introduction:
Manually entering equipment production time and output information, collecting electricity meter and gas meter data, calculating daily consumption and equipment unit consumption.
Before Application (BEFORE)
Difficulties in data collection and statistics: The production time and output information of the equipment need to be entered manually, which not only consumes a lot of labor and time but also easily leads to errors, making it difficult to ensure the accuracy and timeliness of data. The data collection of electricity meters and gas meters may lack systematic operation, making it difficult to obtain comprehensive and accurate energy consumption information.
Unclear unit consumption situation: Due to the lack of effective data integration and analysis methods, it is impossible to calculate the unit consumption situation of devices based on production time and output data, making it difficult for the enterprise to understand energy consumption efficiency at each production link and implement energy-saving optimizations.
After Application (AFTER)
Accurate data statistics and analysis: By standardizing the data collection process, it is possible to accurately obtain the production time, output information, as well as electricity meter and gas meter data, and to statistically summarize consumption statistics for day shifts/evening shifts and full days. Combined with production data, calculating equipment unit consumption provides detailed and accurate energy consumption data for enterprises.
Energy-saving optimization decision support: Based on precise energy consumption data and unit consumption analysis, enterprises can identify production links and devices with higher energy consumption, thus formulating targeted energy-saving measures such as equipment upgrades, process improvements, or production scheduling optimizations to reduce production costs and improve energy utilization efficiency, enhancing competitiveness in the market.
Scene/Image
Energy Consumption Data Entry
Energy Consumption Statistics
Production Unit Energy Consumption Data
5.3 Workshop Planning
Solution Introduction:
Enhance extrusion and post-processing workshop planning scheduling efficiency, reduce communication costs between departments, and achieve online office collaboration among relevant business departments;
Daily scheduling data for precise display, multi-material process one-click scheduling, data visualization, effectively tracking planning progress.
Before Application (BEFORE)
Pain Point 1: There are many business units, and different planning basis and standards exist between business units, making it difficult to synchronize information in the scheduling process, causing deviations in planning execution.
Pain Point 2: A wide variety of products and models lead to scattered scheduling data; personnel rely on spreadsheets for statistics, which is time-consuming and labor-intensive, needing to manually transcribe data to create production planning documents for issuing to the workshop.
After Application (AFTER)
Value 1: Advanced workshop planning defines different scheduling rules according to the needs of different business units. For example, extrusion scheduling resources use extrusion equipment as a bottleneck for scheduling, while the post-processing workshop uses either equipment or group as a scheduling basis, effectively displaying the production situation of various processes, facilitating planning execution.
Value 2: The system automatically calculates material requirements based on the process maintained, BOM, standard working hours, etc., to obtain net demand for parts and split daily production numbers. The page content includes: gross demand, inventory, production amounts, net demand, cumulative material gaps, dates; the net demand calculation supports customization, effectively reducing scheduling time. The scheduling plan document is quickly generated and printed with one click, saving time.
Scene/Image
Scheduling Settings
Work Order Planning Document
Planning Scheduling Interface
Transformation Effect: Planning completion rate stabilizes above 98%
🚀 Product material package link:S|Workshop Planning - Professional Version
5.4 Sales Consolidation Management
Solution Introduction:
Production management consolidates small batch scattered orders, stipulating that work orders with the same process route or set within deadline ranges can be consolidated; after consolidation, the original work orders are nullified, and production quantities are accumulated. When distributing work orders, the "Plan Material Area Rounding" function is set to check planned materials, rounding decimals up. At the same time, consolidated report statistics the number of consolidations, process rates, and raw material savings, while displaying the production progress of consolidated orders distributed.
Before Application (BEFORE)
High risk of inventory backlog: The presence of numerous small batch scattered orders can easily lead to inventory accumulation if not consolidated, occupying large amounts of capital and storage space, and increasing inventory management costs and liquidity pressures.
Complex production plans: Numerous small batch scattered orders complicate the production plan, making resource coordination challenging and easily leading to disorganized production arrangements, affecting production efficiency and delivery timelines.
After Application (AFTER)
Reducing inventory pressure: By consolidating small batch scattered orders, effectively avoiding inventory accumulation. Consolidating work orders with the same process route or set within the deadline reduces unnecessary inventory storage, freeing up capital and warehouse space, and lowering inventory management costs.
Simplifying production plans and resource coordination: Consolidation operations simplify production plans, facilitating central resource production and achieving scale; reducing switching times and improving efficiency, equipment utilization, and customer satisfaction. The rounding function and report optimize material provision and assist management decisions.
Image
Production Order Consolidation
Select Consolidation
Consolidation Report
5.5 Full-Process Scanning Management
Solution Introduction:
1. Solving production site transparency through information management MES software that connects various operating environments, for example: the production of extruded semi-finished products; inspection data of aging performance, production preparation, supplementary materials, returning materials, etc.;
2. Production execution control based on processes/models, utilizing technologies like barcodes; accomplishing product process flow record through scanning materials, scanning production orders/flow cards for reporting, scanning for warehousing, binding and printing batch codes for key batches, ensuring products follow established process paths, achieving data collection recording, and process traceability, making the workshop production more transparent and efficient.
3. Ensuring accurate tracing of product information by scanning materials on-site, implementing anti-error management for actual input materials, enhancing the flow efficiency of materials and standardizing material flows.
Before Application (BEFORE)
Pain Point 1: Preparation work before production and inter-departmental coordination rely entirely on offline communications, leading to low efficiency and difficulty in ensuring timeliness and process records.
Pain Point 2: Production reporting relies on offline work cards and is collected by designated personnel, which is time-consuming and labor-intensive.
Pain Point 3: The production process is fragmented, with long production sequences and many types of work in progress, making it challenging to manage the flow of work in progress.
Pain Point 4: Many batches make error-proofing difficult.
After Application (AFTER)
Value 1: Online generation of related documents for production preparation, allowing tighter coordination between departmental work.
Value 2: Employees can report work in real-time by scanning, eliminating traditional work cards, improving reporting efficiency.
Value 3: MES provides reports on work in progress, accurately displaying the quantities and locations of work in progress in each segment. During production, flow receipt functionality is provided, ensuring consistent upstream and downstream transfer and reception quantities, avoiding discrepancies.
Value 4: MES offers full-process scanning support, ensuring first-in-first-out for outbound, proper on-site material input, and clear identification of materials in the workshop.
Image
Production Order
🚀 Product material package link:S | Production Management - Professional Version
5.6 Process Quality Management
5.6.1 IPQC
Solution Introduction:
IPQC focuses on key quality control points in the production process, conducting regular inspections and sampling based on predetermined inspection standards and specifications to monitor processes such as extrusion, aging, stamping, and anodic cleaning in aluminum profile production. It aims to detect and correct any factors that may affect product quality in a timely manner to prevent unqualified products from entering the next process.
Before Application (BEFORE)
Detection lacks standardization: Previously, quality inspections relied on human experience and simple tools for irregular sampling, with limited and non-standard testing items, making it difficult to fully control product quality and resulting in frequent potential quality issues, with defective products flowing into subsequent processes at high risk, seriously impacting overall product quality and corporate reputation.
Difficulties in tracing information chaos: Lack of barcode management leads to scattered paper records of product information, requiring time and effort to organize and search. In responding to customer feedback or factory audits, it is difficult to quickly provide production details and quality data, failing to meet traceability and compliance requirements, leading to customer dissatisfaction and reputational risk.
After Application (AFTER)
Strict testing improves quality: After implementing the IPQC plan, each process test is strictly conducted according to regulations, using advanced inspection equipment and scientific methods, achieving deep control over product quality. It can timely intercept unqualified products, effectively reducing scrap rates and rework rates, significantly enhancing the stability and consistency of product quality, and strengthening the company's market competitiveness.
Convenient tracing enhances credibility: A comprehensive barcode management system enables efficient and accurate product traceability; through scanning or system retrieval, it allows for quick access to complete production information, enabling rapid localization of problem sources during customer feedback and audits, facilitating timely improvements and optimizations, significantly improving customer trust and corporate brand image, promoting sustained and healthy enterprise development.
Production Inspection Standards
Product Inspection Scheme
🚀 Product material package link:S | IPQC
5.6.2 End-to-End Traceability
Solution Introduction:
At Mindar Aluminum, by setting a unique code for each production step and utilizing information technology such as scanning and database storage, the operation information, equipment parameters, operators, timestamps, etc., for processes such as aluminum rod material receipt, extrusion, aging, stamping, and anodized cleaning are recorded in detail and established in relation to each other, achieving precise traceability of the product's entire lifecycle.
Before Application (BEFORE)
Tracing without a way data chaos: Previously, Mindar Aluminum did not have a unified traceability system; the data from the production process was scattered across various departments and paper records, lacking effective integration and management. This led to an inability to quickly and accurately provide relevant information when responding to the traceability demands of automotive customers, severely affecting customer satisfaction and enterprise reputation.
Management is crude and inefficient: Due to non-standard onsite management, the flow of materials and processes lacked strict recording mechanisms, easily leading to production chaos and errors, which not only increased production costs but also reduced production efficiency, hindering the enterprise's development.
After Application (AFTER)
Precision traceability enables quick responses: By scanning the product barcode, the complete production history, including raw material sources and processing details of each process, can be quickly queried in the system, significantly improving the accuracy and timeliness of traceability, effectively meeting the strict requirements of automotive customers for batch traceability and enhancing customer trust in the enterprise.
Standardized management improves efficiency: Standardized onsite management and data recording make the production process more orderly, reducing material waste and production errors. Quality analysis and production optimization are based on accurate traceability data, enhancing production efficiency, lowering costs, and boosting the competitiveness of the enterprise.
Material Tracing by Module
Tracing - Tree Structure Details
🚀 Product material package link:A | Full Process Traceability
5.7 Equipment Management
5.7.1 Equipment Data Collection
Solution Introduction:
1. List the types of data collection devices for machinery and the types of data.
2. Key equipment collects production process parameters, monitors parameter changes in real-time, alarms when out of limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large equipment quantity, there is no unified platform for management, and data maintenance is difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure the timeliness of employee execution; data storage and querying are cumbersome.
Pain Point 3: Employees need to periodically transcribe the production parameters and inspect for anomalies, increasing unnecessary work volume.
Pain Point 4: When anomalies occur on-site, communication happens through offline phone or WeChat, resulting in high communication costs and inaccurate task assignment, leading to chaotic management without data to assess equipment maintenance efficiency.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system automatically generates corresponding reports based on completed inspections and maintenance, providing a basis for data analysis for managers.
Value 3: Real-time collection of production parameter information from equipment, setting parameter upper and lower limits, with automatic alarms for exceeding limits to relevant personnel for timely processing, enhancing problem handling efficiency.
Value 4: Establishing an anomaly reporting mechanism allows frontline employees to quickly report problems when they occur, the system automatically assigning corresponding personnel for timely handling, and automatically collecting data to statistically assess equipment failure indicators, evaluating the efficiency and capability of maintenance personnel.
Equipment Status Monitoring
Equipment Parameter Monitoring
Equipment Status Dashboard
5.7.2 Preventive Maintenance of Equipment
Solution Introduction:
1. Establish a complete inspection/maintenance plan for equipment, achieving task formulation, distribution, reminders, and execution of inspections/maintenance. Effectively preventing anomalies during processing and ensuring equipment stability.
2. Key equipment collects production process parameters and monitors parameter changes in real-time, with alarms for exceeding limits, ensuring product quality.
Before Application (BEFORE)
Pain Point 1: Over 460 equipment in total, with 420 related to production; inspection and maintenance records are managed offline. With such a large quantity of equipment, there is no unified platform for management, making data maintenance difficult.
Pain Point 2: Manual paper records for inspections and maintenance fail to ensure timeliness; data storage and querying are inconvenient.
Pain Point 3: Employees need to periodically transcribe production process parameters and inspect for anomalies, raising unnecessary work volume.
Pain Point 4: Anomalies occurring on-site result in high communication costs without a structured method for proper task assignment; management is chaotic, lacking data to assess equipment maintenance effectiveness.
After Application (AFTER)
Value 1: The MES system automatically generates inspection tasks based on inspection/maintenance rules, allowing employees to quickly execute inspection tasks. Inspection data is transparent and can be quickly queried.
Value 2: The system generates corresponding reports based on completed inspections and maintenance, providing data analysis support for managers.
Value 3: Real-time collection of production parameters from equipment, establishing upper and lower limits, with automatic alarms for exceeding limits to deal promptly with issues.
Value 4: An anomaly reporting mechanism is established, allowing frontline employees to quickly report when problems occur and automatically assigning corresponding personnel to address issues, while collecting and statistically analyzing equipment failure information for efficiency assessments.
Equipment Log
Daily Equipment Inspection
Equipment Parameters
Equipment Alerts
Equipment Anomaly Handling
APP Execution of Inspection Operations
🚀 Product material package link:A | Preventive Maintenance of Equipment
5.7.3 Equipment OEE
Solution Introduction:
1. Based on management operation indicators set by the enterprise, decompose from top to bottom, completing business processes for data collection, with automatic generation of KPI management reports by the system.
2. Analyze the issues based on KPI results, implement improvements on-site, confirm improvement effects, completing PDCA cycle improvements.
Before Application (BEFORE)
Pain Point 1: Basic data collection is manually compiled with low value and high workload.
Pain Point 2: Manual data collection cannot guarantee data authenticity and timeliness.
After Application (AFTER)
Value 1: Real-time collection of real accurate data through business processes, eliminating manual recording methods.
Value 2: The system automatically generates performance management reports.
Process Parameters
KPI Management Reports
🚀 Product material package link:A | OEE of Equipment Analysis
5.7.4 Task Management
Solution Introduction:
Assisting in arranging labor hours: Display "Labor Hours" in the task order and production order operation view, calculated by the formula "Labor Hours = Task Order Planned Quantity × CT," providing a reference for on-site personnel resource allocation to ensure labor input matches production tasks.
Verification for personnel assignment and machine approval: During secondary assignments, check the number of personnel at workstations, ensuring it does not exceed the process set value, prioritizing personnel or groups maintained by the process work center, to ensure reasonable and efficient personnel allocation and avoid waste. Additionally clarifying operating processes under different allocation scenarios, such as direct assignment without splitting sub-tasks and simultaneous assignment of split sub-tasks.
Before Application (BEFORE)
Personnel allocation is chaotic: On-site personnel distribution lacks effective standards and verification mechanisms, easily leading to over or under allocation in certain processes, resulting in wasted human resources or delays in production tasks, reducing production efficiency.
Low production efficiency: As ineffective matching of personnel and processes may lead to slow progress in some processes due to insufficient personnel while others are underutilized, disrupting the overall production rhythm and affecting product output speed and enterprise benefits.
After Application (AFTER)
Optimizing resource utilization: Accurate personnel and equipment allocation based on process requirements and production tasks avoids wastage of human resources, increasing equipment utilization, leading to more scientifically rational resource allocation in the production process.
Enhancing production efficiency: Ensuring an appropriate number of personnel operate at each process, guaranteeing smooth production flow and decreasing production interruptions and delays caused by personnel issues, effectively improving overall production efficiency and helping the enterprise meet production tasks on time, enhancing market competitiveness.
Arranging Human Resources
Labor Hours = Planned Quantity of Task Order M * CT
🚀 Product material package link:Secondary Assignment
5.7.5 Workstation OEE
Solution Introduction:
Calculating OEE at the workstation level to assist on-site management and increase production efficiency.
OEE = (Net Production Time / Actual Production Time) * (UPH(a) / UPH(p)) * (Qualified Count / Total Reporting Count)
Actual Production Time: Manually clicking start to completion of task reporting
Net Production Time: Actual Production Time - Planned Losses - Equipment Anomaly Losses - Waiting Material Anomalies - Others (e.g., quality pulls or material defects)
UPH(a) = Total Reporting Count / Net Production Time
UPH(p) = Standard Working Time (Processing time maintained within process routes)
Qualified Count: Qualified items within Total Reporting Count, defaults to qualified if inspection results are not available
Total Reporting Count: Total reporting count within the Actual Production Time range
Before Application (BEFORE)
Missing efficiency assessments: Enterprises find it difficult to accurately measure each workstation's actual efficiency performance during production, making it challenging to identify sources of time waste, speed discrepancies, and quality issues during production processes, leading to ineffective improvements.
Management decisions lack scientific basis: Due to the absence of accurate efficiency data, adjustments to production plans, resource allocations, and equipment maintenance often lack well-founded evidence, resulting in resource waste and delays in production.
After Application (AFTER)
Precise efficiency analysis: OEE calculations provide clear insights into utilization of time, production speed, and product quality at each workstation, helping enterprises accurately identify production bottlenecks and inefficient segments.
Optimizing production management: Based on OEE data, targeted improvement measures can be established, such as optimizing equipment maintenance plans, adjusting personnel allocations, and improving production processes, thereby enhancing overall production efficiency, reducing production costs, and increasing enterprise competitiveness.
Details of Equipment OEE
🚀 Product material package link:Equipment OEE Optimization
5.8 KPI Management
5.8.1 Production Plan Achievement Rate
Report/Dashboard Introduction
Visually presents the completion progress of production plans, allowing management to quickly understand whether production tasks are proceeding as planned, for instance, a 70.66% achievement rate can directly reflect the current execution status of production plans and adjust production strategies timely, ensuring the achievement of production goals.
Production Plan Achievement Rate
🚀 Product material package link:B | Production Achievement Rate
5.8.2 Production Process PPM
Report/Dashboard Introduction
The production process PPM report measures quality levels in production processes by displaying PPM report numbers, trends, and summaries, based on the quantity of defects per million products, helping enterprises identify high-frequency quality issues in production segments and provide direction for quality improvements.
Production Process PPM
🚀 Product material package link:B | Production Process Defective PPM
5.8.3 First Pass Yield
Report/Dashboard Introduction
Displays first pass rates from multiple dimensions such as inspection dates, business units, workshops, etc. Detailed inspection and testing data enables enterprises to analyze the stability of production quality across different segments and departments, taking targeted measures to improve the overall yield.
First Pass Yield
🚀 Product material package link:B | FPY First Pass Yield
5.8.4 Quality Defect Analysis
Report/Dashboard Introduction
Lists failure counts, times, defect rates, etc., aiding enterprises in thoroughly analyzing the sources of quality defects, such as equipment failures, process issues, or human factors, thus effectively guiding enterprises in quality improvements and equipment maintenance to enhance product quality.
Quality Defect Analysis
🚀 Product material package link:A | Equipment OEE Analysis
5.8.5 Management Dashboard
Report/Dashboard Introduction
The management dashboard displays daily and next day's planned tasks, quality anomalies, personnel status (red idle, yellow slow, green normal), with functions for prior work warning (10 minutes early) and alarms (15 minutes delayed reporting), helping managers control production progress, quality, and personnel efficiency.
OEE Management Console Dashboard
