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Achieving Zero Defects: Key Applications of Precise Traceability in the Automotive Industry
Page View Time 2024-10-11

Recently, BMW issued a recall announcement in the Chinese market, involving various models from imports and Brilliance BMW, totaling approximately 360,000 delivered vehicles. The reason for the recall was a quality defect in the integrated brake booster (DSCi). Some media outlets estimate that BMW’s recall costs for the third quarter of this year could reach up to $300 million.


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Such incidents remind us of the critical importance of product quality control and traceability in the automotive industry. For first- and second-tier suppliers, ensuring high-quality product delivery and avoiding recall events has become key to survival and competitiveness.

 

As the automotive industry evolves toward electrification and intelligent systems, the complexity of components and product quality requirements continue to rise, making traditional batch traceability inadequate for fine management. Precise traceability, a key function of the LinkedData MES system, is designed to address this challenge. It enhances the transparency of product quality control and helps companies achieve higher efficiency and fewer errors in production management and quality control through meticulous traceability granularity.

 

What is Precise Traceability?

 

Precise traceability is an essential component of the LinkedData MES system that enables comprehensive monitoring of the entire production process. Unlike traditional batch traceability, precise traceability focuses on detailed tracking and recording of individual products.


 與傳統(tǒng)的批次追溯相比,精準(zhǔn)追溯側(cè)重于對(duì)單件產(chǎn)品的詳細(xì)追蹤和記錄。


Specifically, precise traceability can be understood from the following aspects:

 

     1.  Refined Traceability Granularity

The precise traceability function of LinkedData can trace each individual product. Every product’s production stages, raw material sources, process flows, and quality inspection data can be meticulously recorded. This individual-level traceability allows for quicker and more accurate identification of defective products when issues arise, preventing large-scale recalls.

     2.  Completeness of Traceability Information

Precise traceability records not only the production time and equipment of a product but also includes information about the operators, raw material sources, process parameters, quality inspection data, and production environmental conditions. This data forms a complete traceability chain, assisting companies in conducting thorough quality control reviews.

全要素追溯

     3.  Data Completeness and Usability

Supported by LinkedData MES, the precise traceability function ensures that each product’s traceability information during the production process is complete and usable. If a product fails to generate complete traceability data, the system will automatically prevent that product from advancing to the next production stage, thereby averting further production or delivery of non-conforming products.

 

Applications of Precise Traceability

 

In the automotive industry, the precise traceability function aids in comprehensive management from the initial production phase to final product delivery, ensuring production quality. Specific application scenarios include:

 

     1.  Reverse Traceability

When a quality issue arises with a vehicle or component in the market, the precise traceability function can quickly locate the product’s production date, production line, operators, and raw material batch information through the traceability code in the LinkedData MES. This reverse traceability capability allows companies to respond swiftly to issues, reducing the potential for further complications.

逆向追溯

     2.  Forward Traceability

The precise traceability system also possesses the ability to trace from the production process to the finished product. By recording process data at each production stage, companies can ensure that every operation is performed within standard limits, thus preventing the production of non-conforming products. This forward traceability is particularly crucial for error-proofing management.

正向追溯

     3.  Supply Chain Transparency

Automotive manufacturing involves multiple suppliers, and the precise traceability function within LinkedData MES assists companies in recording the sources and production information for each component, ensuring transparent supply chain management. When a supplier’s components have issues, the traceability system enables rapid identification of the problem source, allowing for corrective measures to reduce uncertainties in production.

 

Integration of Precise Traceability and Process Quality Management (PQM)

 

The LinkedData MES system combines precise traceability functionality with Process Quality Management (PQM), enabling companies to perform quality control and optimization during production. PQM monitors each production stage in real time, while precise traceability records detailed operational data for each stage, allowing companies to conduct better quality analysis and production adjustments.

基于數(shù)據(jù)的質(zhì)量管理

 

Data-Driven Quality Management

 

In error-proofing management, the precise traceability function supports error-proofing operations for materials, processes, and personnel. For instance, precise traceability can ensure that the raw materials used for each component during assembly meet standards, preventing errors.

 

LinkedData MES Precise Traceability Solutions

 

The LinkedData MES system not only offers precise traceability functionality but also includes comprehensive production management tools. Companies can achieve end-to-end traceability from raw materials to finished products, while combining PQM for real-time process monitoring and quality management. Precise traceability is a vital module within the MES system, enhancing transparency in production processes and ensuring high-quality product delivery.

零可達(dá)MES精準(zhǔn)追溯解決方案

 

Through LinkedData’s solutions, companies can effectively mitigate quality issues in production, reduce recall risks, and improve overall productivity through more efficient management practices.



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