MES solution for automotive parts industry

As is well known, the assembly of automotive parts/components is a key link in automotive manufacturing, and the transformation of automotive parts is aimed at lean as the ultimate goal, that is, the transformation and upgrading of automotive parts manufacturing enterprises towards lean production and lean management. Workshop information management is the foundation of lean production. The MES system in the automotive parts industry solves the technical bottleneck of efficient data exchange between different automation equipment, providing production line control and traceability system solutions for automotive parts enterprises, helping enterprise customers save costs and improve product quality.

1. The host factory has production traceability requirements for component suppliers, which can trace the production process, key materials, and quality of components;

2. Multi variety, small batch production, fast production pace, high requirements for production, logistics, and quality, as well as high demands for production schedule control and batch quality;

3. According to the procurement plan and safety stock of the host factory, production is carried out. During the production process, there may be abnormalities such as order changes, which require quick response and corresponding adjustments to reduce the impact caused by abnormalities;

4. The production mode of each process node is different, making it difficult to control and track the work in progress;

5. The production process has a high degree of automation, and automation equipment needs to be networked and centrally controlled to monitor equipment status. In the event of equipment abnormalities, the abnormal information can be quickly transmitted to equipment management personnel;

6. Abnormalities in tooling, cutting tools, etc. have a significant impact on production

The SIGER Automotive Industry MIS (Manufacturing Intelligence System) big data analysis architecture is based on massive process data collection, combined with big data architecture technology, supported by Six Sigma statistical analysis, reliability analysis, data mining technology, and deep learning technology, to simplify the analysis process of complex product lifecycle and provide real-time process dynamic analysis.

Based on data crawling technology and device communication technology, SIGER provides an integrated automated data collection solution and data structure system for automotive manufacturing system data collection, helping customers reduce the cost of data acquisition (achieve zero cost data acquisition), and ensuring the authenticity and timeliness of data acquisition, making big data analysis in the automotive industry possible.

The device data collection scheme based on the Internet of Machines not only makes real-time data acquisition simple and feasible, but also makes the data acquisition structure and frequency more reasonable, making comprehensive data analysis feasible.

The SIGER data acquisition system supports multiple NC systems, such as FANUC, Mitsubishi, MAZAK, Siemens and other CNC systems, and has reached a comprehensive strategic cooperation with Huazhong CNC to build an industrial big data acquisition and analysis platform; Support multiple PLC data collection)

Tool lifecycle management process

Traceability management: accurate traceability based on artifact QR code, and discrete batch traceability based on work order flow

Andon management: mobile | whole-process control | directional push | level report

Kanban Management - Production Management APP

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