1. Case Basics 
Case Title: jinhui Optics | Vehicle Optics Digital Workshop (MOM + QMS + FDC) Landing Case 

Customer Name : ningbo Jinhui Optical Technology Co., Ltd. 

Industry : Auto Parts, Optical Components 

Enterprise size : national-level specialized new "little giant" enterprise 

Project cycle :6 months 

2. The customer's original pain points 
Combined with the actual project, the pain points are described as follows:

Production pain points : after the completion of the process, the process relies on manual centralized reporting, information transmission lags behind, management is difficult to grasp the real progress of the workshop, and planning and implementation are seriously out of touch.

Quality/traceability pain point : the whole process of paper document management, version update lag easily leads to wrong version operation; Lack of single SN control system, when the quality is abnormal, the process, personnel, equipment and raw material batch cannot be quickly associated, and the problem location is time-consuming and laborious.

Management/system pain points :ERP, production, storage and other core systems are independent of each other, forming data islands, relying on paper document circulation, and manual repeated entry is inefficient and prone to errors.

Equipment/mold pain points : more than 140 equipment in the whole factory have no real-time acquisition channel, and their operating status is like a "black box", and key process parameters cannot be automatically returned, the rate of equipment movement and loss cannot be accurately counted.

Logistics/storage pain point : raw materials, semi-finished products and finished products rely on manual registration in and out of the warehouse, with large account-to-account deviation; The "first-in, first-out" rule is hard to restrict, and there is no trace for material flow, trace the chain break. 

3. Our solution : with "transparency, traceability and closed loop" as the core, the customized solution is as follows:

Deploy the system :MOM platform + QMS quality management system + FDC (fault detection and classification) system + WMS warehouse management system + IoT device networking 

Hardware configuration : laser laser engraving equipment, PDA mobile terminal, industrial computer, visual kanban, equipment data acquisition terminal 

Implementation content : adopt the strategy of "pilot new factory first, promote old factory later" and implement risk reduction step by step; the expert team is on-site to ensure a smooth transition of the system, and through in-depth research and difference analysis, to ensure that the scheme is in line with the actual business.

System integration : build an integrated MOM digital factory platform, deeply open up ERP, MES, WMS, QMS and IoT equipment acquisition systems, and deploy 15 + standardized interfaces, realize automatic data flow and synchronization of the whole link. 

4. Project implementation effectiveness : after digital transformation, the core indicators have been significantly improved:

Efficiency category : reporting efficiency increased by more than 90%, warehousing efficiency increased by more than 50%, problem response speed increased by more than 80%.

Quality class : the quality traceability efficiency is improved by more than 95%, and the troubleshooting time is shortened from several hours to minutes; the error rate of drawing version is reduced to 0.

Cost category : manual entry error rate is close to 0, which is expected to reduce unplanned downtime loss by more than 30%, and save a lot of paper consumables and manual filing costs.

Management class : realize 100 networking of 142 key equipment and real-time visualization of production data; The coverage rate of quality traceability is 100, realizing full link penetration from raw materials to finished products. 

5. Case Highlights the following are the core values and innovations of this project:

FDC quality closed-loop management : upgrade the traditional "after-the-fact inspection" to "process prediction", through batch identification, full chain traceability, and parameter monitoring, the rapid detection, positioning and closed-loop processing of quality anomalies are realized, and the yield rate is greatly improved.

Single-piece full-dimension traceability : generate a unique SN code for each product through IOT-linked laser engraving, binding all-element information of people, machines, materials, methods and rings, realize minute-level forward and reverse traceability to accurately lock the root cause of the problem.

Device digital neural network : build a device global networking system, collect 142 devices full-cycle data in milliseconds, and break the device "black box", provide accurate data support for preventive maintenance and performance improvement.