Application Case
Zhejiang Ruihui Intelligent Technology Co., Ltd. is committed to becoming a trusted
partner in the digital and intelligent transformation of China's manufacturing industry.
By deploying a MOM (Manufacturing Operations Management) platform and a full-process quality traceability system, we adopt a phased implementation approach, non-disruptive upgrades, and personnel training. This solution integrates with the client's existing ERP system for seamless data exchange, establishing a digital management system for the stamping workshop to enhance production coordination and plan execution efficiency.
1. Case Basics
Ningbo wanjia electric appliance | stamping workshop digital (MOM + whole process quality traceability) landing case
Customer name : ningbo Wanjia Electric Co., Ltd.
Industry : Auto Parts
Enterprise Size : Medium Manufacturing 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 : orders are mostly of many varieties and small batches, and frequent adjustments lead to more mold changes; The production plan lacks the support of real-time workshop capacity data and has low enforceability.
Logistics/storage pain point : material storage depends on labor and takes time to find materials; The loss of workshop materials (coil, plate, shearing plate) cannot be related to the work order, and the material loss rate is high.
Quality/traceability pain point : product production process traceability data collection depends on manual work, lack of implementation monitoring measures, and low accuracy and timeliness of traceability data.
Management/system pain points : the original system cannot be connected, the data is not available, the management cannot monitor the production status in real time, and the decision is lagging behind.
3. Our solution : with "traceability, collaboration and cost reduction" as the core, the customized solution is as follows:
Deploy system :MOM platform + whole process quality traceability system
Hardware configuration :PDA mobile terminal, industrial control computer, field data acquisition terminal, visual kanban
Implementation content : according to the characteristics of the stamping workshop, MOM and traceability modules are implemented in stages to realize transformation without stopping production; through system guidance and on-site training, key users can be quickly empowered to ensure the smooth operation of the system.
System integration : successfully connect the customer's existing ERP system, open up data links, and realize real-time exchange of core data such as work orders, materials, and inventory.
4. Project implementation effectiveness : after digital transformation, the core indicators have been significantly improved:
Efficiency category : scheduling efficiency increased by 15%, logistics transfer efficiency increased by 20%, and production efficiency increased by 5%.
Quality category : product defect rate decreased by 15%, quality inspection efficiency increased by 25%, and missed inspection rate decreased to less than 2%.
Cost category : save 5 people/year, reduce material loss rate by 12%, and increase inventory turnover by 10%.
Management : delivery on-time rate increased from 75% to 85%, production data can be checked in real time, and traceability coverage rate is 100.
5. Case Highlights the following are the core values and innovations of this project:
Data-driven production collaboration : realize real-time capacity monitoring through MOM platform, optimize production and planning collaboration, increase capacity utilization and manufacturing process flexibility.
Lean cost accounting : establish a post accounting system, quantify the actual consumption of materials, realize the accurate allocation of manufacturing costs, and effectively control costs.
Quality traceability of the whole process : build a traceability system for the whole process from raw materials to finished products, improve the quality early warning mechanism, and provide data support for process optimization.