1. Case Basics 
Case Title: biyi electric appliance | injection molding workshop MES + IOT digital factory landing case 

Customer name : Zhejiang biyi electric appliance co., ltd. (a shares listed, stock code: 603215)

Industry : Kitchen small appliance manufacturing (injection molding and surface treatment)

Enterprise size : large-scale listed enterprise with more than 1600 employees and a construction area of over 70000 ㎡, high-tech enterprise 

Project cycle : September 2025-July 2026 (about 10 months, implemented in two phases)

2. The original pain points of customers 
According to the actual investigation of the electric injection molding workshop, the original pain points are mainly concentrated in the following four aspects:

Production pain points : prenatal preparation is not standardized and has no control-whether the machine adjustment parameters are standardized, whether the mold is correct, whether the material preparation is timely and accurate, and whether the equipment mold completes prenatal maintenance are all lack of systematic control; The workshop is not executed according to the production plan, and the production is random. There is no matching test process for special products, there is a serious disconnect between planning and execution.

Logistics/storage pain point : the production progress cannot be mastered in real time, the waiting for shortage of materials is frequent (average waiting 18 minutes/time), and the material information is opaque; AGV is missing, material transfer depends on labor, and, workshop assembly shortage information cannot be linked in real time; Material label management is chaotic and batch traceability is difficult.

Quality/traceability pain point : the first inspection relies on manual paper records, with high risk of missed inspection and no systematic control of inspection tasks; Abnormal product quality cannot be traced back to the source quickly, bad causes (such as flash, lack of glue) lack of data support for root cause analysis; The final inspection process is not standardized, and the status of defective products cannot be systematically marked.

Management/system pain points : data disconnection between original systems-missing data interaction standards for equipment, production lines, PLC and upper management systems; Low degree of integration of digitization, automation and lean three; the soundness and application of the underlying data are insufficient; key indicators such as equipment utilization rate and OEE cannot be counted in real time, and management decisions lack data support. 

3. Our solution:this project takes "informatization, automation and lean integration" as its core idea, and deploys Ruihui intelligent MES system + APS advanced scheduling + IOT equipment networking + Saiyi MOM platform to realize digital closed-loop control of the whole process from planning to warehousing in the injection molding workshop.

Deployment system :MES production execution system + APS scheduling system (Gantt chart visual scheduling) + IOT equipment networking acquisition platform + Saiyi MOM manufacturing operation management platform, four major system integration linkage, implementation plan → start → report for work → data exchange of all links in storage.

Hardware configuration : 276 BN102 data acquisition boxes +2 BN102-4G versions (wireless acquisition in power distribution room) +36 smart meters +266 relays, it covers 242 sets of equipment in injection molding workshop, 24 automatic lines in stamping workshop, 14 production lines in assembly workshop and 3 lines in spraying workshop, totaling 319 collection points.

Implementation content : implemented in two stages without stopping production. The first stage (September-December 2025):IOT equipment networking first, completing data collection at 319 points in the new factory and digital large screen display; The second stage (November 2025-July 2026):MES blueprint design → MES software online in injection molding workshop → MES promotion in assembly workshop → overall completion of the project. It covers core modules such as plan management, production report, mold change and machine adjustment, first patrol and final inspection, mold life cycle management, equipment IOT, lamp installation call, over-production control, E-SOP, label traceability, etc.

System integration :APS → MOM → MES → IOT full-link data interworking. APS scheduling plan is pushed to MOM through interface, MOM is sent to MES for execution, and real-time data of IOT acquisition equipment is returned to MES to form data closed loop. Integration interfaces include: basic material synchronization, BOM synchronization, work order addition/change synchronization, label printing data return, etc. All interfaces are captured in real time by polling. The mobile terminal supports internal and external network access and can change the plan sequence. 

4. Project implementation effectiveness : the following data are based on the actual operation data of the system kanban and the design objectives of the project plan:

Efficiency class : the planned achievement rate is increased to 92.1 (52000 pieces planned and 43980 pieces actually produced on that day), compared with the manual scheduling mode, it is significantly improved. 40 sets of equipment in the injection molding workshop were monitored in real time, and the machine opening rate was 86.5, and the reason for shutdown was responded within 10 minutes.

Quality category : the defective rate of the day is 1.8 (high flash/missing glue is the main defective item), the whole process of the first round and final inspection is systematically controlled, and the missing rate is greatly reduced; if the first inspection fails to pass the prohibition of starting, the automatic alarm for patrol inspection is not submitted on time, and the quantitative inspection system automatically determines the results.

Cost category :319 collection points are automatically collected instead of manual statistics, which is expected to save labor input for positions such as equipment data statistics and production reports. The system automatically calculates the output according to modulus, over-production 3% early warning, 5% team leader intervention, 10% control robot shutdown, effectively reduce material waste and inventory backlog.

Management category : 100 of the 242 equipment in the injection molding workshop are collected online, 100 of the production data are covered, and the workshop data information is fully transparent; Barcode tracing of the whole process from planned order to completion warehousing, human, machine, material and quality data are 100 per cent traceable. 

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

IOT depth coverage of the whole workshop : covering injection molding, assembly, stamping, spraying, coffee machine whole workshop and power distribution room, 319 collection points realize full-dimensional data collection. Through the BN102 collection box + relay + ammeter combination scheme, real-time connection from the bottom data of the equipment to the upper management system is realized, laying a solid foundation for the digitalization of the new factory.

Four management closed loop construction :MES + APS + IOT + MOM four system integration, build production closed loop (plan → start → report → warehousing), quality closed loop (first inspection → patrol inspection → final inspection → traceability), mold closed loop (upper mold → use → lower mold → maintenance → resume), abnormal closed loop (occurrence → processing → confirmation → knowledge base), and upgrade from "post-event statistics" to "real-time task + dynamic warning + closed loop improvement" management mode.

Lean production and counter-control : the system automatically calculates the output according to the combined modulus and compares it with the work order, with 3% warning for overproduction, 5% team leader intervention, and 10% control robot shutdown; if the process parameters exceed the standard, the alarm will be automatically given and the equipment will be controlled to start and stop. The abnormal installation of the lamp will automatically push the DingTalk/WeChat group and upgrade it over time, thus truly realizing the closed-loop management of "finding people for things.