Addressing the Pain Points of Injection Molding, MES Empowers a Comprehensive Upgrade of Production.
Targeting pain points for injection molding enterprises like differentiated deployment, data silos, difficulty acquiring equipment data, and challenging system integration, we offer multiple solutions.
Material Waste Control Optimization
Significant Reduction in Raw Material Waste Rate
Enterprise Pain Point: Traditional workshops had no material tracking, uncontrolled requisitioning, haphazard disposal of regrind, chaotic batches, persistently high material waste, and inability to accurately calculate monthly costs.
Implemented Improvement: Implemented full-process MES material control, achieving complete registration of raw materials, auxiliaries, regrind, and scrap. Full traceability for requisition, return, and recycling. System automatically calculates material waste per work order and per product. Inventory alerts and FIFO rules prevent expired stock accumulation and material mixing errors.
Effectiveness Improvement: Overall enterprise material waste rate reduced by 15%-20%. Raw material costs precisely controllable. Regrind recycling rate increased by over 30%. Completely solved chaotic material records and hidden waste issues.
Production Efficiency Improvement
Significant Increase in Machine Utilization (OEE)
Enterprise Pain Point: Chaotic manual scheduling, disorderly order insertion, time-consuming mold changes, inability to track downtime reasons, long machine idle times, unmaximized capacity, frequent delivery delays.
Implemented Improvement: Standardized workshop production order using MES intelligent scheduling, mold change management, downtime reason reporting, and real-time progress monitoring. Managers gain real-time visibility of machine status, quickly address abnormal idling and faults, optimizing mold change processes and production rhythm.
Effectiveness Improvement: Overall OEE increased by 20%+. Unproductive idle time significantly reduced. Daily workshop output stably increased by over 15%. Order on-time delivery rate notably improved.
Quality Control Upgrade
Continuous Decrease in Defect Rate
Enterprise Pain Point: Quality inspection relied on human experience, no standardized process, inability to trace defect sources, frequent batch defects, high rework costs, high customer complaint rate.
Implemented Improvement: Established a comprehensive quality system including first-piece, patrol, and final inspections. Standardized inspection criteria, real-time anomaly alerts, locking of defective batches and responsible personnel. Generated statistical defect analysis reports for targeted process and operational optimization.
Effectiveness Improvement: Overall product defect rate reduced by 18%+. Rework and repair costs significantly lowered. Complete quality traceability achieved, successfully passing customer factory audits, with notably improved customer satisfaction.
Labor Cost Optimization
Digitalization Replaces Repetitive Manual Ledger Work
Enterprise Pain Point: Workshops heavily reliant on manual record-keeping, statistical reporting, and reconciliation for traceability. Low efficiency, high error rates, time-consuming and labor-intensive, with persistently high labor costs.
Implemented Improvement: MES automatically calculates output, waste, quality, and equipment data, automatically generating various production reports, financial reconciliation ledgers, and quality analysis reports, replacing over 90% of paper records and manual statistical work.
Effectiveness Improvement: Manual workload for workshop statistics, reconciliation, and ledger keeping reduced by 70%+. Reduced manpower needs for repetitive positions. Data accuracy approaches 100%, completely solving problems of manual statistical errors and data lag.
Material Waste Control Optimization
Significant Reduction in Raw Material Waste Rate
Enterprise Pain Point: Traditional workshops had no material tracking, uncontrolled requisitioning, haphazard disposal of regrind, chaotic batches, persistently high material waste, and inability to accurately calculate monthly costs.
Implemented Improvement: Implemented full-process MES material control, achieving complete registration of raw materials, auxiliaries, regrind, and scrap. Full traceability for requisition, return, and recycling. System automatically calculates material waste per work order and per product. Inventory alerts and FIFO rules prevent expired stock accumulation and material mixing errors.
Effectiveness Improvement: Overall enterprise material waste rate reduced by 15%-20%. Raw material costs precisely controllable. Regrind recycling rate increased by over 30%. Completely solved chaotic material records and hidden waste issues.
Production Efficiency Improvement
Significant Increase in Machine Utilization (OEE)
Enterprise Pain Point: Chaotic manual scheduling, disorderly order insertion, time-consuming mold changes, inability to track downtime reasons, long machine idle times, unmaximized capacity, frequent delivery delays.
Implemented Improvement: Standardized workshop production order using MES intelligent scheduling, mold change management, downtime reason reporting, and real-time progress monitoring. Managers gain real-time visibility of machine status, quickly address abnormal idling and faults, optimizing mold change processes and production rhythm.
Effectiveness Improvement: Overall OEE increased by 20%+. Unproductive idle time significantly reduced. Daily workshop output stably increased by over 15%. Order on-time delivery rate notably improved.
Quality Control Upgrade
Continuous Decrease in Defect Rate
Enterprise Pain Point: Quality inspection relied on human experience, no standardized process, inability to trace defect sources, frequent batch defects, high rework costs, high customer complaint rate.
Implemented Improvement: Established a comprehensive quality system including first-piece, patrol, and final inspections. Standardized inspection criteria, real-time anomaly alerts, locking of defective batches and responsible personnel. Generated statistical defect analysis reports for targeted process and operational optimization.
Effectiveness Improvement: Overall product defect rate reduced by 18%+. Rework and repair costs significantly lowered. Complete quality traceability achieved, successfully passing customer factory audits, with notably improved customer satisfaction.
Labor Cost Optimization
Digitalization Replaces Repetitive Manual Ledger Work
Enterprise Pain Point: Workshops heavily reliant on manual record-keeping, statistical reporting, and reconciliation for traceability. Low efficiency, high error rates, time-consuming and labor-intensive, with persistently high labor costs.
Implemented Improvement: MES automatically calculates output, waste, quality, and equipment data, automatically generating various production reports, financial reconciliation ledgers, and quality analysis reports, replacing over 90% of paper records and manual statistical work.
Effectiveness Improvement: Manual workload for workshop statistics, reconciliation, and ledger keeping reduced by 70%+. Reduced manpower needs for repetitive positions. Data accuracy approaches 100%, completely solving problems of manual statistical errors and data lag.
