Core Service
Production Optimization
Scheduling and resource allocation using optimization and simulation
Overview
Production optimization maximizes throughput, minimizes costs, and improves delivery performance through intelligent scheduling and resource allocation. Our solutions combine operations research, simulation, and machine learning to create adaptive production plans that respond to demand changes, equipment availability, and supply chain disruptions in real-time.
Key Features
Linear Programming & Heuristics
Mathematical optimization models and metaheuristics (genetic algorithms, simulated annealing) for complex scheduling problems with multiple constraints.
Bottleneck Analysis
Theory of Constraints analysis to identify production bottlenecks and optimize buffer strategies, drum-buffer-rope scheduling for maximum throughput.
Dynamic Rescheduling
Real-time schedule adaptation to handle machine breakdowns, rush orders, material shortages, and other disruptions with minimal impact.
Discrete Event Simulation
Digital twin simulation to test production scenarios, evaluate layout changes, and optimize WIP levels before implementation.
Technical Approach
Our production optimization methodology delivers measurable improvements:
- Data Integration: Connect to ERP, MES, and shop floor systems to gather production constraints and real-time status
- Problem Formulation: Model objectives (minimize makespan, maximize throughput) and constraints (capacity, precedence, setup times)
- Solution Algorithm: Select optimization approach based on problem size and real-time requirements
- Validation: Simulate schedules to verify feasibility and performance before deployment
- Continuous Improvement: Monitor KPIs and refine models based on actual performance data
Use Cases
Production optimization drives operational excellence:
- Job Shop Scheduling: Optimize machine assignments and sequences for make-to-order manufacturing
- Batch Processing: Maximize equipment utilization for pharmaceutical, chemical, and food processing
- Assembly Line Balancing: Optimize workstation assignments to minimize cycle time and balance workloads
- Workforce Scheduling: Allocate skilled labor to tasks considering availability, skills, and labor rules
Expected Outcomes
Production optimization delivers quantifiable operational gains:
- 15-25% throughput improvement through optimized scheduling
- 20-30% reduction in work-in-progress inventory
- 10-15% improvement in on-time delivery performance
- 30-40% reduction in changeover time through intelligent sequencing
Ready to Optimize Production?
Let's discuss how optimization can improve your manufacturing efficiency and delivery performance.