Integrated Production & Maintenance Optimization Engine
2012 – 2018
Optimization engine that co-schedules production and preventive maintenance under uncertainty to improve system-level performance.
Generates integrated production schedules (job and maintenance task sequencing) that explicitly embed preventive maintenance while accounting for stochastic failures and planning-horizon uncertainty. Balances throughput, tardiness, availability, and cost trade-offs in one decision system.
Decision Domain
Integrated production scheduling + preventive maintenance planning under uncertainty.
Methods
- Mathematical programming (exact and heuristic optimization)
- Stochastic modeling (failures, horizon uncertainty)
- Multi-objective optimization (cost/tardiness/availability trade-offs)
- Efficient solution methods for large-scale instances
- Simulation–optimization (when needed)
Ideal Use Cases
- Manufacturing lines and shops where maintenance windows materially affect throughput and due-date performance
- Flow shop / job scheduling environments with diverse maintenance requirements
- Maintenance-intensive operations needing coordinated planning across production and maintenance teams
Inputs
- Job/work orders and routing (sequence/processing times)
- Due dates / service-level targets
- Machine/resource availability calendars
- Preventive maintenance tasks (durations, intervals, eligibility windows)
- Maintenance task groups (to be schedule together; optional)
- Failure/uncertainty parameters (optional but recommended)
- Cost parameters (tardiness, downtime, maintenance, etc.)
Outputs
- Integrated production + maintenance schedule
- Multi-machine Gantt chart
- Trade-off summaries (availability vs tardiness vs cost)
- Maintenance window plan by resource
- Expected performance under uncertainty (when stochastic inputs are used)
- Constraint diagnostics (feasibility, bottlenecks)