End User
LMS
Description
The AI-Assisted Production Scheduling service generates optimised production schedules that allocate and sequence manufacturing tasks across available resources, with energy efficiency as a primary optimisation criterion alongside makespan and due-date compliance. By evaluating alternative machine sequences and task assignments using AI and combinatorial optimisation, the service identifies schedules that minimise total energy consumption for equivalent production output.
Core Capabilities
Predictive & Prescriptive Analytics
Optimization & Decision Support
Business Need
Manual or rule-based scheduling in multi-machine manufacturing facilities frequently results in resource conflicts, idle time, and suboptimal energy use. With energy costs representing a significant share of manufacturing costs and growing ESG reporting obligations, production planners need systematic tools that embed energy efficiency into scheduling decisions while meeting throughput and delivery targets.
Key Performance Indicators
Energy efficiency improvement: minimum 10% reduction in total energy consumption for equivalent production output
Schedule feasibility: 100% of generated schedules must satisfy all hard constraints (capacity, precedence, due dates)
Schedule generation computation time benchmarked for operational viability
Comparison baseline: First-In-First-Out heuristics or existing manual scheduling practice
Data Provided
Time-indexed schedule: order-to-machine assignments with start/end times and resource allocations
Predicted energy consumption profile over the scheduled period
Inputs: production orders (IDs, quantities, due dates, priorities, process sequences), machine data (processing times, energy consumption per operation, setup times, availability)
TEF
TEF IND