ManufacturingSolution
Production Scheduling and Sequencing Optimization
Generate feasible production schedules against real constraints in minutes, and let planners compare objectives before committing rather than defending a plan built in a spreadsheet.
Solution
Machine Learning
Industry
Manufacturing
Company Size
Solution Overview
industry
Manufacturing
solution
Machine Learning
technologies
Azure Machine Learning, Microsoft Fabric, Power Apps, Power BI, Azure Batch, Dynamics 365 Supply Chain
The Challenge
Production schedules are built in spreadsheets by a small number of experienced planners who hold the sequencing rules in their heads, which makes the plan good but slow, undocumented and impossible to reproduce when they are away.
- 1Schedules built in spreadsheets with sequencing rules held in individual planners' heads
- 2No practical way to test whether an alternative sequence would perform better
- 3Changeover cost, material, labour and commercial priority traded off by judgment alone
Our Approach
CloudGate builds a constraint-based scheduling capability where capacity, changeover, material availability, labour skills and commercial commitments are modeled explicitly and a solver produces feasible schedules against a stated objective.
- Explicit constraint model covering capacity, changeover, material, labour and commitments
- Solver generating feasible schedules against a configurable objective function
- Scenario comparison across competing objectives before a plan is committed
Typical Outcomes
Minutes
TO A FEASIBLE SCHEDULE
Explicit
CONFIGURABLE OPTIMIZATION OBJECTIVE
Planner-approved
BEFORE RELEASE TO THE FLOOR
Typical outcomes for this solution pattern, not the results of a named client engagement.
Technologies Used
Azure Machine LearningMicrosoft FabricPower AppsPower BIAzure BatchDynamics 365 Supply Chain


