Master Production Planning

Process

Master Production Planning looks at the planning process at an aggregate level over the medium term (1-3 months), with the emphasis on cost minimization/profit maximization subject to constraints of production capacity, space capacity, mode capacity etc. Master Production planning is suitable in companies that have distributed manufacturing usually closer to the place of consumption (to minimize transport cost and maximize service levels) wherein each of the production facilities compete with each other on cost/profit to get their share of the manufacturing. In this case, the plan is optimized for the entire supply chain. It is an important step in a multi-facility Supply chain as it ensures an optimal Allocation plan that aims to have the least cost of delivery / maximum contribution for a given set of Demand/Supply constraints.

Master Production Planning could also be used in cases where different products/SKUs compete for multiple production lines within a single plant. Here, the plan is typically optimized at the plant level. It is an important step as it ensures an optimal production plan and product mix that aims to have the least cost of production / maximum contribution/ maximum capacity utilization for a given demand and production capacity constraint.

Master Production Planning creates the map for the Production Planning to be done at a more granular level.

Solution

Our solution uses Mixed Integer Linear Programming (MILP) in order to generate the Master Production Plan for different objective functions of Cost Minimization, Profit Maximization etc. It has the ability to interact with a varied set of Solvers including commercial Solvers such as CPLEX, Gurobi as well as Open Source Solvers such as LPSolve, COIN-OR etc. An inbuilt constraints engine that can be configured in order to suit a particular Supply chain scenario provides increased flexibility. The ability to create and analyze various scenarios for different inputs of Demand/Supply/Constraints is also provided.