A New Approach for Finite Capacity Planning in MRP Environment.
ABSTRACT MRP (Material Requirement Planning) process generates a production plan which guarantees an exact quantity of right materials
on needed time but it sometimes causes capacity problems in the shop floor because of its ignorance on capacity constraints.
This paper presents a new planning method which involves the capacity planning during the MRP process. This planning method
starts from generating resource-based data structure and grouping resources which can act as a bottleneck. Explosion of resources
and adjustment of production schedules in accordance with the time horizon and the critical resources follow the former step.
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ABSTRACT: This paper presents a new framework for manufacturing planning and control systems which we call iterative manufacturing planning in continuous time (IMPICT) that appears to have several advantages over the well-known material requirements planning (MRP) framework. IMPICT explicitly considers capacity constraints and total system cost (including tardiness) to determine order sizes, order release/due dates, and operation schedules in a deterministic, multi-level, finite horizon, dynamic demand environment. Continuous time scheduling variables allow setups to be carried over from one period to the next.Three new heuristics built on the IMPICT framework are presented and tested in a simulation-based, full-factorial experiment with a wide variety of problem environments. The benchmark for the experiment was materials requirements planning with operations sequencing (MRP/OS) implemented with best-case, fixed planned lead times. The experiment showed that all three heuristics were statistically better than MRP/OS. The total cost for the order merging (OM) heuristic was 25 percent better than the total cost for MRP/OS. Computational times for OM were substantially larger than for MRP/OS; however, the computational times in the experiment suggest that OM is still computationally viable for large-scale batch manufacturing environments found in industry.IMPICT is superior to standard MRP systems because it explicitly considers capacity constraints and total system costs when it creates a materials plan. IMPICT is superior to linear programming-based approaches to finite loading and scheduling found in the literature because it allows setups to be carried over from one period to another and because it is computationally viable for realistic-sized problems.Decision Sciences 06/2007; 24(4):739 - 760. · 1.36 Impact Factor