Applying Simheuristics to Minimize Overall Costs of an MRP Planned Production System.

Wolfgang Seiringer,Klaus Altendorfer,Javier Panadero,Juliana Castaneda,Angel A Juan

doi:10.3390/a15020040

Abstract

Looking at current enterprise resource planning systems shows that material requirements planning (MRP) is one of the main production planning approaches implemented there. The MRP planning parameters lot size, safety stock, and planned lead time, have to be identified for each MRP planned material. With increasing production system complexity, more planning parameters have to be defined. Simulation-based optimization is known as a valuable tool for optimizing these MRP planning parameters for the underlying production system. In this article, a fast and easy-to-apply simheuristic was developed with the objective to minimize overall costs. The simheuristic sets the planning parameters lot size, safety stock, and planned lead time for the simulated stochastic production systems. The developed simheuristic applies aspects of simulation annealing (SA) for an efficient metaheuristic-based solution parameter sampling. Additionally, an intelligent simulation budget management (SBM) concept is introduced, which skips replications of not promising iterations. A comprehensive simulation study for a multi-item and multi-staged production system structure is conducted to evaluate its performance. Different simheuristic combinations and parameters are tested, with the result that the combination of SA and SBM led to the lowest overall costs. The contributions of this article are an easy implementable simheuristic for MRP parameter optimization and a promising concept to intelligently manage simulation budget.

Highlights

For manufacturing companies, an enterprise resource planning system (ERP) is the central system to plan and control production-related resources
This article is a further development of the results based on three different simheuristic versions to identify the minimal overall cost only for the material requirements planning (MRP) planning parameter safety stock and planned lead time
From a production planning perspective, the developed simheuristic versions, exponential range reduction (ERR), provides a fast and well performing simulation-based optimization approach which is simple to apply in practical environments

Summary

Introduction

An enterprise resource planning system (ERP) is the central system to plan and control production-related resources. Compared to the technological development of ERP systems, the used planning algorithms have not changed that much during the last decade. Most commercial ERP systems still use the hierarchical production planning approach of material requirements planning (MRP) to generate production orders [1]. The applicability in different industries and the straightforward and scalable logic—independent from the product complexity—fostered MRP’s importance in industry and science. The three planning parameters to control MRP are lot size, planned lead time, and safety stock. Many other parameters must be set up and defined to get a production system on which an MRP can be applied, such as a bill of material (BOM), processing time, setup time, planning period, machine availability, and many more

Methods

Results

Discussion

Conclusion