A high performance finite capacitated MRP process using a computational grid

Abstract

A material requirement planning (MRP) process generates a production plan which guarantees an exact quantity of the right materials available at the needed time. Providing an executable production plan at high speed has remained a goal for MRP since the process was first developed in the 1970s. However, due to the time consuming characteristic of the process with its intensive database interaction, real time processing remained unattainable. Moreover, this performance issue became worse, as the utilisation of production resources on the shop floor are expected to be maximised by the process due to a dynamic market environment. This paper presents a recent work by the authors on the concept of using a computational grid to achieve a breakthrough in its performance under conditions of finite capacity. The proposed system resolves capacity constraints by applying a simple heuristic called longest tail first rule, which is proved to minimise the total lead time, to each distributed cluster obviating the need for any rescheduling procedures. Implementation of this concept in a distributed database environment and its performance analysis are described. The experimental results suggest that the proposed finite capacitated MRP process has desirable characteristics in terms of processing time with a deep bill of material as in current supply chain practice.