Application of Theory of Constraints on Scheduling of Drum-buffer-rope System

Abstract

The successful enterprises deliver products and services in shorter throughput time and turnover inventory as quickly as possible. Three important approaches to achieve these goals are Materials Requirements Planning (MRPI, MRPII), Just-in-Time (JIT), and Theory of Constraints (TOC). TOC seems to be a viable proposition because it does not require costly affair of system change; rather it is simply based on scheduling of the capacity constraint resources. The scheduling system of theory of constraints (TOC) is often referred as drum-buffer-rope (DBR) system. DBR systems operate by developing a schedule for the system’s primary resource constraint. Based on simulation of a flow shop operation considering non-free goods, this study suggests that the performance of DBR results in lower in process inventory compared to conventional production system. In addition, the behavior of the system when bottleneck shifts its position has been studied. A methodology has been proposed using neural networks based on back propagation algorithm for accurate prediction of throughput considering mean processing time, coefficient of variation, buffer size, number of stations and signal buffer