The impact of sequence changes on product lead time

Abstract

In practice, sequence changes during production often occur due to material shortages, rush jobs, etc. Rescheduling, expediting and de-expediting are common practice on the shop floor, but in many cases it is less clear to which extent such control policies influence throughput times. The aim of this paper is to study the impact of sequence changes on the average throughput time and its variability. The analysis is done by means of simulation. Our basic model consists of five machines, each preceded by a buffer with infinite capacity. In a first part, we rely on the first in, first out (FIFO) priority rule, common in queuing theory. In a second part, we keep all parameters the same, except for the priority rule. In each queue, the priority is now given to the entity with the highest probability of being late. Comparing the results of our FIFO model (FIFO rule) with the results of the model with the new priority rule allows us to draw conclusions concerning the impact of sequence changes on both the average and the variance of product lead time. Although further research is necessary, the results of this study indicate that in our setting sequence changes have no significant impact on the average product lead time but do increase the variance of the lead time and thus influence customer service. r In today's business environment, customer satisfaction becomes more and more important and consequently on-time delivery is one of the major competitive concerns. To improve delivery performance, companies often resort to rescheduling jobs on the shop floor, selectively expediting the more urgent ones while de-expediting others. The intention to obtain better delivery performance is not the only reason for rescheduling. This policy is sometimes inevitable because of the lack of raw material, the unavailability of components for assembly, staffing problems, etc. Given its widespread use, we want to investigate the effect of rescheduling on product lead time. In this paper we concentrate on the effect of sequence changes due to rush jobs. In our case, this refers to the expediting of jobs with the highest probability of being late, provided that we do not intervene. Our research question is the following: What is the impact of such sequence changes on the average product lead time and on its variance? To address this question, we use simulation. The simulation models are built with the ARENA Simulation Software. We first describe the structure of these models. Next, the results are discussed. A last section summarizes the most important conclusions. 1. The simulation model In this section we describe the two models built in ARENA: the first in, first out (FIFO) model and the model with sequence changes. 1.1. FIFO model The FIFO model consists of five servers. Each server is preceded by a queue with infinite capacity and FIFO queuing discipline. Jobs are simply processed in the order in which they arrive at the system [1]. Each server has an average service time of 4 s, exponentially distributed. The interarrival time of products is exponentially distributed with an average of 5 s. As soon as a product has been processed on the last machine, it is considered ready for delivery and it leaves the system. The lead time of a product is defined as the time between *Corresponding author. E-mail address: an.dupon@ufsia.ac.be (A. Dupon). 0736-5845/02/$-see front matter r 2002 Published by Elsevier Science Ltd. PII: S 0 7 3 6-5 8 4 5 (0 2) 0 0 0 2 5-X