بهبود عملکرد ساخت تولید کارگاهی همراه با کنترل تولید کشش تقاضا از طریق کاهش راه اندازی / پردازش تغییرات زمان

This study was aimed at investigating the effects of reducing set-up/processing time variability on the production performance of a job shop environment with demand-pull production control. Simulation was employed as the modelling tool. It was found that reducing processing time variability is more effective for a cellular layout than for a functional layout where parts are transported and processed piece by piece within cells. On the other hand, reducing set-up time variability should be given a higher priority for a functional layout or a cellular layout where parts are moved by batches within cells. In addition, set-up or processing time variability hardly affected the selection of appropriate configuration of a job shop with demand-pull production control.

Since the development of the Just-in-Time (JIT) manufacturing techniques at Toyota production plants in the early 1970s, these techniques have been adopted by manufacturing firms globally for improving productivity. One important aspect of JIT manufacturing is the demand-pull production control using Kanbans (‘the Kanban system’, hereafter). The Kanban system provides a highly visible mechanism for controlling the production and movement of parts and thus, avoids excessive stock build-up. A detailed description of the operation of the Kanban system was provided by Monden (1983). Although the Kanban system has been mostly implemented in repetitive manufacturing environments (i.e., flow shops), Gravel and Price (1988) and Lee et al. (1994) have reported the potential of the Kanban system to increase the productivity of job shop environments. In addition, considering the usually lower efficiency of job shop manufacturing in comparison with repetitive manufacturing, Stockton and Lindley (1995) and Sandras (1985) stressed the importance of the Kanban system in driving continuous improvement activities in job shop environments. It is important to note that a crucial prerequisite for realising the benefits of the Kanban system is to reduce production fluctuations to a minimum (i.e., to achieve smooth production flows) (Monden, 1983; Kimura and Terada, 1981). However, in job shop environments, workers are confronted with diversified product types with few repetitions (as opposed to the repetitive product mix of repetitive manufacturing) and thus, the learning curve for production operations is more difficult to evolve. Eventually, the lack of proficiency very often leads to more variable machine set-up and part processing times and in turn, production fluctuations. Therefore, devising strategies for reducing set-up/processing time variability is essential for the Kanban system to operate smoothly in job shop environments. The purpose of this study is to investigate the effects of reducing set-up/processing time variability on the production performance of job shop manufacturing with the Kanban system, and to derive proper implementation strategies under different shop conditions. A simulation model of a job shop environment was developed, and an experiment was carried out using the shop model to collect shop performance data for further analysis. This paper is organised in seven sections. A review of studies related to investigating the effects of set-up/processing time variability on Kanban-based systems is given in the next section. Design of the simulation experiment and shop model is presented in 3 and 4, respectively. In Section 5, development and execution of the simulation model is described. Simulation results are presented and discussed in Section 6, and finally, conclusions are given in Section 7.

In job shop environments, one of the major causes of production fluctuations is the variability of set-up and processing times. Because of the vulnerability of Kanban systems to production fluctuations, high set-up/processing time variability will inevitably hinder the operation of Kanban systems in such environments. The findings of this study support the effectiveness of reducing set-up and processing time variability in improving the production performance of job shop manufacturing with a Kanban system. However, the effectiveness of reducing set-up/processing time variability varies substantially, depending on shop configurations, production flow patterns, and the set-up time reduction effected by cellular manufacturing. The influences of the above factors can be summarised for individual as well as relative shop performances as follows.