سیستم برنامه ریزی هماهنگ شده برای مشکل برنامه ریزی سفارشات مشتری در محیط های تولید کارگاهی

In this study a coordinated scheduling of customer orders (CSCO) system, with the purpose of improving customer order flow time, is proposed for the order-based production system in which several jobs make up a given customer order and nothing is delivered to the customer until the order is complete. The customer order flow time, which elapses between the release of the first job and the completion of the last job of an order, is crucial because it shows how long the order is in the shop and in the finished goods warehouse. Shorter customer order flow time results in less work-in-process (WIP) and finished good inventory (FGI). The CSCO includes two main decisions: (i) release the jobs and (ii) dispatch the jobs at the station level. Extensive simulation experiments were performed to compare the proposed scheduling system with the benchmark mechanisms presented in previous studies. They led to the conclusion that CSCO significantly dominates the others in two order-based job shops.

Over the last decades many research results have been published about the effects of dispatching rules on the performance of job shop production systems. The performance effectiveness of a job shop has long been measured relative to the job flow time. The results of these studies cannot be extrapolated to a shop where several jobs make up a particular customer order and where nothing is delivered to the customer until the order is complete (Blocher, Chhajed, & Leung, 1998). Work jobs within a customer order have different routing length. This type of scheduling problems is usually referred to as customer orders scheduling (COS) problems. The research literatures on COS problems are scarce. Ahmadi and Bagchi (1992) considered the COS problem in a multi-machine, focused factory environment, with performance based on the order flow times and due dates. Gupta, Ho, and van de Veen (1997) studied a bi-criteria COS problem involving both flow time and makespan on a single machine environment. Blocher and Chhajed (1998) focused on minimizing the order flow time in a parallel machine environment. Blocher et al. (1998) examined the performance of order-based dispatch rules in a general job shop, where the environmental factors were shop utilization and due-date tightness and the performance measures were order flow time, order tardiness and proportion of tardy orders. Ahmadi, Bagchi, and Roemer (2005) showed that the problem of minimizing the weighted sum of customer order delivery time is unary NP-hard, and proposed several heuristic solutions for solving special cases of the problem. Yang (2005) established the complexity of several customer order scheduling problems on parallel machines with different types of objectives, job restrictions, and machine environments. Erel and Ghosh (2007) showed that the customer order scheduling problem on a single machine is strongly NP-hard. Based on the above descriptions, most of the research use order flow time as an objective. In this study, we first introduce a new class of customer order scheduling problem of minimizing the customer order flow time. The customer order flow time, which elapses between the release of the first job and the completion of the last job of an order, is considered a crucial measure in this kind of shop environment. Shorter customer order flow time results in less work-in-process (WIP) and finished good inventory (FGI). The WIP and FGI tie up capital and costs interest. Reducing the customer order flow time can therefore contribute in two ways to an increase in the return on investment. In addition to the WIP and FGI levels, shorter customer order flow times result in a higher product yield and better capacity given tool inventory and facility constraints. Therefore, we think that minimizing the customer order flow time in order-based production system is a promising area of research. Furthermore, because of the complexity of the COS problem, the existing studies focused primarily on developing and comparing dispatching rules and due date setting mechanisms, not on proposing an order releasing policy. The primary objective of the present study is to develop a scheduling system, which we call the coordinated scheduling of customer orders (CSCO), involving an order releasing policy and a dispatching rule for the COS problem in dynamic job shop environments, in order to improve the customer order flow time. The results of our experiments indicate that the CSCO performs better than the conventional scheduling combinations of order releasing policies and dispatching rules. The rest of the paper is organized as follows. A description of the order releasing policy and dispatching rule follows in the next section. In Section 3, our proposed framework is described in detail. Then, in the fourth section the simulation model and the experimental design used to study the performance of the scheduling system are discussed. We present some general observations of the results in the fifth section. In the final section we provide a summary of the results and make some suggestions for future work.

While most research works have been done on the COS problem regarding the dispatching and due date assignment rules, relatively few attempts were made to study the relative performances of order releasing policies. In addition, in an order-based production system a measure, customer order flow time (COFT), is important because it shows how long the order is in the shop and in the finished goods warehouse. So, it could be considered a good surrogate measure for controlling the cost, including the work-in-process and the finished goods inventory. This study was an attempt to compare the relative performances (especially for COFT) of scheduling combinations of order releasing policies and dispatching rules in two order-based job shop environments. A new scheduling system, coordinated scheduling of customer orders (CSCO), was introduced as a way of controlling the job release and synchronizing of the within-order jobs in order to reduce the customer order flow time. CSCO and a total of 15 benchmarking scheduling combinations were considered for a performance analysis in this study. Systematic computer simulation was used as a research tool. Overall, CSCO has been shown to be very effective in minimizing COFT. Although IMR with the EDD dispatching rule performs best in minimizing OLT, there is no significant difference between CSCO and IMR-EDD for OLT. The experimental results also indicate that CSCO significantly minimizes FT as well as WIP + FGI. In summary, CSCO is very effective at controlling the release of within-order jobs, in which the non critical job is not released to the shop if it is expected to be too early. It was also evident that CSCO can indeed synchronize the within-order jobs to be finished as soon as possible to the same time. The focus in this study has been on improving the customer order flow time. The next step should be to extend the research to minimize due date related performance measures. In addition, an obvious area for future research is to carry out similar tests for a more realistic shop setting for standard products.