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The purpose of this paper is to determine the interaction between dynamic due date assignment methods and scheduling decision rules in a typical dynamic job shop production system in which setup times are sequence dependent. Two due date assignment methods and six scheduling rules are considered for detailed investigation. The scheduling rules include two new rules which are modifications of the existing rules. The performance of the job shop system is evaluated using various measures related to flow time and tardiness.

A discrete-event simulation model is developed to describe the operation of the job shop. The simulation results are subjected to statistical analysis based on the method of analysis of variance. Regression-based analytical models have been developed using the simulation results. Since the due date assignment methods and the scheduling rules are qualitative in nature, they are modeled using dummy variables. The validation of the regression models involves comparing the predictions of the performance measures of the system with the results obtained through simulation.

The proposed scheduling rules provide better performance for the mean tardiness measure under both the due date assignment methods. The regression models yield a good prediction of the performance of the job shop.

Other methods of due date assignment can also be considered. There is a need for further research to investigate the performance of due date assignment methods and scheduling rules for the experimental conditions that involve system disruptions, namely, breakdowns of machines.

The explicit consideration of sequence-dependent setup time (SDST) certainly enhances the performance of the system. With appropriate combination of due date assignment methods and scheduling rules, better performance of the system can be obtained under different shop floor conditions characterized by setup time and arrival rate of jobs. With reductions in mean flow time and mean tardiness, customers are benefitted in terms of timely delivery promises, thus leading to improved service level of the firm. Reductions in manufacturing lead time can generate numerous other benefits, including lower inventory levels, improved quality, lower costs, and lesser forecasting error.

Two modified scheduling rules for scheduling a dynamic job shop with SDST are proposed. The analysis of the dynamic due date assignment methods in a dynamic job shop with SDST is a significant contribution of the present study. The development of regression-based analytical models for a dynamic job shop operating in an SDST environment is a novelty of the present study.

Due‐date performance (DDP) is a very important performance indicator for the companies. Thus, companies with a high hit rate would have greater competitive advantage; on the contrary, companies that delay customers' orders frequently would lose sales opportunities and reputations. Therefore, there were many academic studies and practical efforts to improve DDP in the past, but the problem of low hit rate still exists. In order to increase the hit rate, some companies have focused on reducing the variation, while others focus on production management, but is the real problem affecting the low rate variability or production management? This is indeed difficult to be validated through practice. Therefore, this study designed three scenarios, tested each scenario for 30 times, each test involved seven subjects. The tests were to provide counter‐evidence in the Job Shop environment without variation. If the variation is the main factor of affecting hit rate, the rate at this time should be good; otherwise, the assumption that variation is the main cause is rebutted. The results demonstrated that production management planning is the main cause, and the method of enhancing the hit rate is obtained during the test.

In this paper, an integrated model for order release and due‐date management is developed to enhance manufacturers’ confidence in the due‐dates offered to customers. The proposed model utilised the backward finite scheduling order release control method and five different due‐date assignment rules. The proposed model is implemented using C++ computer programming language. Due‐date of each order is calculated by a due‐date assignment rule selected. Then the program tries to schedule the whole order with as lowest value as possible of tightness parameter (k). The output of the C++ program is production schedule of the whole order using backward finite scheduling order release method. Experiment results indicate that the modified number of operations due‐date rule_MNOP is superior with respect to the other due‐dates rules of the whole order.

Effective management of resources in a dynamic, multiproject environment requires consideration of two key issues: the availability of each of the multiple resources and the method of scheduling these resources to complete activities and, subsequently, projects. Identifies the trade‐offs between performance and the availability of multiple resources, when some resources are more costly than others. Finds that there are significant effects when the level of either the costly resources or the cheaper resources are varied, that trade‐offs can be made by reducing the availability of the costly resources and increasing the availability of the cheaper resources and that the improvement in completion time performance is reasonably linear over the tested ranges and the rates of improvement differ over the ranges. Describes the resource allocation factors and treatments as well as the scheduling heuristics. Uses a finite scheduling algorithm along with the prioritization heuristics to schedule the constrained multiple resources simultaneously and a simulation to replicate the environment. Develops linear regressions to provide further insight.

Under intensified pressure from both domestic and foreign competition, today′s manufacturers must strive to keep delivery promises and reduce waste. This depends largely on a manufacturer′s ability to assign accurate and attainable due‐dates. Presents an analytical method of assigning optimal total work content (TWK) due‐dates that minimize the average amount of missed due‐dates in a dynamic job shop with assembly operations. The accuracy of the method is assessed through computer simulation of a hypothetical assembly shop with different job structures under various operating conditions. While it is generally more accurate for jobs with simpler structures, the simulation results indicate that, over a range of test conditions, the method is both simple and effective in assigning optimal TWK due‐dates for assembly shops.

In job‐shop scheduling research, the shortest processing time despatching rule (SPT) has received considerable attention. Several truncated shortest processing time (SPT) despatching rules have been published in the literature. The motivation for such rules is that SPT despatching will frequently result in favourable inventory levels but unfavourable due date performance. Thus, the truncated SPT rules periodically switch from SPT despatching to despatching by some other rule. Owing to the complexity associated with these truncated rules, their implementation is doubtful. As a result, a modified truncated rule is presented that is easy to implement and yet performs favourably with respect to inventory and due date performance.

In this paper, the authors investigate the effects bottleneck machines have on the performance of a multi‐stage job shop. The operation performed by the bottleneck and its position in the product Bill of Materials is varied to determine the effects on system performance. It was found that the best place for the bottleneck machine to be located was at gateway operations located low in the Bill of Materials.

Facing keen worldwide competition, it is not enough for companies to pursue customer satisfaction; they must actively pursue customer delight. This paper seeks to design a work‐in‐process (WIP) exception handling system (WIPEHS) not simply measuring on‐time delivery performance for managers to take necessary improvement activities. It helps managers detect abnormal WIP levels in advance, trigger rectifying actions and finally notify pertinent people to coordinate roots causes and preventive means.

The structure of WIPEHS is proposed and then constructed with a soft package, Vigilance. A typical semiconductor factory is built and production data are simulated to evaluate the effectiveness of WIPEHS.

Collecting and analyzing results from the simulated typical semiconductor factory, the paper finds that the proposed system can effectively improve on‐time delivery performance; and that durations from a WIP exception detected a WIP exception back to normal and durations between two successive WIP exceptions significantly.

It helps factories outperform due dates, achieving significantly higher performance than prior performance without the production exception handling system, which should greatly please customers.

The proposed WIPEHS provide a total solution for undesirable production variations potentially harmful to due‐date performance. It anticipates WIP exception, notifies pertinent recipients, tracks the progress of exception resolution, and provides a forum for discussion of the root causes.

The performance of cellular manufacturing (CM) systems has been rigorously investigated during the last two decades. The findings from these studies need to be systematically tabulated, given that they span a wide range of systems and experimental conditions. Some of the findings have also not been in agreement with the prescriptive literature on group technology (GT). No such survey of research exists to date. Attempts to fill the void by providing a taxonomy that categorizes these studies into simulation‐based, analytical and empirical studies. Also discusses past work in the context of various experimental factors and conditions, such as system configurations assumed, setup and operation times, scheduling rules, lot sizes and performance measures used. Summarizes major findings from each stream of literature from the point of view of both researchers and practitioners.

Examines the planning and scheduling systems in an integrative framework for a dual resource constrained (DRC) job shop. Models a bottleneck shop environment which represents a common situation in practice. Research on workload smoothing mechanisms which integrate the planning and scheduling systems is sparse. Simulates 13 smoothing rules (utilizing aggregate workload and bottleneck information), three despatching rules and two order review/release rules. The results of this study indicate that workload smoothing by the planning system has a significant effect on the performance of the DRC job shop. Pulling work ahead in valley periods improved the tardy measures of performance, while pushing jobs back in peak periods usually deteriorated shop performance. Suggests that combining a planning system effectively with order review/release can improve mean tardiness, percentage tardy and mean flowtime measures of performance.