Farzad Mahmoodi

An investigation of dynamic group scheduling heuristics in a job shop manufacturing cell

SUMMARY The objective of this study is to develop dynamic scheduling heuristics for cellular manufacturing environments (group scheduling or family heuristics) and compare them with existing family heuristics under various shop floor conditions. The proposed family heuristics stress good due date performance while reducing overall set-up time. Computer simulation is used to test three queue selection rules in conjunction with three dispatching rules under eight experimental conditions in a job shop cell. The results indicate that several of the proposed heuristics substantially improve the performance of the cell over the best previously suggested family heuristic under all experimental conditions.

A comparison of exhaustive and non-exhaustive group scheduling heuristics in a manufacturing cell

Previous group scheduling research has primarily focused on developing exhaustive two-stage heuristics in order to manage product flow through manufacturing cells. The objective of this paper is to present new, non-exhaustive heuristics and compare them with existing exhaustive heuristics in a job shop cell environment. Computer simulation is utilized to examine six non-exhaustive and six exhaustive heuristics under eight experimental conditions. The results indicate that although some non-exhaustive heuristics dominate the exhaustive heuristics on the average tardiness measure, the performance of exhaustive heuristics are generally superior to that of non-exhaustive heuristics. Furthermore, the performance of the exhaustive heuristics is more robust to the experimental factors.

A comprehensive analysis of group scheduling heuristics in a job shop cell

This paper describes a broad-based simulation study of the performance of two-stage group scheduling heuristics in a job shop cell. The objective of this study was to examine the direct and interactive effects of a variety of shop factors on the performance of the best, previously reported, group scheduling heuristics. A set of traditional single-stage scheduling heuristics were examined as well. Shop factors considered include: setup to runtime ratio, cell load level and variability of inter-arrival times. An assumption common to group scheduling research which provides for an equal division of the part family into subfamilies is also examined. This is accomplished through the creation of an alternative scenario where the majority of the parts are assigned to one subfamily, i.e. one subfamily dominates the part family population. The effects of set up to runtime ratio and cell load have been examined in previous group scheduling research, but not in conjunction with the inter-arrival time variability fac...

The important role of change management in environmental management system implementation

Purpose – There is increasing concern about the environmental aspects of business and production processes, and many companies have chosen to implement environmental management systems (EMSs). The purpose of this paper is to examine whether change management efforts improve the perceived success of EMS implementation.Design/methodology/approach – The paper analyzes empirical survey data using hierarchical regression analyses with a sample of mid‐level engineers and managers in manufacturing facilities.Findings – Change management efforts appear to enhance the perceived environmental performance of manufacturing establishments, primarily driven by top management support for EMS implementation and efforts to institutionalize the EMS.Research limitations/implications – Results are generalizable to large manufacturing facilities implementing EMSs. Results should be replicated with a larger sample and using measures of actual environmental performance.Practical implications – Change management techniques can e...

Supplier selection model with contingency planning for supplier failures

We consider the optimal allocation of demand across a set of suppliers given the risk of supplier failures. We assume items sourced are used in multiple facilities and can be purchased from multiple suppliers with different cost and reliability characteristics. Suppliers have production flexibility that allows them to deliver a contingency quantity in case other suppliers fail. Costs considered include supplier fixed costs and variable costs per unit, while failure to deliver to a demand point results in a particular financial loss. The model utilizes the decision tree approach to consider all the possible states of nature when one or more suppliers fail, as well as expand the traditional transportation problem. Unlike other supplier selection models, this model considers contingency planning in the decision process, minimizing the total network costs. This results in a base allocation to one or more of the available suppliers and a state of nature specific delivery contingency plan from the suppliers to each demand point. A numerical example, as well as sensitivity analysis, is presented to illustrate the model and provide insights.

Safety stock determination based on parametric lead time and demand information

In many production environments where demand and lead times are variable, significant levels of safety stock inventory are required to assure timely production and delivery of the final product. Traditional models to determine the appropriate safety stock level may result in more safety stocks at sub-assembly and finished goods levels than necessary and thus lead to higher inventory carrying costs than desired. Such models generally incorrectly assume that the demand during the lead time follows a normal distribution. This paper revisits and analyses a re-ordering point inventory model developed by Estes (1973) that accounts for demand and lead time variability without making any particular distributional assumptions. Instead, it focuses on historical data to determine the possible outcomes of the replenishment cycle. We compare the proposed model with the traditional model by conducting simulation analysis using three data sets obtained from an electronics manufacturer. The results indicate that the proposed model yields much closer to target service levels and lower inventory carrying costs than the traditional model, regardless of the data set used.

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a systems flow-time performance.

Long-term and penalty contracts in a two-stage supply chain with stochastic demand

Abstract Recent applications of game-theoretic analysis to supply chain efficiency have focused on constructs between a buyer (the retailer or manufacturer ) and a seller (the supplier ) in successive stages of a supply chain. If demand for the final product is stochastic then the supplier has an incentive to keep its capacity relatively low to avoid creating unneeded capacity. The manufacturer, on the other hand, prefers the supplier’s capacity to be high to ensure that the final demand is satisfied. The manufacturer therefore constructs a contract to induce the supplier to increase its production capacity. Most research examines contracting when final demand is realized after the manufacturer places its order to the supplier. However, if final demand is realized before the manufacturer places its order to the supplier, these types of contracts can be ineffective. This paper examines two contracts under the latter timing scenario: long-term contracts in which the business relationship is repeated, and penalty contracts in which the supplier is penalized for too little capacity. Results indicate long-term contracts increase the profit potential of the supply chain. Furthermore, the penalty contracts can ensure that the supplier chooses a capacity level such that the full profit potential is achieved.

Analysis of automated guided vehicle configurations in flexible manufacturing systems

Automated guided vehicle (AGV) systems complement the operation of flexible manufacturing systems (FMS) by providing integrated automated material handling that capitalizes on the systems flexibility. Previous research considering AGV systems for use in FMS installations has focused on complex control strategies to reduce the congestion problem often encountered in these systems. Recently, attention has been given to tandem system configurations that reduce congestion and simplify system control. The present study uses the simulation methodology to compare the performance of three AGV configurations under a variety of experimental conditions. The results indicate that system size, load/unload time, and machine failure rate factors have significant impacts on the operation of the systems considered. In general, with respect to due date performance, it is recommended to use the traditional configuration in small systems while using the tandem/loop configuration in larger systems. Furthermore, it is shown that the addition of the loop to the tandem configuration mitigates the sensitivity of the tandem configuration to the load/unload time factor as well as significantly improving its performance under high load/unload times. Thus, if tandem configuration is desired to reduce congestion and simplify system control, investments must be made to directly reduce the load/unload times or to construct a loop to avoid the load/unload time penalty.

Scheduling unbalanced cellular manufacturing systems with lot splitting

Recently, a large number of studies have addressed lot splitting as a means to reduce flow times as well as improve due date performance. Furthermore, a number of studies have examined scheduling policies in cellular manufacturing systems. These studies have been conducted under a variety of experimental factors, shop structures and operational assumptions. This study examines scheduling cellular manufacturing systems in the presence of lot splitting. In addition, we utilize various scheduling policies to test formally the underlying principles of the synchronous manufacturing philosophy. This is accomplished by utilizing exhaustive and non-exhaustive scheduling heuristics simultaneously at bottleneck and non-bottleneck workcentres. The results indicate that, under certain conditions, performing additional set-ups before the bottleneck can improve due date performance without an adverse effect on average flow time. Furthermore, we show that incurring additional set-ups after the bottleneck does not improve due date performance and may deteriorate flow time performance. These results conflict with some of the tenets of the synchronous manufacturing philosophy.