Bernard W. Taylor

DYNAMICALLY ADJUSTING THE NUMBER OF KANBANS IN A JUST-IN-TIME PRODUCTION SYSTEM USING ESTIMATED VALUES OF LEADTIME

Abstract In a Just-in-Time (JIT) production system with Kanbans, as used by the Japanese, the number of Kanbans employed at each workcenter remains relatively constant from month to month even though demand may change, This occurs because of the unique (and stable) conditions inherent in the production environment of Japanese firms. However, a number of American firms have considered or attempted the implementation of a JIT system without a similar production environment, thus, necessitating that the number of Kanbans at each workcenter be adjusted periodically. In this paper, a procedure for dynamically adjusting the number of Kanbans at workcenters in an unstable production environment is presented and analyzed. The adjustment methodology is presented in a step-by-step manner. This is followed by three examples presented within the context of a simulation model of a hypothetical shop. The first example will illustrate the methodology while the last two examples will demonstrate how well the methodology ...

An investigation of the factors influencing the number of Kanbans required in the implementation of the JIT technique with Kanbans

Abstract Japanese production environments exhibit a number of characteristics not present in many American firms that contribute to the success of the just-in-time (JIT) system with Kanbans. However, because of the advantages of a JIT system with Kanbans many firms have attempted implementation without the existence of the appropriate production environment to do so. The purpose of this paper is first to identify those factors that will influence the number of Kanbans required at a workcentre for the production manager implementing a JIT system in an uniquely American production environment. The factors that will be identified include the throughput velocity (i.e. the rate at which items flow through a workcentre machine), the coefficient of variation in processing times (i.e. the degree of variability of processing times), the machine utilization (i.e. the availability of slack time on a machine), and, autocorrelation of processing times (the degree to which successive processing times on a specific mach...

A comparative analysis of the COVERT job sequencing rule using various shop performance measures

The COVERT job shop dispatching rule was tested extensively twenty years ago with impressive results, however, since then it has been included in only one comparative analysis with other sequencing rules, and, reported instances of its application have been infrequent. In this paper, the COVERT rule is examined in detail relative to its applicability, its sensitivity to various operating parameters and performance measures, and its performance compared to several other sequencing rules including truncated SPT rules, dynamic slack rules and modified duedate rules. The performance of COVERT is examined for a variety of tardiness measures. The examination is conducted within the context of a simulation model of a machine-constrained job shop with serial jobs and random routings. The results indicate that COVERT performs well as a sequencing rule and in most instances was superior to the other sequencing rules tested both directly and across varying degrees of due-date tightness.

Multiple criteria R&D project selection and scheduling using fuzzy logic

Abstract Research on R&D project selection has recently focused on multiple criteria modeling of R&D portfolios. These models include mathematical programming models, decision theory models and scoring models. Each of these model types has proven to be effective in a limited sense, but very few address project scheduling in conjunction with other, more traditional project selection goals. In this paper, an alternative approach is presented which uses fuzzy logic within a standard beam search approach to evaluate a single objective function that reflects the multiple objectives of the R&D project selection problem. These objectives include tradiational R&D objectives such as expected profit and portfolio of success, as well as project scheduling. The model uses a heuristic approach to project scheduling. The methodology is illustrated using an example problem that reflects a realistic R&D problem in terms of problem size, goals, objectives, and constraints. A benchmark study was also conducted to access the computational effectiveness of the proposed approach.

A simulation-based experimental investigation of supply/timing uncertainty in MRP systems

SUMMARY The uncertainty inherent in material requirements planning (MRP) systems is of two general types: demand uncertainty and supply uncertainty. Supply uncertainty is a result of late deliveries (timing) or order shrinkage (quantity) or both. The purpose of this paper is to examine the impact of operating policies on an MRP system given supply uncertainty resulting from timing factors, specifically the uncertainty caused by variability in the lead time of purchased parts. Experiments arc conducted to assess the impact of four factors: the amount of lead time variability, the amount of safety stock or safety lead time, the lot-size rule, and the holding cost and lateness penalty, on the total cost of the MRP system given supply/timing uncertainty. An MRP/Production simulator is employed to perform the experiments. Practical guidelines for the manager of an MRP system with supply/timing uncertainty are presented.

A Goal Programming Approach to the Optimization of Multi response Simulation Models

Abstract This paper presents a direct search approach to the optimization of multiresponse simulation models. The paper develops an approach within the framework of goal programming and uses a modified pattern search routine developed for this purpose. The algorithm and a graphical example are presented. The advantages and disadvantages of the approach determined from computational experiences with the solution procedure are discussed.

A mathematical programming approach for determining workcentre lotsizes in a just-in-time system with signal Kanbans

SUMMARY An essential condition necessary for the implementation of the Japanese just-in-time (JIT) technique with Kanbans is Small setup times relative to processing times. Without this condition bottlenecks occur at workcentres which delay production. However, the Japanese have developed a variation of the strict JIT technique that employs a special type of Kanban, referred to as a ‘signal Kanban’, at workcentres with relatively high setup times. While a normal Kanban triggers the production of larger than normal lots this altered version of the JIT technique provides an alternative approach for firms that desire to use the JIT technique, but are unable to reduce setup times at all workstations. The purpose of this paper is to describe the signal Kanban technique and demonstrate two versions of an integer mathematical programming approach for determining the optimal lotsizes to be used in conjunction with signal Kanbans. A simulation model is subsequently employed to test the effectiveness of the integer...

Allocation of research and development funds: A zero-one goal programming approach

The research and development project selection process is one of the most difficult and important problems faced by management. It is typically complicated by indivisibility of projects and multiple and conflicting objectives, in addition to limitations on funding, facilities, and qualified researchers. In this paper a case example involving a high technology electrical equipment manufacturer is developed to illustrate this problem using zero--one goal programming to accommodate indivisibility of projects in addition to multiple and conflicting goals. The model presented is an attempt to provide managers with a robust tool for allocating scarce resources among research and development projects.

Solving Multiple Response Simulation Models Using Modified Response Surface Methodology Within A Lexicographic Goal Programming Framework

Abstract paper describes a new procedure for obtaining satisfactory solutions to multiple-response, multiple-input simulation models. A modified version of response surface methodology is incorporated to obtain input values which meet user specified goals for the responses. The approach is illustrated with three examples which demonstrate the method. The desirability of incorporating this approach into an interactive computer mode is also discussed.

R&D project selection and scheduling with a filtered beam search approach

Abstract Models developed for selecting an optimal portfolio of R&D projects from among a pool of available projects do not generally include project scheduling as part of the selection criteria. Typically after a portfolio of projects is selected according to various selection criteria, they are subsequently scheduled. If it is not possible to schedule the selected projects through various research facilities and/or stages given the available resources, projects may be replaced with others requiring less time, or resources may be increased, which can result in a suboptimal portfolio. In this paper, project scheduling is included in the selection process, with a heuristic filtered beam search approach. Projects are selected on the basis of traditional selection criteria such as expected profits, as well as the makespan of the portfolio. The heuristic search procedure is demonstrated by an in-depth example and computational experimentation.