Determining the number of kanbans and withdrawal lot sizes in a multistage and multiproduct assembly system - I Nyoman Pujawan; Anulark Pinnoi; Pandey, P.C.; Nagarur, Nagendra N.; Higher Education Project ADB Loan 1253 INO Government of Indonesia (Bangkok : Asian Institute of Technology, 1997)
There has been a growing body of literature dealing with kanban system. Various models have been proposed with a wide range of solution techniques. However, there is no publication of work in the area of kanban system which considers the withdrawal lot size as one of the decision variables. If transportation cost of materials between workstations is considered to be important, determination of withdrawal lot sizes is essential. In this situation, a trade off between inventory holding cost and transportation cost will yield a more economical inventory system. In this study we propose a mathematical model to determine simultaneously the number of production kanbans, the number of withdrawal kanbans, and withdrawal lot size for each item. The initial model is a non linear integer program and becomes a linear integer after transforming some non linear equations and fixing one variable. The model can be applied in a multistage and multiproduct assembly system. Four hypothetical cases are presented to apply the model. Each case represents different complexities of the simplified multistage and multiproduct assembly system. A number of different experiments are conducted to learn the relationships among variables and parameters. Different scenarios of demand for each hypothetical case are investigated to learn the effect of different level and different variance of the demand to the number of production and withdrawal kanbans as well as the cost of the system. We also study the effect of cost parameters to the optimal size of withdrawal lot. The robustness of the decision variable values with respect to the change of cost parameters are also studied. A number of consequences are derived from the findings of the experiments. These consequences provide a good insight into the development of heuristic algorithm. Since the model is hard to solve, the computation time for complex problem is unreasonably long. To alter the computation time we propose a heuristic algorithm for the uncapacitated version of the model. The algorithm has been tested with many different cases and scenarios. The tests show that the algorithms are able to produce solution with discrepancy of the objective function less than 3.5% from the optimal solution with far less amount of computation. At the end of the study we also suggest the future research related to this topic.
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies
Thesis (M.Eng.) - Asian Institute of Technology, 1997
Keywords: Just-in-time systems