Flexibility and enhancing volume flexibility in just in time

In recent years as the technology has been developing rapidly, the variety of the products served to the customers has been increasing. Firms have thereof tended to JIT (Just in Time) production systems including the philosophy of the flexibility in order to overcome the demand fluctuation problems while rivalry increases. The biggest desire of all manufacturers in today?s world is to satisfy the order in a shorter time, more rapidly and without pausing for retooling even in the fixed volume. This is possible as the efficient and less costly manufacturing without waste, the manufacturing system?s speed in reconfiguring itself to meet changing demands and the system?s ability to adjust to customer?s preferences are provided. The issue of strategic flexibility in manufacturing is reviewed to establish the links between output flexibilities and resource level characteristics. Through these links, and considering a JIT environment, the need for flexible Kanban determination is then recognized with respect to demand fluctuations in the marketplace. This is also confirmed through a review of the related literature. In this study, firstly JIT production system was defined by focusing on its importance. Volume flexibility was studied in details by defining the production flexibility and its classifications. A method was proposed and it was investigated by underlining the improvement of volume flexibility, and the definition and rules of Kanban systems, which is the basis of the JIT production system. Based on the need for the flexible Kanban, this method is proposed, using an integer linear programming technique, to flexibly determine the number of Kanban for each stage of a JIT production system, minimizing total inventory cost for a given planning horizon. The effectiveness of the proposed method is then examined and compared with the results for the conventional method of fixed Kanban determination. The comparison proved a cost advantage for the proposed method over the conventional method in fluctuating demand situations while the cost advantage increases with increase in demand fluctuations.