Suchergebnisse

The literature is reviewed on buffer stock allocation strategies in
serial production lines. A number of experiments are conducted to
analyse the behaviour of work‐in‐process inventory given that the
objective is to maximise throughput. Both balanced and unbalanced lines
are examined. The same analysis will be repeated for assembly type of
production lines (merging lines). A key concept in this article is the
"long pull" (or constant work‐in‐process inventory) Kanban
system.

AbstractThis paper considers a discrete time, single item production/inventory system with random period demands. Inventory levels are reviewed periodically and managed using a base‐stock policy. Replenishment orders are placed with the production system which is capacitated in the sense that there is a single server that sequentially processes the items one at a time with stochastic unit processing times. In this setting the variability in demand determines the arrival pattern of production orders at the queue, influencing supply lead times. In addition, the inventory behavior is impacted by the correlation between demand and lead times: a large demand size corresponds to a long lead time, depleting the inventory longer. The contribution of this paper is threefold. First, we present an exact procedure based on matrix‐analytic techniques for computing the replenishment lead time distribution given an arbitrary discrete demand distribution. Second, we numerically characterize the distribution of inventory levels, and various other performance measures such as fill rate, base‐stock levels and optimal safety stocks, taking the correlation between demand and lead times into account. Third, we develop an algorithm to fit the first two moments of the demand and service time distribution to a discrete phase‐type distribution with a minimal number of phases. This provides a practical tool to analyze the effect of demand variability, as measured by its coefficient of variation, on system performance. We also show that our model is more appropriate than some existing models of capacitated systems in discrete time. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007

PurposeThe production dice game is a powerful learning exercise focusing on the impact of variability and dependency on throughput and work‐in‐process inventory of flow lines. This paper seeks to extend the basic dice game along the following lines. First, it will allow operations to take place concurrently as opposed to sequentially, which works better in a classroom setting. Second, it will allow both starvation and blocking of the line. Third, it will consider balanced lines with workstations characterized by different degrees of variability. Finally, it aims to use different sets of dice in order to represent a wide range of variation coefficients of the production line. The obtained insights can be extended to a supply chain context as well. The developed game can be played on‐line and the software is freely downloadable.Design/methodology/approachThe paper extends the dice game and offers an easy‐to‐use simulation tool.FindingsThe key aspect of students' learning experience is the understanding of the relationship between variability and throughput in an environment with dependent workstations and limited buffers.Originality/valueA rather complicated research question is transformed into an easy‐to‐use simulation tool that in no time can be used by practitioners and students.