On multi-stage production/inventory systems under stochastic demand

This paper was presented at the 1992 Conference of the International Society of Inventory Research in Budapest, as a tribute to professor Andrew C. Clark for his inspiring work on multi-echelon inventory models both in theory and practice. It reviews and extends the work of the authors on periodic review serial and convergent multi-echelon systems under stochastic stationary demand. In particular, we highlight the structure of echelon cost functions which play a central role in the derivation of the decomposition results and the optimality of base stock policies. The resulting optimal base stock policy is then compared with an MRP system in terms of cost effectiveness, given a predefined target customer service level. Another extension concerns an at first glance rather different problem; it is shown that the problem of setting safety leadtimes in a multi-stage production-to-order system with stochastic lead times leads to similar decomposition structures as those derived for multi-stage inventory systems. Finally, a discussion on possible extensions to capacitated models, models with uncertainty in both demand and production lead time as well as models with an aborescent structure concludes the paper

Push verse pull:Inventory-leadtime tradeoff for managing system variability

We study a two-stage push–pull system in an assemble-to-order manufacturing environment. Modelling the system as an inventory-queue model, we construct a decision model to determine the optimal stock level of the semifinished base product and the optimal leadtime of the finished products that will minimize the total operational cost. We analytically characterize the structure of the optimal policy. For systems with moderate demand and upstream processing time variabilities, there exists a threshold determined purely by the tradeoff of operational costs so that when the upstream utilization is above the threshold, the push–pull strategy is optimal; otherwise the pure-pull strategy is optimal. When the inter-arrival time or the upstream service time follows a general probability distribution, the optimal policy depends on the demand or process variability at the upstream stage. Our results can be used to guide managers in selecting the right inventory and leadtime strategy to cope with system variability. We find that in comparison of the downstream variability, under some mild condition, the upstream variability has a more significant impact on the choice of the optimal policy, the corresponding inventory, and lead time. Further, the guaranteed/constant downstream processing time does not always benefit the supply chain performance

Planning complex engineer-to-order products

The design and manufacture of complex Engineer-to-Order products is characterised by uncertain operation durations, finite capacity resources and multilevel product structures. Two scheduling methods are presented to minimise expected costs for multiple products across multiple finite capacity resources. The first sub-optimises the operations sequence, using mean operation durations, then refines the schedule by perturbation. The second method generates a schedule of start times directly by random search with an embedded simulation of candidate schedules for evaluation. The methods are compared for industrial examples

Microprocessor manufacturing throuhput time variability

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1994, and Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1994.Includes bibliographical references (p. ).by Jason Ku.M.S

Quantitative models for reverse logistics

This article surveys the recently emerged field of reverse logistics. The management of return flows induced by the various forms of reuse of products and materials in industrial production processes has received growing attentio

The power of cross-functional teams in driving total quality

Garrett Canada, a Division of Allied-Signal Aerospace Canada, has been a member of the Canadian aerospace industry for 40 years. Although Garrett Canada has always been a profitable division with a solid market share, the changing and turbulent business environment and globalization of the aerospace industry has created new demands and challenges. The marketplace is demanding faster introduction of new products, as well as shorter leadtimes for repairs and spares. It was recognized that reducing cycle times for new products and for ongoing production would not only satisfy our customers, it would also enhance our business performance through reduced inventories, lower past due, and more responsiveness to change. It was evident that drastic function changes were required if we were to maintain our position as a premier aerospace supplier. The challenge was to convert a stable, somewhat slow-paced work environment with strong functional boundaries into a boundaryless world class team functioning in a total quality environment and focused on customer satisfaction. Complete and uncompromised customer satisfaction has become our driving force, with Total Quality being our engine to continuously improve our processes and increase our speed. The way in which this transition has been brought about is the subject of this presentation