Minimizing WIP inventory in reliable production lines

Article Abstract:

This work deals with the well-known buffer allocation problem in short reliable production lines. The objective is to find the optimal buffer allocation (OBA) that minimizes the average work-in-process (WIP) inventory, subject to a minimum required throughput. The study leads to some insights concerning the evolution of the throughput and WIP as a function of the ordered buffer allocations. In the case of balanced lines, it is observed that the so-called self-similarity phenomenon prevails. It is also pointed out that the choice of the throughput level is critical for finding the OBA that minimizes the average WIP. Also a heuristic algorithm is proposed to find the OBA, which reduces the search space by over 50% compared to enumeration. [C] 2001 Elsevier Science B.V. All rights reserved. Keywords: Stochastic modelling; Production lines; Optimization; Buffer allocation; WIP inventory; Heuristic algorithms; Self-similarity

United States, Management, Usage, Algorithms, Inventories, Optimal stopping (Mathematical statistics), Buffer stocks

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Integrating material coordination and capacity load smoothing in multi-product multi-phase production systems

Article Abstract:

The integration of capacity load smoothing and materials requirements planning in production systems would require changes in the load-based work-order release strategy used. It is shown that proactive work-order release performs better than reactive release but worse than immediate release. The effects of selective work-order release on inventory holding costs also vary according to product type.

Inventory Control, Material requirements planning

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Learning-induced control model to allocate managerial resources for production technology development

Article Abstract:

Production technology development is critically affected by the policy on production knowledge on the part of middle managers. The manufacturing learning propensity in favor of a certain course of action towards technology development significantly affects resource allocation. The effects of learning may be negligible during initial stages but accelerates as implementation proceeds.

Models, Learning, Teaching models

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