Recoverable manufacturing is becoming an increasingly important alternative to ® rms as they develop environmentally sound strategies aimed at minimizing waste and resources. Remanufacturing helps minimize costs and conserve resources through methods such as extending product life cycles via refurbishments and technical upgrades which require the use of only a fraction of the resources and energy associated with a new product. In this study the impact of product structure complexity on other managerial operating decisions is examined in a remanufacturing environment. It is shown that in the remanufacturing environment, with its greater inherent uncertainty, product structure complexity signi® -cantly a ects the choice of scheduling policies used. Recommendations as to the scheduling policy to use for a dominant product structure in a given environment are made.
The use of repair as an alternative to the replacement of products is a growing trend in many industries, especially those employing expensive assets. Repair shop environments are characterized by a greater degree of uncertainty than traditional job or assembly shop environments, and this introduces unique managerial complications. In this study, scheduling policies are examined in the repair shop environment where no end-item spares are available or where the spares stocking decision is deferred until the minimum obtainable¯owtimes for enditems are established. Previous studies of scheduling policies have focused on the case where spares are allowed and have not considered all of the sources of variation in the repair environment. The model developed in this study incorporates these sources of uncertainty, as well as other factors likely to in¯uence repair shop performance. The results show that the variability in repair shops is su ciently higher than in traditional job or assembly shops to warrant di erent scheduling policies than those previously reported. The choice of scheduling policy to provide minimum¯owtimes and RMS tardiness is operating-environment speci® c, and clear guidelines are presented for the manager in a repair shop environment.
Prior research substantiates the value of compensating customers for poor quality. However, little guidance has been provided for the recovery of errors while service delivery is in progress. The authors provide analytical models inspired by reliability theory to guide managers in allocating their investments in service recovery. Models are constructed to achieve four different objectives and converted to Lagrangian formulations for solution. Example solutions illustrate the contrast in investment allocations.
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