The first paper summarized below analyzes the problem of
production and inventory planning in a manufacturing environment that
incorporates remanufacturing of returned products. The second discusses the
problem of where to locate drivers in the trucking industry in the face of
considerable uncertainty about future demands for movements. The third looks at
the optimal timing of phasing in new and phasing out old products in the
volatile health care industry. All three studies can be found in full in the
April issue of IIE Transactions (Vol. 36, No. 4).
[ILLUSTRATION OMITTED]
Remanufacturing
planning
The benefits associated with remanufacturing extend far
beyond environment-related savings such as using fewer virgin natural resources
and reducing industrial waste. Remanufacturing often represents a cheaper way
for firms to satisfy customer demand than manufacturing. This is because
remanufacturing can effectively reduce material, energy, and waste disposal
costs. In order to reap these potential economic benefits, companies such as
Kodak, Xerox, IBM, HP, Bosch, and GM manage remanufacturing in addition to their
regular manufacturing operations.
The major challenge in coordinating these operations is
the uncertainty associated with the timing, quantity, and quality of returned
used products. Although manufacturers can influence the timing and quantity of
returns through buy-back campaigns and trade-in promotions, the variability in
quality remains a significant problem. The reason for this is that the required
remanufacturing effort, in terms of both cost and time, is largely determined by
the quality condition of the returns.
In "The Effect of Categorizing Returned Products in
Remanufacturing," Necati Aras, Tamer Boyaci, and Vedat Verter develop an
analytical model of a remanufacturing facility that operates together with a
manufacturing plant to satisfy demand. Optimizing this model, they assess the
impact of exploiting returned product quality information.
The authors' results show that by categorizing the
returned products on the basis of their quality, firms can develop more
intelligent production, inventory, and disposal policies and thereby achieve
significant cost savings. Perhaps more importantly, their numerical analyses
indicate to managers that the scale of these savings increases as the quality
variability in the returned products increases, as the overall quality of
returns decreases, as customer demand rate decreases, or as the return
percentage increases. They also show that it is always preferable to prioritize
higher-quality returns in remanufacturing.
CONTACT: Tamer Boyaci; (514) 398-4047;
tamer.boyaci@mcgill.ca; Faculty of Management, McGill University, 1001
Sherbrooke St. West, Montreal, Quebec, Canada H3A 1G5
