Search

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ijpe.2008.08.013 Byline: Handik Widiarta (a), S. Viswanathan (a), Rajesh Piplani (b) Keywords: Forecasting; Top-down forecasting; Bottom-up forecasting; MA(1) process; Exponential smoothing Abstract: We study the relative effectiveness of top-down (TD) and bottom-up (BU) strategies for forecasting the aggregate demand in a production planning framework. The aggregate demand series is composed of several correlated subaggregate components (or items), each of which is assumed to follow a stationary time series process, which is correlated over time. As is common in a production planning environment, it is assumed that exponential smoothing is used as the forecasting technique under both strategies. We analytically show that there is no difference in the relative performance of TD and BU forecasting strategies when the time series for all of the subaggregate components follow a first-order univariate moving average [MA(1)] process with identical coefficients of the serial correlation term. We then perform a simulation study to examine the case when the coefficients of the serial correlation term for the subaggregate components are not identical. It is found from the simulation study that the difference in the performance of the two forecasting strategies is relatively insignificant when the correlation between the subaggregate components is small or moderate. Author Affiliation: (a) Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore (b) School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore

To provide good after-sales service, an efficient and reliable repair network is necessary. This paper describes a case study at a company providing repair services on behalf of a computer manufacturer in the Asia-Pacific region. Faulty parts' repair can be carried out by the part manufacturers or third-party repair vendors, who are located in different countries. Thus, in designing the closed-loop repair network, their locations must also be taken into account. Economical changes in countries may cause the part manufacturers and third-party repair vendors to shift their business to other countries. This study examines the company's redesign of its repair network. The results show that as most part manufacturers and third-party repair vendors are located in China and Taiwan and supply of faulty parts are relatively high in the East Asian countries, operating new distribution centres in China and Taiwan for consolidation of parts before they are sent out for repair would lead to lower total logistics costs. Keywords: Closed-loop service network; Repair network; Facility location allocation model

Supplier-owned inventory (SOI) is an arrangement where the vendor is responsible for maintaining and controlling the inventory at the buyer's premises. The buyer draws the required quantity of the item from this SOI as and when required as if it were its own component store. In return, the vendor is provided with the latest demand information to control its inventory costs. In this paper, we develop a model to analyze and evaluate the SOI strategy. We conduct a numerical study to understand how the various model parameters affect the total costs under the SOI arrangement. The numerical study reveals that the total supply chain costs will never be higher under the SOI arrangement. In general, the benefits of the SOI arrangement to the supply chain are higher when the buyer that adopts SOI accounts for a larger percentage of the supplier's total demand. Keywords: Supplier-owned inventory; Mathematical models of inventories; Inventory management