Abstract

Most hi-tech industries owe at least some of their success to being in the right place at the right time. This is especially true for the aircraft parts manufacturer approval (PMA) industry. A PMA is both a design approval and a production approval. It is issued for the production of modification or replacement parts for aircraft, which includes materials, parts, processes, and appliances. In the current economic climate, airlines throughout the world are looking for partners with financial stability. The reason is simple, they want partners that will continue to support them with extra savings opportunities in the short and long-term future. As more and more PMA companies are advertising through the Internet, a supplier performance measurement model applying to each of these networked organizations will facilitate the airline selection of long-term PMA partners. In this chapter, the Mahalanobis Taguchi System (MTS) approach, a multivariate data based selection system, will be used to identify the promising PMA suppliers. Suppliers who are known to be promising are called promising groups and their performance data sets are used to create a reference metric for the promising PMA supplier population. In view of the synergetic performance of neural network and data mining technologies, it is expected that this MTS-based PMA partner selection method, implementing through a neural data mining system (NDMS) will provide a practical solution in the identification of the promising PMA suppliers. Document type: Part of book or chapter of book

Abstract

The United States Integrated Textile Complex (USITC) consists of fiber, textile, apparel, and retail firms who manufacture and distribute natural and synthetic fiber products. In today`s competitive global economy, USITC companies who team together to form supply chains require relationships which promote responsiveness to consumer demand, encourage business partnerships, and make effective use of resources. These supply chains, or pipelines, are being analyzed to improve time and cost performance. Enterprise analysis is the application of analysis methods and simulation tools to predict integrated performance of these pipelines. Through the use of scenario analysis, various alternatives in pipeline coordination and configuration can be assessed. Simply put, the end result is to design the pipeline so that the product the customer demands is delivered, in the right place, at the right time. In September 1996, industrial participants of the Demand Activated Manufacturing Architecture (DAMA) project completed the Phase 1 pipeline analysis study. The analysis identified opportunities to improve productivity and efficiency among five supply chain members, and proposed a generic modeling architecture and methodology that, if implemented, would identify actions necessary to improve supply-chain coordination among its members. The architecture and methodology are being pursued during the Phase 2 analysis, which is scheduled to be completed by the end of FY 1997. The goal of the Phase 2 analysis is to propose actionable recommendations to supply-chain members leading to a reduction of pipeline lead-time by 50%. Document type: Report