Title :
Scrapping small lots in a low-yield and high-price scenario
Author :
Wu, Muh-Cherng ; Chiou, Chie-Wun ; Hsu, Hsi-Mei
Author_Institution :
Dept. of Ind. Eng. & Manage., Nat. Chiao Tung Univ., Taiwan, Taiwan
Abstract :
Some wafers in a lot may become spoiled after they are processed at a workstation; such a lot is called a small lot. In a low yield and high price scenario, scrapping small lots may increase revenue and profit; yet, this notion has seldom been examined. This study presents a model for formulating the decision-making problem of scrapping small lots. A genetic algorithm is used to solve the problem when the solution space is large. An exhaustive search method is used when the solution space is small. Some numerical examples are used to evaluate the outcome of scrapping small lots. The profit obtained by the proposed scrapping method may be up to 23% higher than that obtained without scrapping.
Keywords :
decision support systems; genetic algorithms; integrated circuit economics; integrated circuit yield; production management; decision-making problem; genetic algorithm; high-price; low-yield; profit; revenue; small lots; wafers; Chemical processes; Costs; Decision making; Fabrication; Genetic algorithms; Merging; Production facilities; Search methods; Semiconductor device modeling; Workstations;
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
DOI :
10.1109/TSM.2003.822732
