The Block-Based Cycle Time Estimation Methodology for Wafer Fabrication Factories

• Main Authors: Hung-Wen Huang, 黃宏文
• Other Authors: Shu-Hsing Chung
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/37388372802798817637

博士 === 國立交通大學 === 工業工程與管理系 === 91 === Cycle time plays a critical role in production planning. However, the interactive effects between some factors such as process complexity and variety of workstations, leads to the difficulty in estimating cycle time. The purpose of this dissertation is to develop a cycle time estimation algorithm with high estimation accuracy and response capability. The core base of cycle time estimation is to find out the reasons for material flow congestion, caused by the heavy machine loading and batch lots accumulation. Recognizing that the batch size difference among machine types is a major factor contributing to the congestion of production flow, the process flow of each product type is divided into the same number of blocks as that of the batch machines passing through. This dissertation thus develops an block-based cycle time (BBCT) estimation algorithm to estimate the product cycle time, consists of the waiting time due to batching and loading factor in every block. The corresponding waiting time was estimated using the M/M/c queueing model and batch factor flow time (BFFT) estimation algorithm. The basic BBCT estimation algorithm is developed for the system only producing normal class products. Considering engineering lots usually existed in shop floor, a revised BBCT estimation algorithm is proposed also. To verify the performance, a simulation model is constructed to evaluate the accuracy of cycle time estimation with BBCT algorithm. The experiment study showed that the BBCT performance was better than that of M/M/c queueing model and of the revised Conway’s formula by Su (1998) under the system environment of higher loading (90%), medium loading (70%) and lower loading (50%) for all normal class scenario and for engineering lots existing scenario. The related experiments also showed that the BBCT could effectively estimate the workstation utilization rate. BBCT thus is a good tool for production planning and control.