Model for throughput performance measures and monitoring system in semiconductor industry

• Main Author: Ng, Poh Lay
• Format: Thesis
• Language: English
• Published: 2009
• Subjects: TS Manufactures
• Online Access: http://eprints.utm.my/10058/1/NgPohLayMFKM2009.pdf

Manufacturing Science has been a proven discipline to further enhance traditional manufacturing practices where manufacturing performance can be quantify, measure and improve. Factory Physics is one of the approaches in manufacturing sciences. Through the application on Factory Physics principles, manufacturing performance gap can be systematically identify for throughput maximization. Managing manufacturing throughput is always a challenge as most of the manufacturing shop floor information available are either qualitative or quantitative but in piece mail which practically make us almost impossible to directly use the information for systematic scientific analysis. This is mainly driven by the dynamic of operation behaviors primary influence by manufacturing variability. Variability in manufacturing is unavoidable and sometime just simply unpredictable. It consists of the varies in people skills, process requirement, equipment performance and products. Buffering the shop floor with excessive work in progress (WIP) is the most common undocumented tribal knowledge to overcome throughput uncertainty. As a result some people even describe that running manufacturing is an art. Four fundamental models for throughput performance measures and monitoring system for a semiconductor assembly plant being developed and introduced. Overall manufacturing system performance expected to be further enhanced and a common ground for continual improvement to be established through this systematic modeling approach with the application of the basic concept of Factory Physics Principles. Based on initial mid range financial analysis over seven months, there is a potential opportunity for USD48000/week incremental Gross Margin through additional 20% of quality throughput couple with 30% Cycle time improvement.