Technique to improve visibility for cycle time improvement in semiconductor manufacturing

• Main Authors: Rahim S.R.A., Ahmad I., Chik M.A.
• Other Authors: 55602785200
• Format: Conference paper
• Published: 2023
• Subjects: Advance Productivity Family (APF); Manufacturing Execution Systems (MES); Work In progress (WIP); Automation; Benchmarking; Data acquisition; Data transfer; Manufacture; Productivity; Automated data; Automated systems; Customer trust; Cycle time; Cycle time improvements; Cycle time reduction; Data collection; Key performance indicators; Manual work; Manufacturing environments; Manufacturing Execution System; Product time; Real problems; Real roots; Real situation; Real time data collections; Semi-conductor fabrication; Semiconductor manufacturing; Work in progress; Semiconductor device manufacture

Cycle time for a product is one of the key performance indicators in semiconductor manufacturing. Reduction of cycle time will shorten product time to market, increase throughput, reduce operational cost and develop customer trust. Semiconductor manufacturing that process 40,000 to 50,000 work-in-progresses (WIP), usually takes 50 to 70 days, 300 to 400 equipments and 300 to 900 steps to complete. Thus, any task related to manual data collection to make indices reports or analysis usually needs high resources requirements to spend for manual work and risk for mistake. In the modern facility of semiconductor fabrication, a system like Manufacturing Execution Systems (MES) was implemented to ease the process and operation traceability. The information is well kept in the appropriate databases. Many applications then are integrated with MES database to perform indices reports. In this paper, the improve method for data collection related to cycle time improvement is introduced. In this approach, the automated systems was developed using existing Advance Productivity Family (APF) programming platform to collecting the data. The system is integrated between MES and APF to have the real time data collection and analysis. In the systems, manual data collection is replaced with respective automated data transfer from real situation in the manufacturing environment. This program then able to shows real root caused with proper relational charting to display real problem for engineering to prioritize and resolve respectively. As a result, 39% reduction of cycle time gained by implementing this technique. The system has successfully implemented and supports the cycle time reduction. � 2012 IEEE.