Abstract

Equipment throughput is one of the most critical parameters for production planning and scheduling, which is often derived by optimization techniques to achieve business goals. However, in semiconductor manufacturing, up-to-date and reliable equipment throughput is not easy to estimate and maintain because of the high complexity and extreme amount of data in the production systems. This article concerns the development and implementation of a throughput management system tailored for a semiconductor wafer fabrication plant (Fab). A brief overview of the semiconductor manufacturing and an introduction of the case Fab are presented first. Then, we focus on the system architecture and some concepts of crucial modules. This study also describes the project timescales and difficulties and discusses both tangible and intangible benefits from this project.

Highlights

  • Equipment throughput (ETH), the basis of capacity management, is absolutely necessary information for practitioners in manufacturing because its timeliness and reliability significantly affect the performance of production systems

  • Filter ensures the data used for calculating Wafer per hour (WPH) are qualified and noiseless; calculator, the core of this system, periodically computes WPH by the process recipe for all equipment units in the fabrication plant (Fab); monitor is a platform for equipment performance monitoring and the detection of process malfunctions; analytics is capable of classifying abnormal recipes into several categories and provides various visual tools for reviewing corresponding historical processing logs

  • The monitor module is powered by control charts, which are based on the statistical process control (SPC) to monitor equipment WPH by recipes in order to enhance manufacturing productivity and reliable results of capacity planning

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Summary

Introduction

Equipment throughput (ETH), the basis of capacity management, is absolutely necessary information for practitioners in manufacturing because its timeliness and reliability significantly affect the performance of production systems. Repeated sampling is necessary due to the existing random noise in processing This method often relies on a massive workforce to maintain its reliability; even in a highly automated Fab with an advanced manufacturing execution system, it can still be time consuming because of complex data screening and pre-treatment. Due to the advanced intelligent lot scheduling and dispatching built around AMHS to control and execute the complex handling operations precisely, there are many manufacturing execution-related systems (MES) for supporting an automatic Fab. the system integration and data synchronization become another challenge for developing a WPH management system. Please note that I must keep the company’s name confidential, the information for apprehending the concept of the proposed system and the key points of implementation is covered

Preliminary Information on Semiconductor Manufacturing
Semiconductor Manufacturing
Equipment Capacity
WPH Improvement
Overview of the Case Fab
WPH Management System
Systems Architecture
Filter
Calculator
Monitor
Analytics
What-If Analysis
Timeline Motion Chart
Working Procedure
Design
System Deployment
Effective System Verification
Preparation of Job Arrangement
Data Validation and Exception Handling
System Maintenance
Findings
Conclusions
Full Text
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