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|Authors: ||劉宏麟;Liu, Hung-Lin|
|Keywords: ||晶圓代工;曝光機台;整數規劃;最佳化;敏感度分析;wafer fabrication;exposure device;integer programming;optimization;sensitivity analysis|
|Issue Date: ||2018-08-31 11:23:51 (UTC+8)|
;Wafer output in today’s wafer fabrication plants mostly depends on production related schedules arranged by
fab manager、senior engineers and operations performed by direct operators onsite based on production scheduling needs or machine conditions, and usually cannot be systematically analyzed, compared and assessed with scientific methods. Therefore, abilities and experiences of senior engineers or direct operators onsite determine whether wafer output will be smooth. In view of this, utilization of improved machine readiness and cost reduction has become an important issue in today’s wafer output operations. The model in this study is the common model of production process alignment in Taiwan’s general wafer fabrication plants. It takes into account (1) different plant sites, (2) limitations on type and number of exposure devices responsible for production, (3) percentage of machine readiness (%), (4) minimum number of machines running for production in each time frame, and (5) numbers of machines running for production in different time frames for wafer output optimization as the scope of research.
In this study, a mathematical optimization model is created with integer programming as the framework to help decision makers in wafer fabrication plants with arrangement for unified planning of exposure devices in the hope of minimizing associated arrangement costs and thus increasing revenue. When external environments and constraints change, parameters can be adjusted anytime according to the latest conditions to rearrange subsequent numbers of exposure devices and quantities of wafer output. At the same time, various related parameters can be proactively adjusted according to trends of change in sensitivity analysis of various parameters to cope with arrangement programs for numbers of exposure devices and quantities of wafer output.
In this study, corresponding constraint parameters were defined based on basic data and individual constraints, and data were input into the Lingo 12.0 software package via Excel 2007 for problem solving to obtain resultant target values of optimized minimum costs. Testing was performed on customer required wafer output operations run by wafer fabrication plants as examples. A comparison was made between the test results and human experience-based decision making and showed that the model in this study produced clearly better results. Therefore, this model is applicable to arrangement planning for multiple types of exposure devices at different plant sites in different time frames and can serve as an important reference for business decision makers.
|Appears in Collections:||[土木工程學系碩士在職專班] 博碩士論文|
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