Semiconductor manufacturing simulation design and analysis with limited data: IE: Industrial engineering
- Resource Type
- Conference
- Authors
- Biller, Bahar; Dulgeroglu, Onur; Corlu, Canan Gunes; Hartig, Michael; Olson, Ronald J.; Sandvik, Peter; Trant, Gerald
- Source
- 2017 28th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) Advanced Semiconductor Manufacturing Conference (ASMC), 2017 28th Annual SEMI. :298-304 May, 2017
- Subject
- Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Analytical models
Data models
Uncertainty
Silicon carbide
Manufacturing
Stochastic processes
Random variables
Data
Input Uncertainty
Simulation
- Language
- ISSN
- 2376-6697
This paper discusses simulation design and analysis for Silicon Carbide (SiC) manufacturing operations management at New York Power Electronics Manufacturing Consortium (PEMC) facility. Prior work has addressed the development of manufacturing system simulation as the decision support to solve the strategic equipment portfolio selection problem for the SiC fab design [1]. As we move into the phase of collecting data from the equipment purchased for the PEMC facility, we discuss how to redesign our manufacturing simulations and analyze their outputs to overcome the challenges that naturally arise in the presence of limited fab data. We conclude with insights on how an approach aimed to reflect learning from data can enable our discrete-event stochastic simulation to accurately estimate the performance measures for SiC manufacturing at the PEMC facility.