2026-09-19T07:26:53Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/323312022-01-13T07:54:19Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Gregory J. McRae and Karen K. Gleason.
Chen, Yue (Yue Nina)
Massachusetts Institute of Technology. Dept. of Chemical Engineering.
Massachusetts Institute of Technology. Department of Chemical Engineering
2006-03-29T18:34:51Z
2006-03-29T18:34:51Z
2005
2005
http://hdl.handle.net/1721.1/32331
61369695
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2005.
Includes bibliographical references (p. 151-157).
Competition requires companies to make decisions that satisfy multiple criteria. Considering profitability alone is no longer sufficient. Ignoring environmental considerations will not only expose a company to potential regulatory costs, but also damaged public image, both of which in turn have negative effect on the economic well- being of companies. At the same time, the fast changing business environment requires companies to reach decisions in a speedy fashion. This work describes a decision- making framework that addresses the obstacles in integrating environmental considerations into technology selections with focus on the semiconductor and flat panel industry. It addresses data availability and data quality issues in environmental evaluations through the uncertainty analysis. It tackles the mismatch between the short innovation cycles in the industry and the long environmental analysis time by a combination of the uncertainty analysis, non-linear sensitivity analysis, hierarchical modeling, and the value of information analysis. It bridges the gap between environmental evaluations, economical evaluations, and technical evaluations by a unified modeling platform that links the process model, the cost-of-ownership model, and the environmental valuation model along with the databases and the random number generators for the uncertainty analysis. It is a generic framework and can be applied to various decision scenarios that face uncertainty in their systems. The paper also reviews sensitivity analysis methods and includes a survey on the current status and needs on environmental, safety, and health in the industry.
(cont.) A case study on Cu CVD illustrates the methods of the evaluations models. A case study on comparing NF₃ and F₂ as the chamber cleaning gas illustrates the decision-making framework.
by Yue Chen.
Ph.D.
157 p.
10634090 bytes
10642703 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Chemical Engineering.
Integrating environmental considerations in technology selections under uncertainty
Thesis
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<Abstract>Competition requires companies to make decisions that satisfy multiple criteria. Considering profitability alone is no longer sufficient. Ignoring environmental considerations will not only expose a company to potential regulatory costs, but also damaged public image, both of which in turn have negative effect on the economic well- being of companies. At the same time, the fast changing business environment requires companies to reach decisions in a speedy fashion. This work describes a decision- making framework that addresses the obstacles in integrating environmental considerations into technology selections with focus on the semiconductor and flat panel industry. It addresses data availability and data quality issues in environmental evaluations through the uncertainty analysis. It tackles the mismatch between the short innovation cycles in the industry and the long environmental analysis time by a combination of the uncertainty analysis, non-linear sensitivity analysis, hierarchical modeling, and the value of information analysis. It bridges the gap between environmental evaluations, economical evaluations, and technical evaluations by a unified modeling platform that links the process model, the cost-of-ownership model, and the environmental valuation model along with the databases and the random number generators for the uncertainty analysis. It is a generic framework and can be applied to various decision scenarios that face uncertainty in their systems. The paper also reviews sensitivity analysis methods and includes a survey on the current status and needs on environmental, safety, and health in the industry.</Abstract>
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