Advancements in information technology enabled to track real time data in a more accurate and precise way in many manufacturing facilities. However, before obtaining the more accurate and precise data, the investment in information technology should be validated. Value of information may be adopted as a criterion in this investment. In this study, we analyze the value of information in a manufacturing facility where production and lead time quotation decisions are taken. In order to assess the value of information, two settings are analyzed. Under the first setting, the manufacturer takes decisions under perfect information. To find the optimal decisions under perfect information, a stochastic model is introduced. Under the second setting, the manufacturer takes decisions under imperfect information. To obtain a solution for this problem, Partially Observable Markov Decision Process is employed. Under the second setting, we study two approaches. In the first approach, we introduce a nonlinear programming model to find the optimal decisions. In the second approach, a heuristic approach, constructed on optimal actions taken under perfect information is presented. We examine the value of information under different parameters by considering the policies under nonlinear programming model and heuristic approach. The profit gap between the two policies is investigated. The effect of Make-to-Order (MTO) and Make-to-Stock (MTS) schemes on the value of information is analyzed. Lastly, different lead time quotation schemes / accept-all, accept-reject and precise lead time / are compared to find under which quotation scheme value of information is highest.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613225/index.pdf |
Date | 01 June 2011 |
Creators | Kaman, Cumhur |
Contributors | Savasaneril, Secil |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | M.S. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
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