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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Siravat Teerasoponpong | en_US |
dc.contributor.author | Apichat Sopadang | en_US |
dc.date.accessioned | 2018-09-05T02:58:38Z | - |
dc.date.available | 2018-09-05T02:58:38Z | - |
dc.date.issued | 2016-01-01 | en_US |
dc.identifier.issn | 18684238 | en_US |
dc.identifier.other | 2-s2.0-84964908540 | en_US |
dc.identifier.other | 10.1007/978-3-319-33111-9_7 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964908540&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/55616 | - |
dc.description.abstract | © IFIP International Federation for Information Processing 2016. The management of the supply chain in presence of uncertainty is a challenge task. This paper proposes a stochastic model for modeling both the structure and the operation of the supply chain. Existing approaches for this task are either deterministic or single level structure which might not be appropriate to capture the essences of the supply chain. The proposed method employs the Markov chain model as the foundation and incorporate the concept of multi-level. The levels are used to model both the internal events and the external events. In the proposed method, the product life cycle management is used as a guiding principle to identify each component of the supply chain. | en_US |
dc.subject | Decision Sciences | en_US |
dc.title | Risk probability assessment model based on PLM’s perspective using modified markov process | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | IFIP Advances in Information and Communication Technology | en_US |
article.volume | 467 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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