Capacity planning under fuzzy environment

dc.contributor.authorVerma, Manoj Kumaren_US
dc.date.accessioned2007-05-22T15:13:37Z
dc.date.available2007-05-22T15:13:37Z
dc.date.issued2001-04-01T00:00:00Zen_US
dc.degree.disciplineMechanical and Manufacturing Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractIn recent years, in manufacturing industry, their has been a great deal of interest in capacity planning because the focus is shifting on techniques that determine flexibility of the amount and timing of work center capacity to satisfy the master production schedule. There are several techniques available for preparing work center capacity plans under crisp environment, but there is a scarcity of technique available for finding the required capacity in terms of labor hours under fuzzy environment. In the present thesis, we analyze the Bill of Labor (BOL), Resource Profile (RP) and Capacity Requirements Planning (CRP) approaches under fuzzy environment with a variety of assumptions. Chapter 1 provides an introduction to the concepts of capacity planning problems considered in the thesis, followed by the literature survey in Chapter 2. The capacity analysis under fuzzy envi onment using BOL approach for rough cut capacity planning (RCCP) is considered in Chapter 3. Assuming that all the components of an item are manufactured in the same time period as the end item, i.e. lead-time offsets are considered to zero. Chapter 4 deals with the capacity analysis under fuzzy environment using RP approach for RCCP by including the lead-time dimension in it. Chapter 5 deals with the capacity requirements planning under fuzzy environment. Finally, conclusion, contribution and recommendations for further research on the aforementioned problems are presented in Chapter 6.en_US
dc.format.extent6536361 bytes
dc.format.extent184 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.identifier.urihttp://hdl.handle.net/1993/2026
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.titleCapacity planning under fuzzy environmenten_US
dc.typemaster thesisen_US
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