Cellular Manufacturing Systems (CMS) have provided
significant increase in manufacturing productivity over the
last two decades. This has been achieved because CMS can
overcome the problems due to frequent setups, high in-process
inventories, long throughput times and complex
planning and coordination commonly associated with a batch-type
manufacturing operation. The underlying concept of CMS
is the grouping of parts into part families and the machines
that process these parts into machine cells in order to
achieve manufacturing efficiencies.
Creating machine cells which can perform all operations
of a part without requiring the part to visit one or more
cells other than its own is hard to achieve, if not
impossible. Hence, in the design of CMS, one tries to
minimize the material handling costs incurred due to the
movements of parts to other cells. Duplication of
"bottleneck" machines that process parts assigned to other
cells into the appropriate cells and subcontracting of
"bottleneck" parts that require one or more operation on
machines assigned to another cell are two important methods
utilized to form disaggregated manufacturing cells in order
to minimize the material handling costs.
A mathematical model and a solution algorithm is
developed to simultaneously deal with the issues of
duplicating bottleneck machines and subcontracting
bottleneck parts. Because there is a cost associated with
the process of duplication and subcontracting, the benefits
attained are analyzed for different budgetary constraints
encountered by a firm.
The algorithm was tested on three different problem
structures for a range of budgetary restrictions. The
results obtained show that the algorithm could be used by
the industry to solve problems encountered in the design of
CMS. / Graduation date: 1994
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/35761 |
| Date | 01 April 1994 |
| Creators | Ramakrishna, Prabha |
| Contributors | Logendran, Rasaratnam |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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