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integrated approach to intermediate planning of manufacturing operations with sequence dependent setups
This research is concerned with the development of an
iv intermediate planning problem in the presence of sequence
dependent setups. The object' e of intermediate planning is
the generation of periodic production quotas to drive actual
shop floor production to meet the production requirements.
This planning approach is unique in that it accounts for
capacity losses due to time spent in sequence dependent
changeovers, when a number of products are produced in a
facility. A planning model is developed for a flow line
manufacturing system, where products are manufactured in a
fixed sequence over multiple stages. The objective of this
model is to minimize the sum of completion times over all
manufacturing stages. The completion constraints in the
planning model are expressed in terms of sequence dependent
setup, production, transfer and resource starvation times.
As a result of this representation, the developed model
consists of both continuous planning and binary sequencing
variables. Obtaining the optimal solution for the developed
model is very difficult even for moderate sized instances of
the problem. Due to sequence dependent setups, the capacity
losses depend on the production sequence which is not known
at the time of planning. However, determination of the
production sequence requires advance knowledge of the
production quantities in a planning period. This cyclic
dependency between the planning and scheduling variables is
exploited in developing an iterative search-based procedure
to efficiently provide good solutions to this problem. The
search procedure is based on simulated annealing. The
simulated annealing procedure employs a dynamic cooling
schedule where the search parameters are adjusted
automatically depending on the problem instance.
Computational results indicate that the method performs well
on a number of test problems of different 'sizes. By
developing a model that accurately captures capacity losses
due to sequence dependent setups and directly represents the
minimization of completion times as a planning objective, the
search based approach yields plans of high quality that
respect actual available capacity and inventory restrictions.
"Major Subject: Industrial Engineering".
Issued also on microfiche from University Microfilms Inc.
Includes bibliographical references: pages 85-89.