|dc.contributor.author||Omar, Rayan Saleem M||
|dc.description.abstract||The clearing function (CF) models the non-linear relationship between work-in-process
(WIP) and throughput and has been proposed for production planning in environments
with queuing (congestion) effects. However, incorporating the CF concept
in multi-product multi-stage manufacturing networks is still a challenging problem.
One approach proposed in literature is to model the CF at the bottleneck machines
only. However, since the bottleneck may shift as the product mix changes and the
queuing network effect is difficult to capture at the bottleneck, this approach has its
The dominant method in the literature to modelling congestion in multi-product
multi-stage networks is the allocated clearing function (ACF) approach. In this approach,
the CF is developed at the resource level using a numerical estimation method
such as discrete-event simulation. Based on these estimates, the CF is fit using piecewise
linear equations. The ACF linear program (LP) then partitions the CF for
resource product combinations.
This thesis proposes an alternative methodology to ACF, where the release and
WIP levels in each period are discrete (FPR). The CF is estimated at discrete load
combinations using simulation, mean-value analysis (MVA), or queuing network analysis.
A mixed-integer programming (MIP) formulation is developed to determine optimal
material release. The approach is data-driven and does not require the use of a
curve-fitting function. The CF estimates at the discrete lattice points in this approach
are network based, as opposed to resource based as in ACF. The MIP behaviour is
illustrated using the MVA approximation for a well-known multi-product re-entrant
semiconductor manufacturing case in the literature.
The FPR-MIP formulation is extended to allow release quantities between the
lattice points using a cubic approximation technique (CA). This approach allows the
MIP to potentially obtain better solutions in continuous space and can be seen as
a generalization of piecewise linearization for the single product case. A detailed
comparison between FPR and CA is discussed using an example case.
Finally, FPR and CA are compared and contrasted with the ACF approach.
In summary, this thesis presents an alternative approach to the state-of-art in the
modelling of congestion in manufacturing networks.||en_US
|dc.title||MANUFACTURING PLANNING AND SHOP FLOOR CONGESTION ANALYSIS IN MULTI-PRODUCT NETWORKS USING A DATA-DRIVEN APPROACH||en_US
|dc.contributor.department||Department of Industrial Engineering||en_US
|dc.contributor.degree||Doctor of Philosophy||en_US
|dc.contributor.external-examiner||Dr. Reha Uzsoy||en_US
|dc.contributor.graduate-coordinator||Dr. Corinne MacDonald||en_US
|dc.contributor.thesis-reader||Dr. Pemberton Cyrus||en_US
|dc.contributor.thesis-reader||Dr. William Phillips||en_US
|dc.contributor.thesis-reader||Dr. Claver Diallo||en_US
|dc.contributor.thesis-supervisor||Dr. Uday Venkatadri||en_US