The primary objective of this research is to investigate MRP under the
uncertainty demand and the change of lot size rules using three major time
series methods; Intervention analysis, transfer function and State Space
A significant part of the research work is devoted to the development
and implementation of a MRP simulation program which is used to measure
the MRP performance under various conditions. More than one hundred
simulation experiments were conducted and analyzed, twenty four
simulations were further investigated and illustrated using the time series
methods, they consisted of (i) five demand intervention analysis (ii) nine lot
size intervention analysis (iii) seven transfer functions (iv) three State Space
models. The simulations are analyzed through three important stages of
Identification, Estimation and Diagnostics.
It is found that the demand variation and lot size rules have significant
effects on the MRP performance. Their dynamic relationships can be
adequately represented using the time series models. The integrated
simulation and time series approach is more useful in the study of the
dynamic and transient behavior of MRP than the conventional steady state
analysis. It is anticipated that by slight modification of the simulation
program, similar studies can be performed on other major MRP policies.
Hence alternative MRP designs can be evaluated.
The time series methods have been successfully adapted to MRP
simulation and the models serve as an important aid to the MRP analyst. This
integrated modelling approach appears to be a powerful methodology for the
design and analysis of complex manufacturing systems. Furthermore, this
research suggests that the modelling approach may find application in other
aspects of manufacturing.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University