|dc.contributor.author||Koh, Siau Ching Lenny||
|dc.description.abstract||Over the last thirty years, Materials Requirements Planning (MRP) based systems
have become commonplace within batch manufacturing environments, but are still widely
held to be under performing. This research hypothesises that there may be inherent
problems associated with the application due to uncertainties that exist within dynamic
Research has highlighted both the absence of any business model that uses a
structured and systematic approach to deal with uncertainty holistically and the lack of any
widely used, consistent performance measures to allow comparison of research results. The
industrial need for such a holistic approach became apparent from survey work, which
showed MRP under-performed in the presence of uncertainty even when numerous
Buffering and Dampening (BAD) approaches were applied.
A business model of uncertainty that structures the causes and effects of uncertainty
as a hierarchy of four levels has been proposed, to be verified and validated through
industrial survey and simulation respectively.
The relationship between causes and effects in the business model has been verified
from survey results using Analysis of Variance (ANOVA), which identified twenty-three
significant uncertainties within Mixed-Mode (MM) operating environments. Using a multi-product,
multi-level dependent demand MRP simulation model within an MM operating
environment driven by planned order release, an experimental programme has been carried
out that showed finished products delivered late to be insensitive as a performance
measure. Parts Delivered Late (PDL) was found to be more sensitive and has been adopted
as the preferred measure. ANOVA on the simulation results validated the cause-and-effect
relationships, showing that the higher the level of uncertainty, the worse was delivery
Individual uncertainties produced effects that were not discretely recognised in the
literature. `Knock-on' effects are created by uncertainties delaying the issue of batches and
affected particular Bill of Materials chains. `Compound' effects are caused by uncertainties
affecting resource availability and also induced consequent knock-on effects.
Simulation results also showed that late deliveries from suppliers, machine
breakdowns, unexpected or urgent changes to schedules affecting machines and customer
design changes are the most significant uncertainties within the parameter levels modelled.
Several significant two-way and three-way interactions were found.
The business model of uncertainty represents a practical and pragmatic attempt to
act as a diagnostic tool to identify significant underlying causes affecting PDL for MM
companies using MR1, enabling more effective application of suitable BAD approaches.
Using the business model to drive a continuous improvement programme that
monitored both levels of uncertainty and PDL would allow internal and external
benchmarking for the efficacy of BAD approaches and for the reduction of uncertainties.||en_US
|dc.publisher||University of Hertfordshire||en_US
|dc.subject||Performance Computer integrated manufacturing systems, Management||en_US
|dc.title||Development of a business model for diagnosing uncertainty in MRP environments||en_US