Type of Document Dissertation Author Fong, Nga Hin Benjamin Author's Email Address email@example.com URN etd-04252005-122011 Title Modeling, Analysis,and Design of Responsive Manufacturing Systems Using Classical Control Theory Degree PhD Department Industrial and Systems Engineering Advisory Committee
Advisor Name Title Shewchuk, John P. Committee Co-Chair Sturges, Robert H. Committee Co-Chair Chen, Fengshan Frank Committee Member Poon, Ting-Chung Committee Member Robertshaw, Harry H. Committee Member Keywords
- System Responsiveness
- Classical Control Theory
- Responsive Manufacturing Systems
Date of Defense 2005-04-15 Availability unrestricted AbstractThe manufacturing systems operating within today’s global enterprises are invariably dynamic and complicated. Lean manufacturing works well where demand is relatively stable and predictable where product diversity is low. However, we need a much higher agility where customer demand is volatile with high product variety. Frequent changes of product designs need quicker response times in ramp-up to volume. To stay competitive in this 21st century global industrialization, companies must posses a new operation design strategy for responsive manufacturing systems that react to unpredictable market changes as well as to launch new products in a cost-effective and efficient way.
The objective of this research is to develop an alternative method to model, analyze, and design responsive manufacturing systems using classical control theory. This new approach permits industrial engineers to study and better predict the transient behavior of responsive manufacturing systems in terms of production lead time, WIP overshoot, system responsiveness, and lean finished inventory. We provide a one-to-one correspondence to translate manufacturing terminologies from the System Dynamics (SD) models into the block diagram representation and transfer functions. We can analytically determine the transient characteristics of responsive manufacturing systems. This analytical formulation is not offered in discrete event simulation or system dynamics approach. We further introduce the Root Locus design technique that investigates the sensitivity of the closed-loop poles location as they relate to the manufacturing world on a complex s-plane. This subsequent complex plane analysis offers new management strategies to better predict and control the dynamic responses of responsive manufacturing systems in terms of inventory build-up (i.e., leanness) and lead time. We define classical control theory terms and interpret their meanings according to the closed-loop poles locations to assist production management in utilizing the Root Locus design tool. Again, by applying this completely graphic view approach, we give a new design approach that determine the responsive manufacturing parametric set of values without iterative trial-and-error simulation replications as found in discrete event simulation or system dynamics approach.
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