Manufacturing companies are striving to remain competitive in the market and maintain their economic growth and productivity. Uncertainties regarding the changes in product demand, workpiece material, product design, and technological advancement, have imposed pressure on manufacturing systems. Market uncertainties force manufacturing companies to be flexible and responsive in producing different parts, by adapting the existing system without the need for a substantial investment. The market is characterized by time variations in product quantities and varieties while manufacturing systems remain inherently fixed. To sustain competitive manufacturing, a company has to adopt to new production requirements and be responsive to market changes quickly. Conscious decisions have to be made for a system to respond to market fluctuations. In order to respond to the dynamic changes, there is a need for developing methodologies that analyse, evaluate and control performance of manufacturing system at the system and/or process levels.

The primary focus of the thesis is to develop a novel generic framework for modelling and controlling manufacturing systems intending for improvement of the performance of manufacturing and make companies more competitive. The framework incorporates the complex interrelations between the process and system parameters, i.e., the dynamics of the system. Thus, provides a quantitative and qualitative analysis for performance evaluation and for optimizing performance of manufacturing system. The generic framework can further be adapted for studying specific manufacturing systems in discrete manufacturing. Three case studies are presented. The case studies are performed in an automotive company where the effect of various levels of control is investigated in manufacturing systems configured as transfer line or as a flexible manufacturing system.

Two aspects of the dynamic nature of manufacturing system are investigated in this thesis: (1) The engineering nature of the system, i.e., the selection of appropriate process parameters to manufacture a product according to the design specification, and (2) The business nature of the system, i.e., the selection of system parameters with respect to the way the product is manufactured. At the process level, the parameters are controlled within the process capability limits to adapt to the changes of the system parameters in response to the market dynamics. At the system level, operational parameters are controlled to satisfy performance criteria.

A case study for resource use analysis during primary processes has also been investigated and presented. The critical operations and the operations that have the highest energy consumptions and the potential for energy savings have been identified.

The methodology developed for analysing the performance of the dynamic manufacturing system is based on a system dynamics modelling approach. Results obtained from different modelling approaches are presented and compared based on the selected performance metrics.