Manufacturing system design decisions are costly and involve significant investment in terms of allocation of resources. These decisions are complex, due to uncertainties related to uncontrollable factors such as processing times and part demands. Designers often need to find a robust manufacturing system design that meets certain objectives under these uncertainties. Failure to find a robust design can lead to expensive consequences in terms of lost sales and high production costs. In order to find a robust design configuration, designers need accurate methods to model various uncertainties and efficient ways to search for feasible configurations. The dissertation work uses a multi-objective Genetic Algorithm (GA) and Petri net based modeling framework for a robust manufacturing system design. The Petri nets are coupled with Bayesian Model Averaging (BMA) to capture uncertainties associated with uncontrollable factors. BMA provides a unified framework to capture model, parameter and stochastic uncertainties associated with representation of various manufacturing activities. The BMA based approach overcomes limitations associated with uncertainty representation using classical methods presented in literature. Petri net based modeling is used to capture interactions among various subsystems, operation precedence and to identify bottleneck or conflicting situations. When coupled with Bayesian methods, Petri nets provide accurate assessment of manufacturing system dynamics and performance in presence of uncertainties. A multi-objective Genetic Algorithm (GA) is used to search manufacturing system designs, allowing designers to consider multiple objectives. The dissertation work provides algorithms for integrating Bayesian methods with Petri nets. Two manufacturing system design examples are presented to demonstrate the proposed approach. The results obtained using Bayesian methods are compared with classical methods and the effect of choosing different types of priors is evaluated. In summary, the dissertation provides a new, integrated Petri net based modeling framework coupled with BMA based approach for modeling and performance analysis of manufacturing system designs. The dissertation work allows designers to obtain accurate performance estimates of design configurations by considering model, parameter and stochastic uncertainties associated with representation of uncontrollable factors. Multi-objective GA coupled with Petri nets provide a flexible and time saving approach for searching and evaluating alternative manufacturing system designs.

Universiẗat, Diss.--Duisburg-Essen, 2005.

Thèse doctorat : Informatique : Rennes 1 : 2005. / Bibliogr. p. [129]-132.

Thèse doctorat : Traitement du signal et télécommunications : Rennes 1 : 2005. / Bibliogr. p. 175-178.

Thèse de doctorat : Mathématiques appliquées : Bordeaux 1 : 2008. / Titre provenant de l'écran-titre.

Reproduction de : Thèse de doctorat : Automatique et informatique industrielle : Villeneuve d'Ascq, Ecole centrale de Lille : 2006. / Titre provenant de la page de titre du document numérisé. Bibliogr. p. 143-153.

Thesis (M.Sc.)--Memorial University of Newfoundland, 2000. / Bibliography: p. 79-84.

The verification of analog designs has been a challenging task for a few years now. Several approaches have been taken to tackle the main problem related to the complexity that such task presents to design and verification teams. The methodology presented in this document is based on the experiences and research work carried out by the Concordia University's Hardware Verification and the U. of Texas' IC systems design groups. The representation of complex systems where different interactions either mechanical or electrical take place requires an intricate set of mathematical descriptions which greatly vary according to the system under test. As a simple and very relevant example one can look at the integration of RF-MEMS as active elements in System-On-Chip architectures. In order to tackle such heterogeneous interaction for a consistent model, the use of stochastic hybrid models is described and implemented for very simple examples using high level modeling tools for a succinct and precise description. / text

Reducing the complexity in information systems is a main concern on which researchers work. Separation of concerns, also known as the principle of ‘divide and conquer’, has long time been a strategy for dealing with complexity. Two examples of the application of this principle in the area of information system design are the break out the data management into Database Management Systems(DBMSs) and the separation of the business logic from the application logic into Business Process Management Systems (BPMSs). However, separation of cross-cutting concerns from the core-concern of a business process is not yet supported in the Business Process Management (BPM) area. Aspect Oriented principle recommends such a separation. When looking into the business process, several concerns, such as security and privacy, can be identified. Therefore, a formal model that provides a foundation for enabling BPMSs to support separation of concerns in BPM area is needed. This thesis provides a formal model for dealing with separation of concerns in the BPM area. Implementing this model in BPMSs would facilitate the design and implementation of business processes with a lower level of complexity, which in turn would reduce the costs associated with BPM projects. The thesis starts with a literature review on aspect orientation both in programming and in the BPM areas. Based on this study, a list of requirements for an Aspect Oriented Service for BPMSs is compiled. Then a formal model for such a service, fulfilling a set of these requirements, is designed using Coloured Petri Nets and implemented in CPN Tools. The model is evaluated through the execution of a number of scenarios. The solution is also validated through an industrial case study. The results of the case study are presented the direction for future work outlined. The case study demonstrates that separation of concerns through aspect orientation does indeed reduce the complexity of business process models.

published_or_final_version / Computer Science / Master / Master of Philosophy