Thesis (M.S.)--Air Force Institute of Technology, 2002. / Title from title screen (viewed Oct. 28, 2003). Vita. "AFIT/GOR/ENS/02-01." Includes bibliographical references (leaves 84-86). Also issued in paper format.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 146-154). Also available in electronic version. Access restricted to campus users.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 57-59).

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 56-58).

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 135-138). Also available in electronic version. Access restricted to campus users.

This dissertation focuses on service scheduling and transshipment problems. The study of service scheduling is motivated by decisions facing service planners, who must inspect and maintain geographically dispersed infrastructure facilities. We study the problem of deciding which operations a service unit must perform at each customer location, given the sequence in which the unit periodically visits these locations. Each customer requires multiple service operations, and each operation has a time-varying completion or penalty cost that depends on the previous service time. The goal is to schedule the service start time for each customer and select the operations to perform so as to minimize the total completion cost. We first discuss how to solve a special case of this problem in which each site is visited only once per service cycle. We formulate this problem as a discrete time indexed network flow problem and prove that it is NP-hard in the ordinary sense. Then, we represent the problem as a multidimensional shortest path problem with path-dependent arc lengths. In this structure, arc costs depend on the total time spent for all customers. The resulting formulation is solvable via algorithms that have pseudo-polynomial run times. Computational results show that the shortest path approach outperformed the general network flow model. We then analyze the general case of this problem, in which each site can be visited more than once and prove that the problem is NP-Hard in the strong sense. We discuss the valid cuts and describe the preprocessor that reduces the problem size. Next, we examine an application to the general case of the problem and develop a fast and effective heuristic procedure that repeatedly applies the shortest path approach to subsequences that do not visit any customer more than once. Computational results for several problem instances show that the proposed heuristic identifies near optimal results very quickly, whereas a general purpose integer-programming solver (CPLEX) is not able to find an optimal solution even after many hours of computational time. Then we focus on techniques such as problem reduction, branching variables, and subdividing problem to smaller problems to get better solution times for the actual problem. Computational results show that these techniques can improve solution times substantially. Finally, we study a transshipment problem, in which the shipments need to be transported from their origin to destination and are subject to the logical and physical transportation network on which they rely. We consider a space-time network that allows one to formulate the problem as a multi-commodity network flow problem with additional side constraints and show the complexity results. We propose alternative models and propose algorithms for lower and upper bound calculations. / text

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

This research deals with production scheduling of manufacturing systems that predominantly consist of hybrid flowshops. Hybrid Flowshop Scheduling (HFS) problems are common in metal working industries. Their solution has significant inferences on company performance in a globally competitive market in terms of production cycle time, delivery dates, warehouse and work-in-process inventory management. HFS problems have attracted considerable research efforts on examining their scientific complexity and practical solution algorithms. In conventional HFS systems, an individual job goes through the flowshop with its own processing route, which has no influence on other jobs. However, in many metal working HFS systems, jobs have interdependent relationships during the process. This thesis focuses on addressing two classes of HFS problems with job interdependence that have been motivated by real-life industrial problems observed from our collaborating companies. The first class of HFS problems with job interdependence are faced by manufacturers of typically standard metal components where jobs are organized in families according to their machine settings and tools. Family setup times arise when a machine shifts from processing one job family to another. This problem is compounded by the challenges that the formation of job families is different in different stages and only a limited number of jobs can be processed within one setup. This class of problems is defined as HFS with family setup and inconsistent family formation. The second class of HFS problems with job interdependence is typically faced in a production process consisting of divergent operations where a single input item is converted into multiple output items. Two important challenges have been investigated. One is that one product can be produced following different process routes. The other is that the total inventory capacity is very limited in the company in the sense that the inventory spaces are commonly shared by raw materials, work-in-process items and finished products. This class of problems is defined as HFS with divergent production and common inventory. The aim is to analyze the general characteristics of HFS with job interdependence and develop effective and practical methodologies that can tackle real-world constraints and reduce the scheduling effort in daily production. This research has made the following contributions: (1) A V-A-X structural classification has been proposed to represent the divergent (V), convergent (A) and mixed (X) job interdependent relations during the production. (2) A genetic algorithm based approach and a particle swarm optimization based approach have been developed to solve two classes of HFS problems with job interdependence, respectively. The computational results based on actual production data have shown that the proposed solutions are robust, efficient and advantageous for solving the practical problems. (3) A waiting factor approach and delay timetable approach have been developed to extend the solutions space of two classes of HFS problems by inserting intentional idle times into original schedules. The computational results have indicated that better schedules can be obtained in the extended solution spaces. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

 This research is concerned with the transformation Mould and Die (MD) manufacturing industry from the traditional manufacturing paradigm into service-oriented manufacturing (SOM) in collaboration with leading manufacturers in the sector. It investigates how the new concept of Production Service System (PnSS) can be used and extended to integrate distributed manufacturing-oriented services (MOSs) so that all participants could efficiently and effectively collaborate in response to market opportunities. In the PnSS model, MD manufacturers become more specialized in providing certain types of MD products and components while outsourcing other components or related services as MOSs from MOS providers (MOSPs). The main objective of this research is to develop an information and collaboration platform for PnSS (iPnSS) to utilize MOSs and support the implementation of PnSS strategy for MD industry. The proposed iPnSS is developed based on the SOA (Service-oriented Architecture) paradigm, which aims to encapsulate MOSs as Software as a Service so that MOSs can be advertised, searched, and utilized by stakeholders in PnSS. Several core MOSs have been developed as the core components of iPnSS to meet the urgent requirements of participants in new business model, including Ontology-based Dynamic Alliance Service (ODAS) for forming PnSS alliance, Real-time Order Progress Kanban Service (RT-OPKS) for collaborative project tracking and coordinating, and Hybrid Flow Shop Assembly Scheduling Service (HFS-ASS) for production planning and scheduling which is specified for MD production. The research makes several key contributions. First, this research investigates the characteristics and challenges of MD industry, and develops the PnSS business model to transform the traditional manufacturing into service-oriented manufacturing for MD industry. An information and collaboration platform called iPnSS is developed to provide related IT solutions for integrating distributed MOSs to facilitate the practical usage of PnSS. Second, Ontology-based Dynamic Alliance Service is developed to enable participants to form alliance and take advantage of SOM. This service provides a systematic and integrated supplier selection approach in PnSS, being responsible for the major stages in the life cycle of a service-enabled manufacturing process, including service provision and consumption as well as service evaluation and organization respectively. Third, Real-time Order Progress Kanban Service with the support of Radio Frequency Identification (RFID) technology is developed to support the efficient knowledge feedback for shop floor visibility and traceability. This service provides a set of mechanisms to monitor, evaluate and coordinate the manufacturing execution during the process of collaborative manufacturing after the formation of alliance. Finally, Hybrid Flow Shop Assembly Scheduling Service is developed to deal with scheduling problem for manufacturing one-of-a-kind products, which is based on real-life study with MD industrial collaborators. For each order in MD manufacturing is assembled after the required components have been produced, the service firstly considers the production simultaneity of components of the same product for final assembly. The service automatically generates scheduling results for PnSS user. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy