This research investigates a metallurgy manufacturer whose products are assembled on fixed position assembly islands. The products of collaborating company are characterized by large-scale with high complexity and mass customization. With such configuration, a product is always set on one location throughout its whole assembly cycle. Assembly materials, machines and operators can be continuity sent to one location to reduce damage or movement cost. To understand the production challenges of a real-life enterprise, this research investigates production procedures of the collaborating enterprise on planning, scheduling, logistics and assembly. The management challenges of assembly method with fixed-position layout are summarized as: (1) High dynamic of material, tools and operator movement. (2) The movement of operators, assembly machines maybe expensive. (3) The requirements of assembly operators are too high to find suitable operators with low cost. The cause of current production problems of the collaborating enterprise are summarized as: (1) lack of appropriate real-time operation data capturing and collection methods (2) current visibility and traceability functions at shop floor is wasteful, time consuming and inaccuracy (3) production data can hardly be synchronized between different production unites, e.g. assembly island buffers and stock areas. Hence RFID technology is applied to solve the problems. The creation of RFID-enable assembly environment is following the AUTOM RFID implementation solutions. The methodology of deployment RFID hardware facilities and the functions of choosing production object to tag RFID tags, finding value-adding points to deploy RFID readers and building networks to integrate the RFID hardware facilities are introduced. Decision support system is developed to connect and transfer information between shop-floor execution and decision. This system guides executions and collects real-time information involved in execution procedures and converts the information as reference for decision makers. This system can also release shop-floor decisions instantly to operators. Four core components including Explorers, Modules, Services and Data repository compose the framework. These four components interrelates to each other to guarantee the smooth shop-floor information transformation. Finally, a case study demonstrates the RFID solution has been successfully deployed in proof-of-concept shop floor of the collaborating enterprise. The decision support system can proper manage the captured real-time information and convert the information into useful reference data for decision makers. As the operation processes of this case is designed strictly following the real-life operation processes, therefore this RFID solution is capable to be applied in real-life shop floor to assist the enterprise operation and management. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

RFID (Radio Frequency Identification) technology has been widely used in manufacturing companies to support their production decision-makings such as planning and scheduling. Significant benefits have been obtained like real-time data collection, advanced production planning and scheduling (APS), as well as efficient material tracing & tracking. However, these companies are dazed when facing vast amount of RFID data, which could be further processed to obtain some invaluable knowledge for advanced decision-makings. This thesis proposes a holistic RFID-enabled solution for manufacturing companies which are facing typical challenges like paper-based data collection, inefficient planning and scheduling, ineffective work-in-progress (WIP) items visibility and traceability, as well as unsynchronized decision-making procedures. This solution includes several aspects. Firstly, RFID devices are systematically deployed in manufacturing sites (e.g. warehouse and shopfloors) to create an RFID-enabled ubiquitous production environment, where typical resources are converted into smart manufacturing objects (SMOs) which are able to sense and interact with each other. Thus, production logics could be carried out adaptively. Secondly, a real-time production planning and scheduling model is worked out for suiting the RFID-enabled ubiquitous manufacturing environment. This model uses several key concepts like hybrid flow shop scheduling (HFS), real-time job pool, and hierarchical decision-making principle to integrate production planning and scheduling level interactively. A real-time Kanban is proposed to coordinate these two levels. Thus, production decisions achieve a real-time fashion. Thirdly, in order to make full use of the RFID-captured real-time shopfloor production data, a data mining approach is introduced to excavate invaluable information and knowledge for APS decision-makings. Standard operation times (SOTs) and decision rules are mined for this purpose. Fourthly, an RFID-enabled real-time APS model is proposed for production decision-making. The resulting APS model is based on a hierarchical production decision-making principle to formulate planning and scheduling levels. An RFID-event driven mechanism is adopted to integrate these two levels for collaborative decision-making with the data mining approach. An RFID-enabled real-time advanced production planning and scheduling shell (RAPShell) is developed by using the concepts and models proposed in this thesis. Some cutting-edge technologies are implemented within RAPShell such as service-oriented architecture (SOA), Software as a Service (SaaS), and XML-based (re)configuration. A case study from a real-life automotive manufacturer is presented for demonstrating how RAPShell is able to facilitate the production activities and decision-making procedures. Benefits from quantitative and qualitative aspects in this case are summarized and discussed. Some innovative contributions are significant. Firstly, an affordable and systematic RFID deployment scheme is proposed to create an RFID-enabled ubiquitous manufacturing environment. Secondly, an entire data mining approach is worked out for discovering the invaluable information and knowledge from vast amount of RFID production data. Thirdly, an APS model using RFID-event driven and data mining technique is proposed to achieve ultimate APS within the ubiquitous manufacturing. Finally, insights and lessons learnt from this research and implementations are generated as managerial implications which could be referred by both academics and practitioners when contemplating the RFID-enabled solution. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

No description available.

This thesis addresses research towards the development of an intelligent design for assembly evaluation system (IDFAES) based on the design for assembly (DFA) principels. The research project aimed to enhance the capability of existing DFA methodologies in order to support activities such as redesign, design modification and assembly planning during the product development cycle. / Thesis (PhD)--University of South Australia, 2001.

Thesis (M.S.)--University of Texas at El Paso, 2007. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (Ph. D.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xi, 86 p. : ill. Includes abstract. Includes bibliographical references (p. 82-86).

Thesis (Ph.D.)--University of Adelaide, Dept. of Mechanical Engineering, 2001? / Bibliography: leaves 172-184.

Thesis (Ph. D.)--Universität Regensburg, 2008. / Includes vita. Includes bibliographical references (p. 237-245).

Thesis (M.S.)--Ohio University, June, 1997. / Title from PDF t.p.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.