published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

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

Logistics plays a more and more important role in manufacturing company to sharp competitive in today’s supply chain integration. As the end of logistics in manufacturer, container loading intellectualization has attracted more and more focuses. Harmonious coordination between planning and execution ground high performance of the container loading. Several challenges exist in business operations. Firstly, container loading planning is time-consuming. Several case-based constraints exist in the optimization defined by different customers and the Customs. Secondly, execution driven by container loading is inefficient. Operators may use unclear or unreadable paper-based guidance during execution which is inconvenient to handle. Besides, due to various situations, shipping documentations are complex. Afterwards Order-picking, a critical part in executions, is a costly activity. Thirdly, coordination during whole container loading process is another challenge. Information sharing between planning and execution is delayed and inaccurate. The whole procedure usually cannot be monitored by managers in a remote office. Problems cannot be addressed without timely provision of data. This research targets to establish a smart container loading platform based on real life practices and constraints. Unlike common warehouse operation, warehouse executions are driven by container loading. To overcome the challenges, an integrated solution is proposed with three main parts. The first one is to establish RFID-enabled real-time smart environment where device-level data is collected timely with bidirectional communications under Wi-Fi occasionally connected situation. Secondly, Service-oriented Architecture (SOA) is applied in rule-based computation and heterogeneous information sources integration. In rule-based computation, constraint is computed and wrapped as rule. It is a kind of service which is restored in service repository according to its properties. Under different cases, several rules are addressed and invoked in a specified sequence to realize different business logics. And the platform should communicate with heterogeneous sources within short time. Systems wrap application programming interfaces (API) as web services which can be invoked flexibly at any time. Data fetch process is divided into several threads which extract data concurrently. Thirdly, container loading optimal model is provided based on practical constraints. Based on various rules, shipments are clustered as groups before loading. To load containers more equally, heuristic algorithm is provided with reducing container capacity continuously until other constraints are violated or more shipment groups are separated. Four contributions have been made in this study. Firstly, a five-layer system architecture is proposed for small and medium enterprises (SMEs) applications especially in occasionally connected network environment, rule-based computations, and efficient data exchanges. Secondly, several practical constraints of loading planning are addressed and a heuristic algorithm is designed. Shipments can be equally loaded while satisfying most conflicted constraints. Thirdly, a solution for auto-ID enabled warehouse execution is provided. The solution is driven by container loading equipped with real-time information capturing and processing. Fourthly, a guidance can be refereed for real life implementations in SME. The guidance summarizes system customization procedures with reengineered resources. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

To survive and thrive in the customer-oriented global market, retail companies have to make persistent efforts to provide customers with satisfactory shopping experience enriched by leisure process, interaction for merchandise information and personalised assistance. In traditional retail stores, customers’ needs cannot be fully satisfied due to difficulties in locating target products, out-of-stocks, a lack of professional assistance for product selection, and long waiting for payments. The relative visibility and traceability of individual items provided by the radio frequency identification (RFID) technology is helpful for enhancement of customer shopping experience (CSE). However, current RFID applications for retail business tend to be limited to inventory control and replenishment, with few implementations for CSE enhancement based on collection and analysis of real-time RFID data. To mitigate these limitations, this research project develops RFID applications for real-time collection and analysis of customer shopping behaviour (CSB) data in retail stores. Artificial intelligence (AI) is incorporated for data analysis to facilitate business decision-making and proactive individual marketing. Accordingly, an item-level RFID-based customer shopping experience enhancement (IRCSEE) system is developed to provide customers with leisure shopping process, interaction for merchandise information and personalised guidance for enhancement of CSE in apparel retail stores. The IRCSEE system incorporates RFID hardware devices installed in an apparel retail store to interrogate RFID-tagged apparel items to obtain data for subsequent sales processing and analysis. It is characterised with a programmable data format for unique identification of individual apparel items, together with a suite of software modules to control the RFID hardware devices at different locations of the apparel retail store for real-time collection of product information and CSB data. Moreover, an innovative fuzzy screening (FS) algorithm of AI techniques is developed to analyse the RFID-collected CSB data and the corresponding product information for generation of apparel collocation recommendations to provide customers with intelligent and personalised assistances in product selection. The algorithm considers not only the static fashion expertise, but also the dynamic customer preferences for collocation, such that the recommendations are more effective and adaptive for enhancement of CSE in the fast-changing apparel retail industry. The IRCSEE system is validated in an emulated RFID-based apparel retail store. Experimental results demonstrate that with appropriate RFID hardware settings, the proposed system is effective to help enhance CSE in apparel retail stores by providing customers with leisure shopping process, interaction for merchandise information and personalised apparel collocations. Furthermore, the approaches for collecting real-time CSB by RFID technology and analysing such data by AI techniques can be conveniently adapted for many other products to improve retail business management in general. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

Thesis (MTech. degree in Computer Systems) -- Tshwane University of Technology, 2010. / Radio Frequency Identification (RFID) systems are becoming more popular today, especially in first world countries. This is a result of the systems wide range of applications. RFID technology is used in several industries, such as: transport, sport, medicine and government institutions. The advantages that the technology offers promote its widespread use and implementation in various industries. RFID systems have the capacity to store more information than other identification technologies (for example barcode technology). Data can be read with ease as it does not require line of sight and human intervention. Despite several implementations in many industries, RFID still has some disadvantages, for instance implementation cost and issues of security and privacy. The focus of this study is the security and privacy issues in the RFID environment.

Manual cattle handling systems are widely used in South Africa. A literature review and consultations were conducted with both producers and equipment manufactures, to assess the advantages and disadvantages of various cattle handling systems with the objective of developing a more efficient system that incorporates automation, electronics and Radio Frequency Identification (RFID) technology. In this study an automated, selective sorting (RFID) based cattle handling system was developed and assessed as an alternative to the widely adopted conventional manual management system practiced in South Africa. The system is still under research and not yet available on the market. This document describes the research and development process undertaken which included planning, literature review, consultation, design, fabrication, evaluation and discussions. The RFID based system developed consists of manual, semi- and fully automated components in the form of a neck-body clamp with through access, flow control double split gates and a weigh-identification-sort system. For the ease of comparison the system was developed with a manual by-pass as a control to compare the automated and manual systems in terms of establishment cost, handling duration including identification, weighing and sorting, and operator and animal stress levels which impact on business profitability and system efficiency. Both the manual by-pass and automated RFID-based systems were evaluated. The automated system resulted in reduced handling duration, operational costs and handling stress on both operator and the animal whilst enabling selective automated sorting. The infrastructure was designed to have a capacity to handle 500 animals per day with 5 handlers and a capital investment of R200 000 was required with an operational cost of R25 000 per month. After incorporating RFID, electronics and automation of the system it was established that, on average, cattle handling duration was reduced by 63%, incorrect sorting was reduced by 5.5%, man hours were reduced by 70% with 23% and 14% less fatigue and stress levels to the handler and the animals respectively, whilst achieving efficient selective sorting. A cost benefit analysis was undertaken for both systems with the aim of assessing and determining the most profitable system. An assumption was made that the cash flow pattern remains uniform for both systems over the entire evaluation period. This revealed that the introduction of RFID based technology as an alternative to a manual based system results in an increase in business profitability by 20% and shorten the payback period by 5 years. Although there is still need to further investigate the performance parameters under different environments, it can be concluded that the introduction of RFID, electronics and automation improves the overall system technical efficiency by 32% whilst enabling efficient selective handling. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2013.

No description available.

Thesis (M. Phil.)--University of Hong Kong, 2008. / Also available in print.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2008. / Includes bibliographical references. Also available in electronic version.