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Strategies for reuse of components are important in order to create a closed loop manufacturing system. Over decades, the notion has been gaining ground due to environmental and legislative reasons. Reuse of components is desirable and in many cases might be economically beneficial. However, the implementation of reuse strategies has been hindered by the requirement of reliable methodologies to assess the remaining life and reuse potential of used components. The estimation of the remaining life is problematic as the useful life of a component is affected by several causes of obsolescence. The common causes are due to physical and technological issues. So far, little research has attempted to address these issues simultaneously, and integrating them. This thesis seeks to develop methodologies that aid in predicting the integrated remaining lifetime of used components. There are three core parts of this research. First, the methodology determines the remaining life of used components from the physical lifetime perspective. This was derived from the estimation of physical failure using failure rate data, and the statistical analysis of usage intensity age as obtained from customers survey. Second, the research presents the use of the technological forecasting technique to predict the remaining technological life. As it is influenced by the technology progress, the forecast was developed on the basis of product technology clusters and market trend extrapolation analysis. Finally, the resulting estimations from the two aspects were combined to obtain an integrated assessment for estimating the remaining life of components. The potential for components in a product to be reused is justified when the remaining life is greater than the average expected lifespan of the product. Two cases of domestic appliances – televisions and washing machines were used to highlight and demonstrate the validity of the proposed methodology. The results show that the proposed method provides the practitioners with a promising tool for end-of-life decision making. This is in particularly attractive when used as a preliminary decision support tool prior to the time consuming and costly processes such as disassembly and quality testing.

Strategies for reuse of components are important in order to create a closed loop manufacturing system. Over decades, the notion has been gaining ground due to environmental and legislative reasons. Reuse of components is desirable and in many cases might be economically beneficial. However, the implementation of reuse strategies has been hindered by the requirement of reliable methodologies to assess the remaining life and reuse potential of used components. The estimation of the remaining life is problematic as the useful life of a component is affected by several causes of obsolescence. The common causes are due to physical and technological issues. So far, little research has attempted to address these issues simultaneously, and integrating them. This thesis seeks to develop methodologies that aid in predicting the integrated remaining lifetime of used components. There are three core parts of this research. First, the methodology determines the remaining life of used components from the physical lifetime perspective. This was derived from the estimation of physical failure using failure rate data, and the statistical analysis of usage intensity age as obtained from customers survey. Second, the research presents the use of the technological forecasting technique to predict the remaining technological life. As it is influenced by the technology progress, the forecast was developed on the basis of product technology clusters and market trend extrapolation analysis. Finally, the resulting estimations from the two aspects were combined to obtain an integrated assessment for estimating the remaining life of components. The potential for components in a product to be reused is justified when the remaining life is greater than the average expected lifespan of the product. Two cases of domestic appliances – televisions and washing machines were used to highlight and demonstrate the validity of the proposed methodology. The results show that the proposed method provides the practitioners with a promising tool for end-of-life decision making. This is in particularly attractive when used as a preliminary decision support tool prior to the time consuming and costly processes such as disassembly and quality testing.

Programming has advanced a great deal since the appearance of the stored-program architecture. Through the successive generations of machine codes, assembly languages, high-level languages, and object-oriented languages, the drive has been toward program descriptions that express more meaning in a shorter space. This trend continues today with domain-specific languages. However, conventional languages rely on a textual formalism (commands, statements, lines of code) to capture the programmer's intent, which, regardless of its level of abstraction, imposes inevitable overheads. Before successful programming activities can take place, the syntax has to be mastered, names and keywords memorized, the library routines mastered, etc. Existing visual programming languages avoid some of these overheads, but do not release the programmer from the task of specifying the program logic, which consumes the main portion of programming time and also is the major source of difficult bugs. Our work aims to minimize the demands a formalism imposes on the programmer of geometric subroutines other than what is inherent in the problem itself. Our approach frees the programmer from syntactic constraints and generates logically correct programs automatically from program descriptions in the form of diagrams. To write a program, the programmer simply draws a few diagrams to depict the problem context and specifies all the necessary parameters through menu operations. Diagrams are succinct, easy to learn, and intuitive to use. They are much easier to modify than code, and they help the user visualize and analyze the problem, in addition to providing information to the computer. Furthermore, diagrams describe a situation rather than a task and thus are reusable for different tasks—in general, a single diagram can generate many programs. For these reasons, we have chosen diagrams as the main specification mechanism. In addition, we leverage the power of automatic inference to reason about diagrams and generic components—the building blocks of our programs—and discover the logic for assembling these components into correct programs. To facilitate inference, symbolic facts encode entities present in the diagrams, their spatial relationships, and the preconditions and effects of reusable components. We have developed a reference implementation and tested it on a number of real-world examples to demonstrate the feasibility and efficacy of our approach. / text

As Information Communication Technologies (ICTs) are growing, there have been ceaseless efforts to develop a National Health Information Infrastructure (NHII). One of the challenges in constructing a NHII is concerned with the management of Electronic Health Records (EHRs). In particular, exchanging EHRs is an important factor in establishing interoperability within a NHII, and the reusability of the functionality for exchanging EHRs is one of major solutions to construct an NHII. In this study, we obtain several component models, and conduct empirical studies to validate the component models in terms of component reusability. Using HL7 CDA (Health Level 7 Clinical Document Architecture) as an EHR standard, we implemented three prototypes of the EHR Exchanger based on JavaBeans, the exogenous connectors and the mediator connector respectively. As shown in the experiment results, the reuse approach using a mediator connector leads to better component reusability in terms of external dependency, total coupling between objects (CBO), additional lines of codes (LOC), and performance. Thus, we believe that the reuse approach using a mediator connector yields many benefits in terms of component reusability for the EHR Exchanger implementation.