Thesis (M.B.A.)--Boston University / This thesis deals with manufacturing costs in the electronics industry. More accurately, it deals with all costs - including engineering, purchasing and distribution, as well as the costs of labor, material and occupancy charges. They are all interrelated. It is impossible to properly consider costs without looking at the total picture. Further, since it examines costs in the electronics industry, the weight of importance of our set of cost factors is considerably different from those applying to another industry.

Thesis (M.B.A.)--Boston University

<p>The objective of this thesis is to investigate the influence of thermal cycling on tool life in intermittent cuting processes. Particular emphasis is given to the peripheral milling process. In intermittent cutting processes, it has been established that the thermal cycling is the most significant factor which controls the type of failure and the life of cutting tools. The previous theoretical studies of the thermal cycling were based on strongly simplified models. The experimental studies were based on the measurement of the tool/chip interface temperature in the cutting period. Consequently, any implications for tool wear or breakage could only be indirectly estimated. In this work, the thermal cycling is studied by means of finite element computation of the transient temperatures and stresses in the tool wedge. The finite element formulation of the energy equations and the associated boundary conditions, which govern the heat transfer mechanism, is developed for the intermittent cutting processes. A two-dimensional tool/chip model is developed which reflects the interaction between the heat sources, and provides the capability of computing a complete temperature field. The computed temperature field is then used to determine the thermal stresses. The computation of a complete temperature field and the associated thermal stresses is necessary to explain experimentally determined characteristics of tool wear, cracking and breakage. The transient temperature field in both the chip and tool, and the corresponding thermal and mechanical stresses, are computed for the peripheral milling process with different cutting conditions. The theoretical results are correlated with experimental data. The experimental data are taken, mostly, from the tests of Barrow and Yellowley ⁽¹²⁾ and from similar tests conducted by the author. The experimental work concentrates on the flank wear of both high speed steel and sintered carbide milling cutter. It is found that the cutting time ratio has significant effect on tool life. The correlation shows that the number of thermal cycles is the most important parameter which affects the tool life in peripheral milling. The thesis starts with a statement of the problem and the scope of this work in Chapter 1. Chapter 2 provides a summary of the state of knowledge in the area of tool damage in intermittent cutting processes. The temperature problems in continuous and intermittent cutting process are discussed in Chapter 3. The mathematical modelling and the finite element formulation of the heat transfer problem are developed in Chapter 4. The modelling of the cutting process and the computation of the transient temperature distribution are presented in Chapter 5. Chapter 6 is devoted to the presentation and discussion of the computed thermal stresses. The important parameters which may affect the tool flank wear in milling are established and correlated to the experimental data in Chapter 7. Finally, Chapter 8 provides conclusions and recommendations for further research. Specifically, this thesis provides the following contributions: 1. The mathematical modelling and the finite element formulation of the transient heat transfer problem in intermittent cutting (Chapter 4). 2. Derivation of an automatic time step control algorithm for two-point recurrence schemes for the first order ordinary differential equations (Chapter 4). 3. Development of a two-dimensional tool/chip model for the cutting process (Chapter 5). 4. Implementation of a software system, based on he developed models, to compute the temperature and stress fields (Chapter 5 and 6). 5. The study of the influence of thermal cycling on tool flank wear in peripheral milling based on correlating the computed results with experimental data (Chapter 7).</p> / Doctor of Philosophy (PhD)

Thesis (M.S.)--Ohio University, March, 2006. / Title from PDF t.p. Includes bibliographical references (p. 87-89)

No description available.

In process industries, there is a great demand for additional process information such as the product quality level or the exact process state estimation. At the same time, there is a large amount of process data like temperatures, pressures, etc. measured and stored every moment. This data is mainly measured for process control and monitoring purposes but its potential reaches far beyond these applications. The task of soft sensors is the maximal exploitation of this potential by extracting and transforming the latent information from the data into more useful process knowledge. Theoretically, achieving this goal should be straightforward since the process data as well as the tools for soft sensor development in the form of computational learning methods, are both readily available. However, contrary to this evidence, there are still several obstacles which prevent soft sensors from broader application in the process industry. The identification of the sources of these obstacles and proposing a concept for dealing with them is the general purpose of this work. The proposed solution addressing the issues of current soft sensors is a conceptual architecture for the development of robust and adaptive soft sensing algorithms. The architecture reflects the results of two review studies that were conducted during this project. The first one focuses on the process industry aspects of soft sensor development and application. The main conclusions of this study are that soft sensor development is currently being done in a non-systematic, ad-hoc way which results in a large amount of manual work needed for their development and maintenance. It is also found that a large part of the issues can be related to the process data upon which the soft sensors are built. The second review study dealt with the same topic but this time it was biased towards the machine learning viewpoint. The review focused on the identification of machine learning tools, which support the goals of this work. The machine learning concepts which are considered are: (i) general regression techniques for building of soft sensors; (ii) ensemble methods; (iii) local learning; (iv) meta-learning; and (v) concept drift detection and handling. The proposed architecture arranges the above techniques into a three-level hierarchy, where the actual prediction-making models operate at the bottom level. Their predictions are flexibly merged by applying ensemble methods at the next higher level. Finally from the top level, the underlying algorithm is managed by means of metalearning methods. The architecture has a modular structure that allows new pre-processing, predictive or adaptation methods to be plugged in. Another important property of the architecture is that each of the levels can be equipped with adaptation mechanisms, which aim at prolonging the lifetime of the resulting soft sensors. The relevance of the architecture is demonstrated by means of a complex soft sensing algorithm, which can be seen as its instance. This algorithm provides mechanisms for autonomous selection of data preprocessing and predictive methods and their parameters. It also includes five different adaptation mechanisms, some of which can be applied on a sample-by-sample basis without any requirement to store the on-line data. Other, more complex ones are started only on-demand if the performance of the soft sensor drops below a defined level. The actual soft sensors are built by applying the soft sensing algorithm to three industrial data sets. The different application scenarios aim at the analysis of the fulfilment of the defined goals. It is shown that the soft sensors are able to follow changes in dynamic environment and keep a stable performance level by exploiting the implemented adaptation mechanisms. It is also demonstrated that, although the algorithm is rather complex, it can be applied to develop simple and transparent soft sensors. In another experiment, the soft sensors are built without any manual model selection or parameter tuning, which demonstrates the ability of the algorithm to reduce the effort required for soft sensor development. However, if desirable, the algorithm is at the same time very flexible and provides a number of parameters that can be manually optimised. Evidence of the ability of the algorithm to deploy soft sensors with minimal training data and as such to provide the possibility to save the time consuming and costly training data collection is also given in this work.

The work reported in this thesis is the culmination of a collaborative venture between Matra BAe Dynamics and the CIM Institute at Cranfield University. Initially the thesis examines the philosophy of the engineering doctorate, before describing the collaborating organisation's history and the background to the decision to formulate a structured process to aid information systems integration, including an appraisal of the perspective prior to the research. Following an extensive literature search of information systems and its integration, the findings from a survey of information systems in manufacturing organisations are described. These illustrate the need for a holistic modelling approach to aid information systems integration, the limitations of capital investment appraisal methods and the need to evaluate individual and multiple IS projects according to business objectives. The thesis then extends to the development of a process framework constituting three modules Audit, Assessment and Suggestion which provide a novel holistic approach to the problem of information systems integration. Following a review of modelling techniques, queuing models were selected to review the present engineering process through the creation of a theoretical model to benchmark performance of the information systems. Whilst linear goal programming models were utilised within the assessment module to optimise the multi-variable criteria involved in the selection of information system portfolios. The creation of financial scenarios based on corporate accounts and market limitations considered the implications of an information systems portfolio in conjunction with traditional investment appraisal methods to provide a comprehensive assessment of individual and multiple projects. The techniques used in this research were validated throughout and hence shown to exhibit criterion validity, whilst an industrial case study was undertaken to substantiate construct validity. Finally, recommendations for future work are presented and proposals for future developments outlined.

Thesis (M.B.A.)--Boston University

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 2003. / Includes bibliographical references.

M.Tech. Business Administration. Business School.