1,721,089 research outputs found
A paradigm to maximise performance and profitability of engineering products in the presence of manufacturing uncertainty
No full textVariation in the manufactured geometry of engineering components is perpetually present in production. Random variation can arise due to slight differences in material properties, machines and tools, processes and even climatic conditions in the factory. To guarantee the functionality or quality of individual components, features are inspected to verify they conform to the tolerance limits imposed. It is undesirable to produce nonconforming features, due to the cost of reworking features or scrapping components. In practice, it is not always feasible to improve manufacturing capability (reduce variation), or design components to be less susceptible to variation; in such a situation the cost of non-conformance should be minimised. Optimal Mean Setting, a methodology to maximise profit from a production system where the manufacturing variation is often greater than a feature's tolerance limits, can be applied in these circumstances. Although the principle of Optimal Mean Setting dates back over 60 years, its application to engineering design is relatively undeveloped. A major part of this thesis was devoted to developing a robust, reliable and generalised framework to practice Optimal Mean Setting in engineering design. Errors were uncovered in previous attempts in the literature relating to Optimal Mean Setting of simple systems. Improvements to the maximum obtainable profit were also realised by implementing a new optimisation strategy to that developed in the literature. Another innovation developed in this thesis was the application of copula function modelling to Optimal Mean Setting. Copulas allowed joint distributions to be created from non-parametric (or non family specific) feature variation distributions. This permitted Optimal Mean Setting to be applied to components with several quality characteristics where different distributions modelled the manufacturing variation. It also allowed the final geometry of a component to be modelled to access the distribution of performance of a batch of components. Numerical examples and the applications to real components are given
Generalising optimal mean setting for any number and combination of serial and parallel manufacturing operations
No full textConsider a production system where products are continuously manufactured and their features inspected for conformance within specification limits. If features are produced above or below the specification limits, they are either subject to rework or the product scrapped. Optimal mean setting may be applied to adjust the manufacturing means to influence the amount of rework or scrap produced, maximising profit. Within the production system, manufacturing and then inspecting each feature in turn is termed serial production, whereas manufacturing multiple features before inspection is termed parallel production. This paper develops a generalised expression to optimise the mean values of each feature (optimal mean setting), where n number of features are produced in any combination of serial and parallel operations. Previous literature is restricted to considering two features in parallel. The production of multiple features in combinations of serial and parallel operations is not fully considered. The new generalised expression is validated by showing it is consistent with specific cases from past literature. The approach is then applied to a practical example of a gearbox shaft, considering the expected profit of eight possible manufacturing sequences, as well as the deviation of the manufactured means relative to the design intent. The generalised expression is widely applicable in component design and manufacturing planning where the process capability index (Cpk) of features is below one. The generalised expression also forms the basis for trade-offs between profitability and minimising deviations of manufactured means, which is the subject of further development
Improving profitability of optimal mean setting with multiple feature means for dual quality characteristics
Full text linkThe setting of a process mean for a manufacturing process which frequently produces scrap and rework can significantly affect profitability. Optimal mean setting is a methodology by which the process mean is adjusted to maximize profit. This paper studies the dynamics of the problem and investigates the possibility of applying different process means to each rework iteration, to further maximize profit. A proof is given confirming there is only one optimal mean that applies over all rework iterations in the single feature case. However, applying similar reasoning to a dual feature case led to the development of a new optimal mean setting methodology which outperformed the existing approach in terms of the maximum expected profi
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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