862 resultados para Process capability analysis
Resumo:
This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimize heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed with basis on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.
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The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.
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Strategic alliances represent a key driver for internationalization and growth, being the purpose of this work project to better understand the intertwined relationship between trust and the existence of an alliance management position. Previous research supports the positive impact of such position in stock market returns. However, little attention has been given to the impact of such position on the level of trust in the collaborative arrangement, which is deemed to be a key driver for alliance success. A qualitative comparative case-study of three Portuguese SMEs is used to draw conclusions from the literature to real life business cases and it demonstrates the positive impact of an alliance management position on trust.
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The interest in chromium (Cr) arises from the widespread use of this heavy metal in various industrial processes that cause its release as liquid, solid and gaseous waste into the environment. The impact of Cr on the environment and living organisms primarily depends on its chemical form, since Cr(III) is an essential micronutrient for humans, other animals and plants, and Cr(VI) is highly toxic and a known human carcinogen. This study aimed to evaluate if the electrodialytic process (ED) is an appropriate treatment for Cr removal, through a critical overview of Cr speciation, before and after the ED experiments, to assess possible Cr(III)-Cr(VI) interconversions during the treatment. ED was the treatment technique applied to two types of matrices containing Cr: chromate copper arsenate (CCA) contaminated soil and municipal solid waste incineration (MSWI) fly ash. In order to study Cr remediation, three EDR set-ups were used: a new set-up, the combined cell (2/3C or 3/2C), with three compartments, alternating current between two anodes and different initial experimental conditions, one set-up with three compartments (3C cell) and the other set-up with two compartments (2C cell). The Cr removal rates obtained in this study were between 10-36% for the soil, and 1-13% for the fly ash. The highest Cr removal rates were achieved in the 26 days experiments: 36% for the soil, 13% for the fly ash. Regarding the 13 days experiments, the highest Cr removal rates were attained with the 2/3C set-up: 24% for the soil, 5% for the fly ash. The analysis of Cr(VI) was performed before and after ED experiments to evaluate eventual changes in Cr speciation during the treatment. This analysis was conducted by two methods: USEPA Method 3060A, for the extraction of Cr(VI); and Hach Company Method 8023, for the detection of Cr(VI). Despite the differences in Cr total concentration, both matrices presented a similar speciation, with Cr(III) being the main species found and Cr(VI) less than 3% of Cr total, before and after the treatment. For fly ash, Cr(VI) was initially below the detection limit of the method and remained that way after the treatment. For soil, Cr(VI) decreased after the treatment. Oxidation of Cr(III) to Cr(VI) did not occur during the ED process since there was no increase in Cr(VI) in the matrices after the treatment. Hence, the results of this study indicate that ED is an appropriate technique to remediate matrices containing Cr because it contributes to Cr removal, without causing Cr(III)-Cr(VI) interconversions.
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The level of information provided by ink evidence to the criminal and civil justice system is limited. The limitations arise from the weakness of the interpretative framework currently used, as proposed in the ASTM 1422-05 and 1789-04 on ink analysis. It is proposed to use the likelihood ratio from the Bayes theorem to interpret ink evidence. Unfortunately, when considering the analytical practices, as defined in the ASTM standards on ink analysis, it appears that current ink analytical practices do not allow for the level of reproducibility and accuracy required by a probabilistic framework. Such framework relies on the evaluation of the statistics of the ink characteristics using an ink reference database and the objective measurement of similarities between ink samples. A complete research programme was designed to (a) develop a standard methodology for analysing ink samples in a more reproducible way, (b) comparing automatically and objectively ink samples and (c) evaluate the proposed methodology in a forensic context. This report focuses on the first of the three stages. A calibration process, based on a standard dye ladder, is proposed to improve the reproducibility of ink analysis by HPTLC, when these inks are analysed at different times and/or by different examiners. The impact of this process on the variability between the repetitive analyses of ink samples in various conditions is studied. The results show significant improvements in the reproducibility of ink analysis compared to traditional calibration methods.
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The quantitative component of this study examined the effect of computerassisted instruction (CAI) on science problem-solving performance, as well as the significance of logical reasoning ability to this relationship. I had the dual role of researcher and teacher, as I conducted the study with 84 grade seven students to whom I simultaneously taught science on a rotary-basis. A two-treatment research design using this sample of convenience allowed for a comparison between the problem-solving performance of a CAI treatment group (n = 46) versus a laboratory-based control group (n = 38). Science problem-solving performance was measured by a pretest and posttest that I developed for this study. The validity of these tests was addressed through critical discussions with faculty members, colleagues, as well as through feedback gained in a pilot study. High reliability was revealed between the pretest and the posttest; in this way, students who tended to score high on the pretest also tended to score high on the posttest. Interrater reliability was found to be high for 30 randomly-selected test responses which were scored independently by two raters (i.e., myself and my faculty advisor). Results indicated that the form of computer-assisted instruction (CAI) used in this study did not significantly improve students' problem-solving performance. Logical reasoning ability was measured by an abbreviated version of the Group Assessment of Lx)gical Thinking (GALT). Logical reasoning ability was found to be correlated to problem-solving performance in that, students with high logical reasoning ability tended to do better on the problem-solving tests and vice versa. However, no significant difference was observed in problem-solving improvement, in the laboratory-based instruction group versus the CAI group, for students varying in level of logical reasoning ability.Insignificant trends were noted in results obtained from students of high logical reasoning ability, but require further study. It was acknowledged that conclusions drawn from the quantitative component of this study were limited, as further modifications of the tests were recommended, as well as the use of a larger sample size. The purpose of the qualitative component of the study was to provide a detailed description ofmy thesis research process as a Brock University Master of Education student. My research journal notes served as the data base for open coding analysis. This analysis revealed six main themes which best described my research experience: research interests, practical considerations, research design, research analysis, development of the problem-solving tests, and scoring scheme development. These important areas ofmy thesis research experience were recounted in the form of a personal narrative. It was noted that the research process was a form of problem solving in itself, as I made use of several problem-solving strategies to achieve desired thesis outcomes.
Resumo:
To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.
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This article reflects on key methodological issues emerging from children and young people's involvement in data analysis processes. We outline a pragmatic framework illustrating different approaches to engaging children, using two case studies of children's experiences of participating in data analysis. The article highlights methods of engagement and important issues such as the balance of power between adults and children, training, support, ethical considerations, time and resources. We argue that involving children in data analysis processes can have several benefits, including enabling a greater understanding of children's perspectives and helping to prioritise children's agendas in policy and practice. (C) 2007 The Author(s). Journal compilation (C) 2007 National Children's Bureau.
Resumo:
Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.
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A case study on the tendering process and cost/time performance of a public building project in Ghana is conducted. Competitive bids submitted by five contractors for the project, in which contractors were required to prepare their own quantities, were analyzed to compare differences in their pricing levels and risk/requirement perceptions. Queries sent to the consultants at the tender stage were also analyzed to identify the significant areas of concern to contractors in relation to the tender documentation. The five bidding prices were significantly different. The queries submitted for clarifications were significantly different, although a few were similar. Using a before-and-after experiment, the expected cost/time estimate at the start of the project was compared to the actual cost/time values, i.e. what happened in the actual construction phase. The analysis showed that the project exceeded its expected cost by 18% and its planned time by 210%. Variations and inadequate design were the major reasons. Following an exploration of these issues, an alternative tendering mechanism is recommended to clients. A shift away from the conventional approach of awarding work based on price, and serious consideration of alternative procurement routes can help clients in Ghana obtain better value for money on their projects.