Part Based Mold Quotation With Methods Of Machine Learning

The dominating mass-manufacturing process of today is plastic injection molding. This production process uses economies of scale because parts are produced in seconds at marginal cost of plastics. However, upfront investment costs for the tooling of molds are the basis for deciding if a mold is tooled and hence if a part is viable for mass-production. If tooling costs are too high, a product may not viable for production. If tooling costs are estimated too low by the tool shop, contract implications may arise. Because injection molds differ in their complexity, price estimations for the tooling of molds are an ongoing quest. There are various methods for estimating the costs of injection molds such as rule based, analytical or data driven approaches. The advantage of data driven approaches is the ability of adjusting to historical production data as well as readjusting while training on new batches of recent data. The focus of our research was to support the quotation process of tool shops. To this end, we studied a data driven machine learning approach. The goal of this research is to develop a method with humanlike quotation accuracy, achieve standardization, factor in historic quotation data and shorten quotation process times. The machine learning approach developed is based on geometry data of parts and additional meta-information. Within this research, a system was developed to interact with live production systems of an electronic part producing tool shop. The method developed was trained and validated on production data in a case study. To enhance the quotation process, the method developed was embedded into a server-based application with a web user interface and interfaces to live production systems for the automation of processes

A novel intelligent fault diagnosis method of rotating machinery based on deep learning and PSO-SVM

A novel intelligent fault diagnosis method based on deep learning and particle swarm optimization support vectors machine (PSO-SVM) is proposed. The method uses deep learning neural network (DNN) to extract fault features automatically, and then uses support vector machine to classify diagnose faults based on extracted features. DNN consists of a stack of denoising autoencoders. Through pre-training and fine-tuning of DNN, features of input parameters can be extracted automatically. This paper uses particle swarm optimization algorithm to select the best parameters for SVM. The extracted features from multiple hidden layers of DNN are used as the input of PSO-SVM. Experimental data is derived from the data of rolling bearing test platform of West University. The results demonstrate that deep learning can automatically extract fault feature, which removes the need for manual feature selection, various signal processing technologies and diagnosis experience, and improves the efficiency of fault feature extraction. Under the condition of small sample size, combining the features of the multiple hidden layers as the input into the PSO-SVM can significantly increase the accuracy of fault diagnosis

When costs from being a constraint become a driver for concept generation

Managing innovation requires solving issues related to the internal development and engineering processes of a company (supply side), in addition to facing the market and competition (demand side). In this context, the product development process is crucial, as different tradeoffs and issues that require managerial attention tend to arise. The main challenges result in managers requiring practical support tools that can help them in planning and controlling the process, and of designers requiring them for supporting their design decisions. Hence, the thesis aims to focus on product costs to understand its influence on design decisions as well as on the overall management of the product development process. The core part of the thesis is based on the models and methods developed for enhancing cost analysis at the beginning of the product development process. This investigation aims to determine the importance of cost estimation in improving the overall performance of a newly designed product. The focus on post-sales and, more generally, on the customer, has become so relevant that manufacturers have to take into account not only the most obvious aspects about the product and related services, but even consider the associated implications for customers during product use. However, implementing a product life cycle perspective is still a challenging process for companies. From a methodological perspective, the reasons include uncertainty regarding the available approaches and ambiguity about their application. In terms of implementation, the main challenge is the long-term cost management, when one considers uncertainty in process duration, data collection, and other supply chain issues. In fact, helping designers and managers efficiently understand the strategic and operational consequences of a cost analysis implementation is still a problem, although advanced methodologies for more in-depth and timely analyses are available. And this is even more if one considers that product lifecycle represents a critical area of investment, particularly in light of the new challenges and opportunities provided by big data analysis in the Industry 4.0 contexts. This dissertation addresses these aspects and provides a methodological approach to assess a rigorous implementation of life-cycle cost while discussing the evidence derived from its operational and strategic impacts. The novelty lies in the way the data and information are collected, dynamically moving the focus of the investigation with regard to the data aggregation level and the product structure. The way the techniques have been combined represents a further aspect of novelty. In fact, the introduced approach contributes to a new trend in the Product Cost Estimation (PCE) literature, which suggests the integration of different techniques for product life-cycle cost analysis. The findings obtained at the end of the process can be employed to assess the impact of platform design strategy and variety proliferations on the total life-cycle costs. By evaluating the possible mix of options, and hence offering the optimal product configuration, a more conscious way for planning the product portfolio has been provided. In this sense, a detailed operational analysis (as the cost estimation) is used to inform and drive the strategic planning of the portfolio. Finally, the thesis discusses the future opportunities and challenges for product cost analysis, assessing how digitalisation of manufacturing operations may affect the data gathering and analysis process. In this new environment, the opportunity for a more informed, cost-driven decision-making will multiply, leading to varied opportunities in this research field

Índice multicritério da perceção de qualidade do ambiente interior

Tese de doutoramento em Engenharia Mecânica, na especialidade de Aerodinâmica, apresentada à Faculdade de Ciências e Tecnologia da Universidade de CoimbraNeste trabalho são analisadas as contribuições do ambiente térmico, do ambiente acústico, do ambiente visual e da qualidade do ar para a perceção global da qualidade ambiental de um espaço interior. Os resultados obtidos repercutem a perceção humana após um tempo de exposição prolongada ao mesmo ambiente. Todos os ensaios efetuados, ao longo de cerca de dois anos, decorreram em contexto de sala de aula, no Campus de uma instituição de ensino superior e em edifícios naturalmente ventilados. Verificou-se que, nas condições referidas, é possível prever a perceção global de qualidade do ambiente interior com base em apenas três das quatro variáveis mencionadas: Conforto Térmico, Conforto Visual e Conforto Acústico. Para cada uma destas variáveis é possível determinar os respetivos voto médio previsível e percentagem previsível de insatisfeitos em função de um conjunto de variáveis físicas objetivamente mensuráveis. No caso do ambiente térmico verificou-se que o voto médio previsível, calculado de acordo com as correspondentes normas internacionais, apresenta boa concordância com o conjunto de resultados obtidos. No caso da percentagem previsível de insatisfeitos com o ambiente térmico, é proposta uma nova metodologia para a obtenção deste índice que apresenta vantagens ao nível da interpretação física dos resultados obtidos. Ainda no âmbito do conforto térmico, foi efetuada uma análise detalhada da aplicação do standard de conforto térmico adaptativo. Verificou-se que num contexto em que o nível de atividade metabólica é constante para toda a população, são as mesmas variáveis que influenciam o nível de isolamento térmico do vestuário que também influenciam a temperatura interior de conforto e exatamente nas mesmas ponderações. Com base nas conclusões obtidas, é proposta uma nova metodologia para o cálculo da temperatura interior de conforto adaptativo. É ainda proposto um novo índice de temperaturas: A Razão de Equivalência Térmica, concebido para a regulação de temperatura em edifícios naturalmente ventilados e edifícios híbridos. Nos casos dos conforto acústico e conforto visual, foram desenvolvidos dois índices do Voto Médio Previsível e Percentagem Previsível de Insatisfeitos, respetivamente para cada um destes. Em ambos os casos, o Voto Médio Previsível é obtido com base em grandezas físicas medidas localmente. No caso da perceção de qualidade do ar interior e nestas condições de exposição longa duração, não foi possível identificar um conjunto de grandezas físicas que permitam estimar o Voto Médio Previsível respetivo. É possível no entanto estimar a Percentagem Previsível de insatisfeitos com a qualidade do ar apenas com base no voto médio observado para esta perceção. A formulação matemática correspondente é apresentada, conjuntamente com as demais. Ainda no âmbito da perceção de qualidade do ar, foram identificados alguns efeitos que se supõem estar associados à matriz de distribuição espacial humana e que provocam alterações nas ponderações com que as perceções de ar viciado e de odores influenciam o voto médio de qualidade do ar. Em ensaios realizados em condições de exames finais, verificou-se que os "estados de alma" (traduzidos pela autoavaliação da performance face às expectativas iniciais) não influenciam as avaliações individuais de perceção da qualidade de cada um dos ambiente considerados nem tão pouco a avaliação global efetuada ao ambiente interior no seu todo. Verificou-se que todas as quatro perceções do ambiente interior, bem como a perceção global do mesmo, possuem uma matriz comum da curva de percentagem previsível de insatisfeitos em função do voto médio respetivo, quando este é expresso em escala unipolar.This work presents an assessment on the influence of thermal comfort, acoustic comfort, visual comfort and air quality perception over the global human perception of an indoor environment. All field essays were conducted in circumstances where the participants were exposed to the indoor environment for a long period. Experiments were conducted for a period of two years in naturally ventilated classrooms of an academic campus. In these circumstances it is possible to calculate both the Predicted Mean Vote and the Predicted Percentage of Dissatisfied for each of the significant environments that contribute to the global environmental perception. These models can be calculated based on a set of measured physical variables significant for each perception and the mathematical formulation for the significant perceptions is presented. In the case of Thermal Comfort, the Predicted Mean Vote was calculated according to the international standard were this index is described. The obtained values showed good agreement with the expressed vote in the field experiments. In the case of the Predicted Percentage of Dissatisfied with the thermal environment, a new methodology is proposed for the calculation of this index. The main benefit arises from the physical interpretation that can be extracted from the proposed equation. Still in the context of Thermal Comfort an analysis of the Adaptive Thermal Standard's application was performed. In field experiments performed, the metabolic level was not a variable that could be used to perform thermal adaptation, once all individuals were compelled to perform the same sedentary activity. In these conditions the temperature variables that are significant for the determination of the clothing insulation level showed to be exactly the same that allow to calculate the adaptive comfort temperature. The weight of each significant temperature to the calculation of the clothing insulation level is exactly the same to the calculation of the adaptive thermal comfort. Based on these conclusions, a new formula for the calculation of the adaptive comfort temperature is proposed and a new temperature index is proposed: The Thermal Equivalence Ratio. This index was conceived for the thermal regulation of the temperature in naturally ventilated buildings and hybrid buildings. In the cases of Acoustic Comfort and Visual Comfort, two Predicted Mean Vote indexes were developed (one for each of these). In both cases the respective indexes can be calculated based on a particular set of measured physical variables. Also, for each of these two comforts aspects, the Predicted Percentage of Dissatisfied can be calculated based on the same physical variables. In the case of the Air Quality Perception, it was not possible to identify a set of physical variables that would allow to estimate the respective Predicted Mean Vote. However, it is possible to estimate the Predicted Percentage of Dissatisfied with the indoor air, based on the mean vote for this perception. The mathematical formulation for this purpose is presented along with the other ones. Still in the context of the air quality perception, some effects were identified that cause changes in the weighting of the odour and air stiffness perception contributions to the air quality perception as a whole. These effects are supposed to be associated with the human distribution inside the room. In field experiments conducted during final exams it was possible to assess that the individual state of mind (described by the self-estimated performance compared to the individual expectations prior to the exam) does not influence the individual perceptions of the indoor environment nor the perception of the indoor environment as a whole. All four analysed perceptions of the indoor environment, as well as the global perception of the same environment present a common pattern of the percentage of dissatisfied curve when plotted as a function of the respective mean average vote, if this vote is presented in a unipolar scale