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[pt] A Gestão da Cadeia de Suprimento é uma área de crescente interesse na literatura, e da mesma forma as companhias estão cada vez mais voltando à atenção, especificamente, para técnicas para Gestão de Risco da Cadeia de Suprimento. Porém, existe uma carência na literatura para estudos empíricos da Gestao de Risco, em particular para grandes projetos como a construção naval, mesmo sendo muitos das características dessa indústria – como longos períodos de lead time, complexos processos produtivos, alto investimento de capital e estruturas de organização dinâmica – aumenta a sua exposição a riscos. Existe um gap na literatura com relação à gestão de risco para estudos empíricos, em especial para grandes projetos, como a construção naval. No Brasil em específico, esta carência da indústria se tornou mais evidente devido ao fato da indústria de construção naval no Brasil ter vivenciado um longo período de recessão nas décadas de 80 e 90. Este estudo empírico visa preencher essa lacuna, através da identificação dos principais riscos da cadeia de suprimentos para os principais estaleiros brasileiros e oferecendo um perfil de risco inicial para que a indústria. Foi realizada uma coleta de dados com os estaleiros visando (1) identificar os principais riscos presentes na indústria naval brasileira; (2) avaliar a probabilidade de ocorrência destes riscos; e (3) reconhecer as fontes principais e potenciais impactos de riscos, bem como possíveis estratégias para mitigar os riscos. O estudo confirmou a presença de riscos identificados em estudos da indústria de construção naval em outros países, e também identificou novos riscos relevantes no contexto brasileiro. Por fim, for apresentado um perfil de risco para a indústria naval brasileira. / [en] Supply Chain Management (SCM) is an area of growing interest by scholars and practitioners, and companies are increasingly paying attention to the role of risk in their business, in particular, to the development of Supply Chain Risk Management (SCRM) techniques. However, a gap in the literature is observed in regards to empirical studies on SCRM, in special for large projects as the shipbuilding industry, despite the fact that many characteristics of this industry - such as long lead times, complex processes, financial intensity and dynamic organization structures - make it fundamentally vulnerable to risks. For the Brazilian shipbuilding in particular, empirical evidence also showed to be more crucial, not only because there is a scarcity of studies for shipbuilding in general, but also because the Brazilian shipbuilding industry experienced a long period of stagnation during the 80s and 90s decades. This study attempts to fulfill this gap, by identifying the main supply chain risks for Brazilian ship builders and offering an initial risk profile for the industry. The study integrated and implemented methodologies proposed by other scholars in the field to develop a survey approach targeted at experts from shipyards in Brazil. The survey asked participants to: (1) identify the main risks present in the Brazilian shipbuilding industry; (2) evaluate the likelihood of their occurrence; and (3) recognize main sources and potential impacts, as well as potential strategies to mitigate them. The study confirmed the presence of risks identified in the literature and new ones of particular importance to the Brazilian context. The study also yielded a preliminary risk profile for the Brazilian shipbuilding industry.

Th. Ph. D.--University of Birmingham (UK), 1995.

En esta tesis se presenta la aplicación de redes neuronales artificiales (ANNs) para modelar dos variables de gran importancia en la ingeniería del riego: la evapotranspiración de referencia y las pérdidas de carga localizadas provocadas por los emisores integrados. Por una parte, se ha propuesto un modelo ANN para la predicción de las pérdidas de presión ocasionadas por la inserción de emisores integrados en los laterales de riego localizado, lo que nunca se ha llevado a cabo mediante redes neuronales. Por otro lado, se ha analizado la validez de un modelo ANN de 4 inputs existente para predicción de ETo en distintos contextos continentales de la Comunidad Valenciana y se ha planteado un nuevo modelo ANN de 6 inputs para mejorar el rendimiento del anterior. Para llevar a cabo dichos estudios, se ha recurrido al uso de perceptrones multinivel (MLP) sometidos al algoritmo Levenberg Marquardt. En los tres casos, se analizaron redes con múltiples configuraciones y se repitió el proceso de entrenamiento de cada red un número variable de veces para compensar el efecto derivado de la asignación inicial aleatoria de pesos en dicho proceso. Asimismo, en los tres problemas abordados se llevaron a cabo distintas estrategias en la asignación de los datos disponibles a los conjuntos de entrenamiento, validación cruzada y test. A diferencia de los modelos estadísticos existentes, el modelo ANN propuesto para predicción de pérdidas de carga localizadas posee indicadores de rendimiento referidos a un set de test independiente, lo que ha permitido evaluar su potencial real de generalización. Para diferentes combinaciones de validación cruzada, con datos al menos de tres emisores, se obtuvieron valores medios del performance index por encima de 0.85. En cuanto a los modelos de predicción de ETo, el rendimiento del modelo existente de 4 inputs depende del grado de oscilación térmica del contexto continental en que se utilice y su validez fuera de la sede de entrenamiento es muy lim / Martí Pérez, PC. (2009). Aplicación de redes neuronales artificiales para predicción de variables en ingeniería del riego: evapotranspiración de referencia y pérdidas de carga localizadas en emisores integrados [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64909 / Palancia

Engineered to Order (ETO) products can benefit from the concepts and tools offered by Product and Platforms Line Engineering (PLE) (such as increased variety offer and efficient use of resources), and CAD/PLM (Computer Aided Design/Product Life-cycle management) in order to gain competitiveness. This paper portrays a framework for describing and measuring the processes that conform that connection between PLE and CAD; presents a description of the key components of the entire process, their relationships, as well a set of metrics for assessing the ability of a process for creating Geometrical CAD Platforms. A case study of an ETO product development with the implementation of this framework is presented in two different scenarios for validating the concepts exposed and demonstrating the use of the framework for assessing the capability of an organization for creating 3DCAD platforms for ETO Products.

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No description available.

Syfte – Examensarbetets syfte  är att beskriva utvecklingsprocessen för utbildningar inom en konsultverksamhet utifrån kundorderpunktsmodeller som används inom tillverkande verksamheter. Syftet har brutits ned i två delmål: Delmål: Att beskriva utvecklingsprocessen för utbildningar inom en konsultverksamhet. Delmål: Att placera in utvecklingsprocessen för utbildningar i kundorder­punkts­modellerna. Metod – För att uppfylla examensarbetets syfte genomfördes en fallstudie på teknikkonsultföretaget Combitech AB i Jönköping. För att ge en grund till det teoretiska ramverket gjordes en litteraturstudie. Empiri samlades in genom en fallstudie, innehållande intervjuer och dokumentstudie. Empirin har sedan analyserats mot det teoretiska ramverket och genom mönsterjämförelse placerades kundorderpunkterna in i modellerna. Analysen har bidragit till att uppnå examensarbetets syfte. Resultat – De utvecklingsprocesser som identifierades för de tre utbildnings­kategorierna saknade ett standardiserat arbetssätt. I stället var utbildningarna ofta enskilt framtagna och hårt knutna till de enskilda konsulterna. Examensarbetet visar att de två kundorderpunktsmodellerna från tillverkande verksamhet fungerade olika bra för att visualisera graden av kundorderstyrning i utvecklingsprocessen för en konsultverksamhet. Som visualiseringsverktyg fungerade den tvådimensionella kundorderpunktsmodellen lite sämre då den inte visade så stor skillnad mellan de beskrivna processerna. Modellen för utvecklings- och designprocessen var mer nyanserad och fungerade bättre för att indikera vilken aktivitet i utvecklingsprocessen som var kundorderdriven. Implikationer – Kundorderpunktsmodellerna är skapade för en tillverkande verksamhet som producerar fysiska varor och genom att testa modellerna på en tjänsteverksamhet utmanas modellens ramverk och funktion. Detta examensarbete har bidragit till att täcka en del av det identifierade teoretiska gapet i användningen av kundorderpunktsmodeller mellan tillverkande verksamhet och tjänsteverksamhet. Vidare forskning – För att bidra till att täcka det teoretiska gapet kan förslagsvis den tvådimensionella kundorderpunktsmodellen vidareutvecklas och anpassas helt för tjänsteverksamhet. En person med akademisk kunskap om tjänsteverksamhet och kundorderpunktsteorier skulle kunna bidra med ny teori inom området. Det skulle också vara intressant att undersöka om det går att kombinera de två kundorderpunktsmodellerna som presenterats i detta examensarbete. / Purpose – The purpose of this thesis is to describe the development process for educations within consulting with customer order decoupling point models commonly used within manufacturing operations. The purpose has been broken down into two parts: Objective: To describe the development process for educations within a consultancy. Objective: To position the development process for educations based on the customer order decoupling point models. Method – In order to meet the thesis purpose, a case study was conducted on the engineering consultancy Combitech AB in Jönköping. To provide a basis for the theoretical framework a literature study was performed. To collect empirical data a case study including interviews and a document study was conducted. The empirical data were then analysed against the theoretical framework, and through pattern matching the customer order decoupling points were positioned into the models. The analysis has helped to achieve the thesis purpose. Findings – The engineering process that was identified for the three educational categories lacked a standardized approach. Instead, programs were often individually designed and tightly tied to the individual consultants. The thesis shows that the two customer order decoupling point models from manufacturing operations varied in usefulness to visualize the degree of customer order management in the engineering process of a consultancy business. As a visualization tool the two-dimensional customer order decoupling point model was of limited value because it didn’t show much difference between the processes described. The model for the engineering and design process was more nuanced and worked better to indicate which activities in the engineering process that were customer order driven. Implications – The customer order decoupling point models are created for manufacturing operations that produce physical goods and by testing these models on a service, the model framework and function is challenged. This thesis has helped to cover a part of the identified theoretical gap in the use of customer order decoupling point models between manufacturing operations and service operations. Limitations – To help cover the theoretical gap the two-dimensional customer order decoupling point model can tentatively be further developed and fully customized for service operations. A person with an academic knowledge of service and customer order decoupling point theories could help create new theory in the field. It would also be interesting to investigate whether it is possible to combine the two customer order decoupling point models presented in this thesis. / KOPtimera

Digital transformation is rising rapidly, where absolutely any kind of data is readily available. With the rise in digital information and technologies, businesses are aiming at measuring their processes and thereby getting better control over their operations. Industries are striving to increase efficiency and productivity to survive in the high global competitive market by adopting a digital tool. Simulation has been one of the most common tools of Industry 4.0 that allows a virtual representation of the real system. The use of simulation has tremendously increased in manufacturing industries due to its advantages where changes can be made and checked virtually before implementing them to the physical system. Data acquisition has been an important aspect that remains unfocussed especially in Engineer to Order (ETO) and Make to Order (MTO) environments where the production processes are complex, nonstandardised and depend heavily on manual work leading to a prolonged barrier towards digitalisation. So, can data create new values for companies? Are firms realising the importance of data? As the economy is moving towards a more data-driven state, it is essential for companies to realise the importance of data and find efficient ways of data collection. The thesis is based on a case study at an electrical transformer manufacturing firm taking its first step towards digital technology to have better control over its manufacturing processes. However, this transformation is primarily hindered by the limited availability of data and poor data quality due to manual data acquisition methods. Analysis of organisational documents and Value Stream Mapping (VSM) have been used to analyse missing primary and secondary production data. The results of this study conclude that modelling of the system can give additional data gaps, and the simulation model can be served as a powerful decision support tool for the firm. This switch in approach from intuition-based decision making to more fact-based decision making can result in better planning and control over the production. This thesis will lay the foundation for studies related to data acquisition and simulation in an ETO environment as it is not widely discussed in the existing literature

The competition in the manufacturing industry has never been higher. Owing to the technological changes and advancements in the market, readily available data is no longer a thing of the past. Numerous studies have discussed the impact of industry 4.0, digital transformation as well as better production planning methods in the manufacturing industry.  The Mass-Manufacturing industry, in specific, has gained efficiency levels in production that were previously unimaginable. Industry 4.0 has been discussed as the ‘next big thing’ in the manufacturing context. In fact, it is seen as a necessity for manufacturing companies to stay competitive. However, efficient production planning methodologies are a preliminary requirement in order to successfully adopt the new manufacturing paradigms. The Engineering-to-order (ETO) industry is still widely unexplored by the academia ETO industries, barely have any production planning methodologies to rely on owing to their complex production processes and high reliance on manual-labour. Regression techniques have repeatedly been used in the production planning context. Considering its statistical prowess, it is no surprise that even the newer machine-learning techniques are based on regression. Considering its success in the mass-manufacturing industry for production planning, is it possible that its usage in the ETO industry might lead to the same results? This thesis involves a case study that was performed at an electrical transformer manufacturing plant in Sweden. After understanding the several operations that are performed in the production process, regression techniques are employed to estimate man-hours. The results from the study reconfirm the statistical prowess of regression and show the possibility of using regression in order to estimate man-hours in the ETO industry. In addition, several factors that can affect successful adoption of this tool in the production planning context are discussed. It is hoped that this study will lay the foundation for better production planning methodologies for the ETO industries in the future which might subsequently result in more data-driven decision making rather than instincts.