A proposal to introduce digitalization technologies within the automation learning process

Although the digital factory (DF) concept has raised high expectations since its inception, it is still missing industrial impact. One of the problems attributed to this issue is the lack of education curricula for enhancing the related digital competences of the future professionals. Higher education institutions, as major stakeholders in education, should introduce the new technologies for DF in practical courses. However, it is difficult to deal with the complexity of those technologies in a time-limited environment such us a bachelor or a master course. Instead of providing complete knowledge, this paper proposes to focus on the methodological aspects that allow students to acquire the skills needed to handle those technologies. Specifically, this paper illustrates this approach for teaching virtual commissioning (VC) within the automation learning process. The goal is to show the students how to use powerful industrial tools for performing VC through a set of methodological steps that help students manage the complexity of the VC process regardless of the specific tools used for it.This work was financed by Erasmus+, UE (grant number 2018-1-FR01-KA203-048175) and by GV/EJ (grant numbers IT1324-19 and KK-2019-00095

Explorando ferramentas de modelação digital, aumentada e orientada por dados em engenharia e design de produto

Tools are indispensable for all diligent professional practice. New concepts and possibilities for paradigm shifting are emerging with recent computational technological developments in digital tools. However, new tools from key concepts such as “Big-Data”, “Accessibility” and “Algorithmic Design” are fundamentally changing the input and position of the Product Engineer and Designer. After the context introduction, this dissertation document starts by extracting three pivotal criteria from the Product Design Engineering's State of the Art analysis. In each one of those criteria the new emergent, more relevant and paradigmatic concepts are explored and later on are positioned and compared within the Product Lifecycle Management wheel scheme, where the potential risks and gaps are pointed to be explored in the experience part. There are two types of empirical experiences: the first being of case studies from Architecture and Urban Planning — from the student's professional experience —, that served as a pretext and inspiration for the experiments directly made for Product Design Engineering. First with a set of isolated explorations and analysis, second with a hypothetical experience derived from the latter and, finally, a deliberative section that culminate in a listing of risks and changes concluded from all the previous work. The urgency to reflect on what will change in that role and position, what kind of ethical and/or conceptual reformulations should exist for the profession to maintain its intellectual integrity and, ultimately, to survive, are of the utmost evidence.As ferramentas são indispensáveis para toda a prática diligente profissional. Novos conceitos e possibilidades de mudança de paradigma estão a surgir com os recentes progressos tecnológicos a nível computacional nas ferramentas digitais. Contudo, novas ferramentas originadas sobre conceitos-chave como “Big Data”, “Acessibilidade” e “Design Algorítmico” estão a mudar de forma fundamental o contributo e posição do Engenheiro e Designer de Produto. Esta dissertação, após uma primeira introdução contextual, começa por extrair três conceitos-eixo duma análise ao Estado da Arte actual em Engenharia e Design de Produto. Em cada um desses conceitos explora-se os novos conceitos emergentes mais relevantes e paradigmáticos, que então são comparados e posicionados no círculo de Gestão de Ciclo de Vida de Produto, apontando aí potenciais riscos e falhas que possam ser explorados em experiências. As experiências empíricas têm duas índoles: a primeira de projetos e casos de estudo de arquitetura e planeamento urbanístico — experiência em contexto de trabalho do aluno —, que serviu de pretexto e inspiração para as experiências relacionadas com Engenharia e Design de Produto. Primeiro com uma série de análises e experiências isoladas, segundo com uma formulação hipotética com o compêndio dessas experiências e, finalmente, com uma secção de reflexão que culmina numa série de riscos e mudanças induzidas do trabalho anterior. A urgência em refletir sobre o que irá alterar nesse papel e posição, que género de reformulações éticas e/ou conceptuais deverão existir para que a profissão mantenha a sua integridade intelectual e, em última instância, sobreviva, são bastante evidentes.Mestrado em Engenharia e Design de Produt

Digital Twins:State of the Art Theory and Practice, Challenges, and Open Research Questions

Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation and forecasting. However, the theoretical framework and practical implementations of digital twins (DT) are still far from this vision. Although successful implementations exist, sufficient implementation details are not publicly available, therefore it is difficult to assess their effectiveness, draw comparisons and jointly advance the DT methodology. This work explores the various DT features and current approaches, the shortcomings and reasons behind the delay in the implementation and adoption of digital twin. Advancements in machine learning, internet of things and big data have contributed hugely to the improvements in DT with regards to its real-time monitoring and forecasting properties. Despite this progress and individual company-based efforts, certain research gaps exist in the field, which have caused delay in the widespread adoption of this concept. We reviewed relevant works and identified that the major reasons for this delay are the lack of a universal reference framework, domain dependence, security concerns of shared data, reliance of digital twin on other technologies, and lack of quantitative metrics. We define the necessary components of a digital twin required for a universal reference framework, which also validate its uniqueness as a concept compared to similar concepts like simulation, autonomous systems, etc. This work further assesses the digital twin applications in different domains and the current state of machine learning and big data in it. It thus answers and identifies novel research questions, both of which will help to better understand and advance the theory and practice of digital twins

Digital transformation as a backbone for holistic product development of transformers

Transformer manufacturers have a tough job competing globally, as it is a traditional, highly legacy driven, price-sensitive that also demands high reliability. With shareholders targeting to improve profits, manufacturers tend to focus on production capacity, flexibility, and improving production processes. On the contrary, when production goes global, the product development process faces critical hallenges in localisation of design and production, transnational design collaboration and meeting local regulations and standards. Therefore, it becomes key to international success. Digital transformation is a lever for transforming the product development process to realise the success of the global expansion. The article covers proven technologies from other industries and captures customers’ requirements to order execution by managing product complexity. System driven product development can be used as a tool for system thinking by adapting modularisation, knowledge management, and design automation in engineering design processes. A combination of these technologies can be successfully used to build a paperless factory and product digital twin. This article acts as a guide to top managers in defining proven approaches to the digital transformation of the product development process and hence to achieve success. Digital transformation in the product development of transformers is an important lever to increase profitability in transformer manufacturing. Digital transformation is a top management topic and needs a strategic approach. If appropriately addressed, it has the ability to transform the entire business. This encompasses multiple important functions, from customer requirements, product portfolio management, complexity management, design and development, manufacturing support, supply chain management. All these need to be integrated with a digital thread by analysing the existing process in four layers: product development process, sub-process, objects, and IT architecture. Following a combination of the top-down and bottom-up approach, management can successfully convert the benefits of digital transformation into balance sheet figures