Assistance as a Service

This paper reviews currently available hardware and software for remote assistance during transformer maintenance and provides a newly created business model. Recently, a large number of wearables has entered the market, which could help support technicians in their maintenance work. This paper will focus on three of these wearables. Additionally, some software packages that are available offer a possibility to see what the technicians are doing at a certain point in time. It has been established that in order to provide a tailored remote assistance to customers, the remote assistance paradigm must include five key components, and they are: expertise, infrastructure, application and platforms, security and privacy, and a business process and business model. The resulting paradigm and the overlaying business model is called “assistance as a service”

Assistance as a Service

This paper reviews currently available hardware and software for remote assistance during transformer maintenance and provides a newly created business model. Recently, a large number of wearables has entered the market, which could help support technicians in their maintenance work. This paper will focus on three of these wearables. Additionally, some software packages that are available offer a possibility to see what the technicians are doing at a certain point in time. It has been established that in order to provide a tailored remote assistance to customers, the remote assistance paradigm must include five key components, and they are: expertise, infrastructure, application and platforms, security and privacy, and a business process and business model. The resulting paradigm and the overlaying business model is called “assistance as a service”

Smart operators: How augmented and virtual technologies are affecting the worker's performance in manufacturing contexts

Purpose: The correct interaction between the workforce and augmented, virtual, and mixed reality technologies represents a crucial aspect of the success of the smart factory. This interaction is, indeed, affected by the variability of human behavior and its reliability, which can strongly influence the quality, safety, and productivity standards. For this reason, this paper aims to provide a clear and complete analysis of the impacts of these technologies on the performance of operators. Design/methodology/approach: A Systematic Literature Review (SLR) was conducted to identify peer-reviewed papers that focused on the implementation of augmented and virtual technologies in manufacturing systems and their effects on human performance. Findings: In total, 61 papers were selected and thoroughly analyzed. The findings of this study reveal that Augmented, Virtual and Mixed Reality can be applied for several applications in manufacturing systems with different types of devices, that involve various advantages and disadvantages. The worker’s performance that are influencing by the use of these technologies are above all time to complete a task, error rate and mental and physical workload. Originality/value: Over the years Augmented, Virtual and Mixed Reality technologies in manufacturing systems have been investigated by researchers. Several studies mostly focused on technological issues, have been conducted. The role of the operator, whose tasks may be influenced positively or negatively by the use of new devices, has been hardly ever analyzed and a deep analysis of human performance affected by these technologies is missing. This study represents a preliminary analysis to fill this gap. The results obtained from the SLR allowed us to develop a conceptual framework that investigates the current state-of-the-art knowledge about the topic and highlights gaps in the current researchPeer Reviewe

Iniciação do BackOffice do GlarAssist

A situação pandémica de Covid-19 aumentou a procura por soluções remotas, uma vez que a mesma obrigou a maioria das empresas a transitarem as suas operações para um ambiente remoto. Por consequência, as soluções remotas ganharam ainda mais relevância nos últimos anos. Para além disso, o trabalho remoto colaborativo tem sido aprofundado para diversos contextos. Uma das abordagens mais investigadas é a assistência remota, que possibilita a assistência de pessoas à distância. A assistência remota (AR) permite auxiliar uma pessoa ou colaborador remotamente, evitando deslocações, e assim, reduzir o tempo e custos gastos nas mesmas. Um assistente pode observar o contexto do assistido, pela transmissão de vídeo e voz, em diversos dispositivos. Contudo, a assistência remota, apenas por vídeo e voz, não permite resolver a maioria das operações durante a assistência. Para auxiliar as AR é integrada a tecnologia de realidade aumentada (RA). A RA nas assistências remotas proporciona outras formas de realizar a assistência. Uma delas é a introdução de objetos 2D ou 3D ou de ferramentas de desenho no ambiente real do assistido, para indicar ao assistido pormenorizadamente as várias etapas a realizar para concluir as operações da assistência. A aplicação GlarAssist, desenvolvida pela Glartek, é uma solução de assistência remota com RA que possibilita aos seus utilizadores e organizações realizarem assistências com diversas ferramentas. Contudo, apenas está desenvolvida a funcionalidade da assistência remota e não existe a possibilidade de organizações gerirem os recursos da aplicação, como colaboradores ou assistências. Desta forma, os seus clientes têm vindo a procurar novas funcionalidades. No presente relatório é apresentado o trabalho realizado no início do desenvolvimento do BackOffice do GlarAssist. Para o desenvolvimento do mesmo foram implementadas funcionalidades que possibilitam aos diferentes utilizadores acederem à informação partilhada na aplicação, e ao mesmo tempo, criarem e gerirem as suas organizações. Assim, foram desenvolvidas onze funcionalidades que são abordadas no presente relatório. Durante o desenvolvimento das mesmas, foram realizados diferentes testes, para validar as funcionalidades antes de serem integradas no ambiente produtivo. Depois de realizados os testes, verifica-se que as funcionalidades foram incorporadas com sucesso no GlarAssist