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    Implications of digitalization for value chains

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    Social behaviours in dog-owner interactions can serve as a model of companion robot behaviour

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    It is essential for social robots to fit in the human society. In order to facilitate this process we propose to use the family dog’s social behaviour shown towards humans as an inspiration. In this study we explored dogs’ low level social monitoring in dog-human interactions and extracted individually consistent and context dependent behaviours in simple everyday social scenarios. We found that proximity seeking and tail wagging were most individually distinctive in dogs, while activity, orientation towards the owner, and exploration were dependent on the context and/or the activity of the owner. The functional analogues of these dog behaviours can be implemented in social robots of different embodiments in order to make them acceptable and more believable for humans

    Moving Sensory Ethnography Online

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    This case study reflects on the process of migrating Sensory Ethnography online in response to the social distancing measures that came into effect in the UK to contain the spread of COVID-19. The research case study in focus sets out to examine whether new industrial robots’ impact how touch works in the industry, affecting the social and sensory character of manual labor. Fieldwork was initially designed with five selected sites. At the time of the first lockdown, three stints of fieldwork were complete; however, with physical access to the other sites no longer possible, the anticipated trajectory of the project was derailed. Consequently, the research focus was reorientated and was moved online through sensory interviews. This posed a set of challenges that were navigated and are reflected upon in this case study. Two reflexive strategies and a set of techniques are illustrated in retelling how the research pivoted online. Reflecting on these research experiences raises questions around the prospects for, and nature of, doing sensory ethnography online. Therefore, while this case is situated within the specific peculiarities of researching touch during the pandemic, the lessons that can be drawn from these experiences will resonate more broadly with a contemporary context where sensory researchers are operating in increasingly digital worlds

    Autonomous Robotic Systems in a Variable World:A Task-Centric approach based on Explainable Models

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    Impact of COVID-19 on Airline Industry and Strategic Plan for its Recovery with Special Reference to Data Analytics Technology

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    This paper discusses the status quo of the airline industry around the world facing the COVID-19 pandemic situation. The purpose of the first part of this study was to assess the impact of COVID-19 on global air traffic, airline revenues by region of operation, number of international passengers by region, and the number of domestic passenger traffic by route group. The data for this study was collected from January 2019 to December 2020 from the International Civil Aviation Organization (ICAO) database. The research strategy of the second part of this study is based on PEST analysis which is applied to evaluate the current situation of the airline industry. Based on the findings, this paper suggests strategies and recommendations for the airline industry to adapt to the pandemic situation based on technology aspects more specifically related to data analytics with a multi-step approach for COVID-19 Airline Recovery Plan. The results and recommendations of this research study will provide valuable information to the aviation industry for its preparedness for the Post-COVID-19 era

    Autonomous Robotic Systems in a Variable World:A Task-Centric approach based on Explainable Models

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    A model for assessment of human assistive robot capability

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    The purpose of this research is to develop a generalised model for levels of autonomy and sophistication for autonomous systems. It begins with an introduction to the research, its aims and objectives before a detailed review of related literature is presented as it pertains to the subject matter and the methodology used in the research. The research tasks are carried out using appropriate methods including literature reviews, case studies and semi-structured interviews. Through identifying the gaps in the current work on human assistive robots, a generalised model for assessing levels of autonomy and sophistication for human assistive robots (ALFHAR) is created through logical modelling, semi-structured interview methods and case studies. A web-based tool for the ALFHAR model is also created to support the model application. The ALFHAR model evaluates levels of autonomy and sophistication with regard to the decision making, interaction, and mechanical ability aspects of human assistive robots. The verification of the model is achieved by analysing evaluation results from the web-based tool and ALFHAR model. The model is validated using a set of tests with stakeholders participation through the conduction of a case study using the web-based tool. The main finding from this research is that the ALFHAR model can be considered as a model to be used in the evaluation of levels of autonomy and sophistication for human assistive robots. It can also prove helpful as part of through life management support for autonomous systems. The thesis concludes with a critical review of the research and some recommendations for further research

    Big Data IoT-based Agile-Lean Logistic in Pharmaceutical Industries

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    Purpose: In today’s world, with the presence of huge volumes of data, although organizations have faced many problems, using big data analysis has been able to significantly improve their efficiency and integrate information in the supply chain through the topic of computing. Cloud and big data achieve coordination between components and improve communication. On the other hand, Internet of Things (IoT) technology tools are one of the most important sources of big data production, and understanding and correct use of this data and their timely analysis using big data analysis techniques and technologies based on artificial intelligence can be effective steps to improve supply chain processes. Also, the use of these technologies can play an important role in process agility and, as a result, supply chain resilience. Methodology: In this study, the dimensions and key components of the use of large data obtained from the Internet of Things (IoT) in an industry's supply chain are investigated as a case study. Finally, a model for implementing an agile and lean supply chain based on IoT data analysis to improve the supply chain performance of these industries during emergency drug distribution during critical conditions is presented. Findings: This study shows that these technologies can be used as a powerful enabler, especially in the distribution of fast-acting pharmaceutical products.                                                                         Originality/Value: In this paper a model for implementing an agile and lean supply chain based on IoT data analysis to improve the supply chain performance of these industries during emergency drug distribution during critical conditions is presented

    Agile Methods on the Shop Floor: Towards a "Tesla Production System"?

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    This discussion paper investigates two questions: To what extend can Tesla be regarded as a digital firm, and do we - as a result - see elements of a distinct "Tesla production system"? While the EV-startup is widely approached as a competing automaker focusing on the electric drive train, which it certainly is, this paper argues that it can only fully be understood as a digital firm - a digital car company with a digital product embedded in a digital ecosystem. Its roots in Silicon Valley, its software-first approach, and its strategic exploitation of user activity data point into this direction. In the second part, this paper explores to what extent Tesla's rootedness in software and its Silicon-Valley ancestry gave reason to introduce methods borrowed from software development on the shop floor. To a certain degree, concepts from agile software development found their way to the very assembly-line at Tesla. Although it might be exaggerated to speak of a distinct "Tesla Production system", indications for a considerable and possibly enduring alteration of Lean Production paradigm can be determined
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