Using a spiral approach to facilitate engineering research and education embedded in real industry settings

Engineering research and education is often done in collaboration with industrial partners through the Industry as Laboratory (IaL), and Challenge-Based Learning (CBL) paradigms. However, its findings are not always adopted, despite the use of well-established and rigorous research methodologies. Academia employs oftentimes extensive and time consuming analyses, while industry operates in smaller cycles with tangible intermediate results. This can lead to the industry losing interest in the research. The Spiral Approach for Systems Engineering Research (SASER) is an approach that aims to mitigate that risk. This can have a twofold benefit in the industry remaining interested, but also the researcher staying motivated. To apply this approach in practice and receive feedback from a broader audience of people we created the SEFI 2023 workshop entitled: “Using a spiral approach to facilitate engineering research and education embedded in real industry settings”. This workshop has the objective of discussing best practices when conducting engineering education and research in collaboration with industry. To achieve the planned learning outcomes, the workshop activities will follow a cycle of learn=&gt;apply=&gt;reflect on provided specific case studies that are developed in order to allow the application of SASER. The workshop was attended by 8 participants that were split into 2 groups of 4 people (the 2nd group further decided to split further into a group of 3 and one individual). The results of the case studies and the reflection of the participants in the workshop indicate a clear potential for SASER and are promising for further research and development.</p

Using A Spiral Approach To Facilitating Engineering Research And Education In Real Industry Settings

Engineering research and education is often done in collaboration with industrial partners through the Industry as Laboratory (IaL), and Challenge-Based Learning (CBL) paradigms. However, its findings are not always adopted, despite the use of well-established and rigorous research methodologies. Academia employs oftentimes extensive and time consuming analyses, while industry operates in smaller cycles with tangible intermediate results. This can lead to the industry losing interest in the research. The Spiral Approach for Systems Engineering Research (SASER) is an approach that aims to mitigate that risk. This can have a twofold benefit in the industry remaining interested, but also the researcher staying motivated. To apply this approach in practice and receive feedback from a broader audience of people we created the SEFI 2023 workshop entitled: “Using a spiral approach to facilitate engineering research and education embedded in real industry settings”. This workshop has the objective of discussing best practices when conducting engineering education and research in collaboration with industry. To achieve the planned learning outcomes, the workshop activities will follow a cycle of learn=\u3eapply=\u3ereflect on provided specific case studies that are developed in order to allow the application of SASER. The workshop was attended by 8 participants that were split into 2 groups of 4 people (the 2nd group further decided to split further into a group of 3 and one individual). The results of the case studies and the reflection of the participants in the workshop indicate a clear potential for SASER and are promising for further research and development

Real-time myoelectric control of wrist/hand motion in Duchenne muscular dystrophy:A case study

Introduction: Duchenne muscular dystrophy (DMD) is a genetic disorder that induces progressive muscular degeneration. Currently, the increase in DMD individuals' life expectancy is not being matched by an increase in quality of life. The functioning of the hand and wrist is central for performing daily activities and for providing a higher degree of independence. Active exoskeletons can assist this functioning but require the accurate decoding of the users' motor intention. These methods have, however, never been systematically analyzed in the context of DMD.Methods: This case study evaluated direct control (DC) and pattern recognition (PR), combined with an admittance model. This enabled customization of myoelectric controllers to one DMD individual and to a control population of ten healthy participants during a target-reaching task in 1- and 2- degrees of freedom (DOF). We quantified real-time myocontrol performance using target reaching times and compared the differences between the healthy individuals and the DMD individual.Results and Discussion: Our findings suggest that despite the muscle tissue degeneration, the myocontrol performance of the DMD individual was comparable to that of the healthy individuals in both DOFs and with both control approaches. It was also evident that PR control performed better for the 2-DOF tasks for both DMD and healthy participants, while DC performed better for the 1-DOF tasks. The insights gained from this study can lead to further developments for the intuitive multi-DOF myoelectric control of active hand exoskeletons for individuals with DMD

More than 10 years of industry 4.0 in the Netherlands:an opinion on promises, achievements, and emerging challenges

The concept of Industry 4.0, as a means to move forward in the industrial ecosystem, has reached an important turning point. Where do we stand now in terms of industrial innovation and transition? This opinion paper provides an overview of the situation in the Netherlands, a reflection on what has been achieved by the Industry 4.0 paradigm, and the necessary way forward to solidify its implementation. Tentative results reveal that the pervasiveness of Industry 4.0 applications is sector-specific. This work provides industrial stakeholders and academics with useful suggestions and a possible path to move towards better integration of Industry 4.0 in company reality. In this opinion paper, we employ a mixed methods research methodology to argue that, based on our findings on industrial adaptation in The Netherlands, Industry 4.0 is the outcome of an evolutionary process and not of a revolution, as it is often claimed