Mutual learning in innovation and co-creation processes

New digital solutions are often lacking integration and acceptance by potential users. Therefore, only a small amount of innovative software solutions is really in use. The article describes a co-creation process by integrating end-users and relevant stakeholders right in the beginning in a social innovation process. Within this process, technology is seen as an enabler of innovation getting its relevance from new social practices of the people using it (e.g. working practices). Against the background of EU funded projects conducted by the authors (GT-VET, GREEN STAR, COCOP, and ROBOHARSH) the relevance of mutual learning processes of engineers / researchers / trainers on the one side and end-users / beneficiaries / learners on the other side will become evident. Moreover, new (digital and analogue) skills of employees have been identified as key for a successful digital transformation. Thereby, this article shows a twofold perspective on social innovation in education: new skills demands for employees and mutual learning processes of developers and users/stakeholders. To obtain needed skills, traditional innovation practices have to be changed by setting up a social innovation process. Such a process design has to include stakeholder and user involvement beyond pure feedback on a new technology. Co-creation means that experience, knowledge and ideas of users will be considered to ensure high usability and impact of the new technology framed by organisational and people related measures. In this respect, the innovation process and the innovation itself is much more than technological functionality–it is a contribution to new social practices and performances of the people that innovate and use the technology

A new innovation paradigm: combining technological and social innovation

A new innovation paradigm is needed to answer the societal, economic and environmental challenges the world and companies are facing. The EU funded Horizon 2020 SPIRE Project “Coordinating Optimisation of Complex Industrial Processes” (COCOP) is combining technological and social innovation within a steel company pilot case (Sidenor). The project aims at reducing raw materials consumption (and energy and emissions reduction as well) by plant-wide optimisation of production processes based on a software solution and at the same time changing social practices. Key for COCOP is a methodology integrating technological innovation within a social innovation process of co-creation and co-development by involving (potential) users of the future software system and relevant stakeholders right from the beginning; thereby improving effectiveness and impact of the innovations and the implementation process. This involvement is instructed and measured by social key performance indicators (social KPIs) and operationalised in surveys (questionnaire and interviews) with future users, engineers and external experts (from different industry sectors not involved in the project). The article presents the results of the starting point of COCOP illustrating the future user perspective of the pilot steel company (Sidenor) contrasted by the view of external experts – seriously taking into account the interfaces between technology, human and organisation

Understanding future skills: requirements for better data

Deliverable 6.3 focuses on data necessary for a comprehensive analysis of skills for digitalisation. Reliable data is needed to make appropriate decisions for the New Skills Agenda for Europe, national initiatives, and VET systems. Qualitative assessments of Tasks 6.1 to 6.4 are contrasted with quantitative WP3 data to identify gaps in data, indicators and measures that support monitoring of skill requirements. The main outcome is that there are still gaps in European data on skills that leave stakeholders partially blindfolded when looking at changes in skill demand and resulting needs for adaptations of skill supply. The report formulates requirements for the improvement of data

Understanding future skills and enriching the skills debate

This 3rd report of the Deliverable 6.1 builds on the framework for future skills and the skills categorisation developed in the 1st and 2nd reports of the Deliverable 6.1. The report focuses on empirical results of the Beyond 4.0 project on the topic of skills within the digital transformation. It draws from the range of empirical data collected during the qualitative research undertaken in Work Packages 4 and 8 of the BEYOND 4.0 project by identifying illustrative examples exemplifying the impact of digitalisation on the five categories of the aforementioned skills categorisation, presents and discusses the findings along the lines of skills demand and skills supply-sides issues, and accordingly, presents a number of recommendations for policymakers

Sociotechnical perspectives on digitalisation and Industry 4.0

The sociotechnical systems approach and theory (STS) helps to deal with today's rapid digital transformations in designing best suitable work, organisations and jobs. Not surprisingly, related approaches based on STS assumptions, such as modern sociotechnical thinking (MST) and workplace innovation (WPI) theory, are rapidly developing in Europe. Yet, research and (theoretical) analyses that place STS in today's digital industry challenges and WPI are sparse. The basics of sociotechnical concepts and new research, needs and perspectives for further development of STS in today's context need to be explored. Therefore, against the background of empirical experiences in logistics and process industry and in context of Industry 4.0, this article discusses firstly the model of classical STS approach and the skill orientated work design. Secondly, MST and its derived concept of WPI is positioned. Furthermore, a complementary 'practice theory' perspective is introduced, illustrated by an example design project. Finally, some future recommendations for research are made

Understanding future skills and enriching the skills debate

Deliverable 6.1 includes a framework for new or increasingly important skills within the digital transformation. This report updates an earlier version that was submitted in December 2019 and reflects progress and new insights. It includes results from a more detailed analysis of future skill demands performed within task 6.2 (which is based on a systematic literature review on skill needs for the digital transformation). These results were used to check and refine the skills ca- tegorisation developed in the first version of the report. Another progress was made within the chapter on the quantitative part of changes in skill demand (section 5) : The availability of data was reassessed by considering several further datasets

Education and Training in Inclusive Welfare States

This working paper analyses opportunities for inclusiveness in the context of the digital transfor-mation. There are fears that digitalisation will create new cleavages in societies, and there will be gaps in skills needed in digital working life. Older workers and immigrants, in particular, are in a vulnerable position. The theoretical approaches of social investment and combined capabilities stress the needs for upskilling. These are identified to develop digital and non-digital skills to cope with the challenges of the digital transformation. We show that it is not enough to develop indi-vidual capabilities. To really improve inclusiveness, combined capabilities are needed, which take into account institutional arrangements and corresponding public services

Integration of the structural solver B2000++ in a multi-disciplinary process chain for aircraft design

Within the DLR project VicToria (2016 - 2020) multidisciplinary aircraft design process chains were developed to evaluate and optimize transport aircraft under a variety of different aspects such as aerodynamics, structural behaviour, flight control, etc. Aside from the different disciplines the process chains also combine analysis tools on different fidelity levels with the focus on sophisticated CFD and CSM methods based on Finite Element analyses [1]. For the transfer of aircraft parameters between the disciplinary tools a data format called CPACS (Common Parameterized Aircraft Configuration Schema) has been established [2, 3]. In a gradient free optimization process the modelling and sizing of the fuselage structure is performed using the PANDORA (Parametric Numerical Design and Optimization Routines for Aircraft) software framework. The PANDORA development started in 2016 to replace a set of established individual tools for model generation and structural sizing [4, 5] with the objectives to increase flexibility and performance. One major decision was to use the interpreted high level programming language Python and further open source packages such a numpy, pandas, etc. to allow the application on a variety of computer systems from Windows PCs up to computer clusters. In addition, a VTK based graphical user interface has been added to make the model preparation and results evaluation independent from third party commercial software [6,7]. Recently the structural analysis and sizing process has been adapted to integrate the FE Solver B2000++ [8]. This solver was initially developed at SMR in Switzerland and is now available at the DLR including the source code for future developments and direct integration into High-Fidelity process chains. In a first part of the paper recent developments of the PANDORA framework are presented after a brief overview of the MDO process chain and the CPACS data structure. These new developments include improvements in the model generation and the subsequent integration of structural analysis and sizing into the multi-disciplinary process chain. In this process the structural analyses can be performed using the established proprietary structural solvers ANSYS or NASTRAN. The validity of the results is proved by comparison with the previously used tools and the increase of performance is presented. The second part of the paper focusses on the integration of the FE solver B2000++ into the process chain, which shall allow a further reduction of the global process runtime by starting several calculations in parallel without any software license restrictions. A set of benchmark simulations with B2000++ are performed and the results on basic element, coupon and component level compared with those obtained with proprietary solvers. Finally, the integration into the MDO framework and first simulations on full aircraft level are presented. The comparison within the MDO process will include accuracy and performance aspects