Training

The digitalisation of the working world leads to the need and at the same time to the possibility of qualifying employees in a context-oriented, individual and process-oriented way. The challenge in this context is the target-oriented and coordinated use of different learning forms and systems. The present contribution provides an approach for combining content-related and structural gamification in e-learning and the increase of motivation for e-learning as well as knowledge consolidation through mobile learning by means of a game application tailored to the sector of application. To this end, the need to adapt education to digital change is described at the beginning, the pillars of the envisaged concept (gamification, e-learning and mobile learning) are classified, an implementation of the application case of the maintenance of wind turbines is delivered and, finally, the results of the evaluation as well as the added value of this contribution are discussed.

An ageing workforce is a central entrepreneurial challenge. One solution is vocational training. For older workers it is associated with problems. The contribution addresses these problems and the increasing amount of mobile industrial Internet of Things Technology (IIoT) within work processes. The aim is to identify solutions for age-appropriate vocational training by work-related learning.

Many companies face the challenge of training their employees to handle increasingly complex products and to execute complex processes. In the course of globalization, this is no longer just classically interdisciplinary, but also multicultural and multilingual. In addition, the same level of knowledge often needs to be built up and maintained at production sites around the world. In this context, the question arises if traditional training in the form of external human-to-human training will meet the requirements of today’s qualification or whether digitization itself offers opportunities to make training more effective and efficient. An innovative approach, which is presented in the article and is currently being developed by DECURA Consulting GmbH is the combination of virtual reality (VR) and photogrammetry in combination with gamification elements.

The digital interactions along the value chain pose new challenges for managing information and knowledge. The objectives of this article are to describe the changes in knowledge-based value creation induced by digitalisation and to derive fields of action for knowledge management for Industry 4.0. The “knowledge ladder 4.0” shows how digital technologies can transform strategic and operative knowledge management. Subsequently, we offer a framework for the knowledge-oriented design of dynamic digital organisations that consists of three layers of activities for the operation, reflection and design of knowledge management illustrated with leading questions and case examples in order to promote the productive, responsible and sustainable usage of digital technologies.

Companies are increasingly acquiring new technologies that enable higher quality and efficiency. Every technology adoption is also a change process which affects the employees and their work and thus needs to be managed in an optimal way. This article is focused on the importance of goal definition during a change process. To facilitate this process, a checklist with 81 goals is presented. The checklist was developed based on scientific literature and practice-oriented tools and can be used by project teams to focus their activities on a holistic change process and track the goal progress.

Industrie 4.0 with the digitisation of products and processes offers companies a large pool of information for process optimization. In many cases these information cannot be used directly in the textile industry, as raw materials are subject to natural fluctuations and the influencing factors and interactions of many product and process parameters are only partially known. In this contribution, an approach is presented that combines information from production with the experience of the employees and thus supports product and process optimization. The approach is based on the machine learning method “Case-Based Reasoning”.