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Musculoskeletal disorders are the major cause of incapacity to work in the production industry in Germany. Accordingly, ergonomic work processes are particularly important in order to protect the health of employees and to reduce the high follow-up costs for companies and society. This article presents an approach that assesses and analyzes the individual worker capabilities and individual strain at the workplace with the help of modern motion capture systems. A learning assistance system uses the analysis results for ergonomic behavioral prevention in production.

An important element for companies to deal with the demands of the world of work is the continuous and needs-specific further training of employees. The possibility of learning close to the workplace has a major role to play here.

The ongoing digital transformation is changing work and production environments of companies. In addition, a demand-oriented development and efficient use of employee skills are becoming ever more important for success. Thus, there is a need for new decentralized and situationally adaptable solutions that enable self-organized learning paths and informal competence development. This paper presents challenges of collaborative competence development and solutions for IT-supported self-organized learning paths at different organizational levels and shows project examples from the textile industry.

Automatization and Digitalization are keywords regarding innovative assembly of Smart Factories. Despite all, no Smart Factory is able to produce completely without blue color workers. To stay competitive in the global world companies they need to find the balance to hire only as less employees as possible to guarantee all assembly processes. Therefore, Labor Efficiency is the key figure to control attendance and output. This article explains the role of labor efficiency with regards to the Smart Factory. For this purpose, the input factors attendance and output are explained and illustrated by practical examples. Moreover, it explains how labor efficiency can influence competitiveness positively.

The authors present a methodological approach for designing assistance systems conducive to learning and derive requirements for their design. They base the design of these systems on a fundamental understanding of the cooperation between humans and machines, which still places decisions and responsibility with humans. Finally, the authors show concrete requirements and measures of a participatory design and implementation process.

Assistance systems are being used increasingly in the context of digital transformation. They can support employees in industrial production processes both in the learning phase and in the active work phase. In this way, competencies can be built up in a way that is close to the workplace and the process as well as demand-oriented. This paper discusses the current state of research on the possible applications of these assistance systems and illustrates them with examples. Among other things, the current challenges are also highlighted. At the end of the paper, focal points for the future development of AI in industrial learning processes and research on this are identified.

Employees, machines and products get connected: the 4th Industrial Revolution has begun [1]. This is a central statement on the homepage of the German „Plattform Industrie 4.0“. Meanwhile the basic ideas started to move from the shopfloor level to the level of business processes and business models. In consequence it was detected pretty early, that digitization will affect the employees and their qualification and tasks in the companies; the term Work 4.0 evolved. The following contribution emphasizes the systematization of qualifications. A new model will be displayed, that helps to bring transparency to the distribution of qualification in companies. The useability of the model is verified in two case studies. The model is a practicable instrument for companies to gain a realistic view to the upcoming challenges of the shift of qualification due to digitization.

This paper focuses on the investigation of current technical challenges in the context of industrial Virtual Reality (VR)-based training applications. This paper analyzes the current state of the art of industrial VR applications and provides a structured overview of the existing technical challenges. The identified challenges are discussed based on an industrial training scenario for the safe handling of electrical components.

The use of LNG propulsion in ships has significant environmental benefits but also creates chal- lenges in handling. Due to safety regulations, the maintenance of the LNG ship systems requires a high degree of reliability and accuracy. Thus, this paper deals with the development and evaluation of an AR-assistance system. The system based on an Android smartphone enables users to access maintenance instructions and manuals and supports the work process step by step through context-sensitive virtualizations. Its evaluation was conducted as a combined quantitative and qualitative user study.

Urban logistics has to change to become more silent and eco-friendlier. Off-peak delivery is regarded as an effective measure to cut carbon emissions. Implementing this concept will require the deployment of electric trucks to comply with noise regulations. This article provides an overview of current research themes in this field and uses McKinnon’s “Analytical framework for green logistics”to illustrate off-peak delivery as a concept, its benefits and limitations as well as the key requirements to make this concept work.