Technologie: Training

The digital transformation, especially the shift of maintenance to smart maintenance, contains a number of challenges. The management of data plays a significant role in this [1]. The use of sensor technology and devices for mobile data acquisition offers a variety of possibilities for quickly capturing large amounts of data, even in real time. In this context, however, there is also a need for tools that enable efficient data exchange and, at the same time, structured storage of large amounts of data. One of these tools is the digital lifecycle record, which has enormous potential for data-driven services thanks to its special features.

The employee remains a key productivity element in industrial assembly. Assembly assistance systems have therefore become an integral part of employee support. This paper presents a novel assistance system that complements process-related assistance with human-centered functionalities. In addition, an approach for the systematic evaluation of assembly assistance systems is presented in this paper. The research is based on an evaluation of the current state of the art through systematic market analysis of available assembly assistance systems.

German industrial companies are suffering from an increasing shortage of skilled workers. In order to secure Germany’s existing competitive advantages, suitable solutions have to be carried out to counter this shortage. Technologies in the context of “Industry 4.0” offer promising solutions. Using this technologies, significant productivity improvements as well as higher resource utilization rates can be achieved. However, the main challenge is to identify the right technical solutions for the specific business challenges. In the following, a systematic approach is presented to face these challenges.

The paper reflects the potential and remaining shortcomings of AI-based work systems for exploiting and enhancing individual and organizational learning processes. It especially refers to the use adaptive systems in production and gives examples of good practice for the design of AI-based work systems which promote the interplay between individual and artificial intelligence. The conceptual framework refers to different methods in machine learning which are complemented by insights from individual and organizational learning theory.

Due to increasingly specialised, diverse and also new competencies and competency profiles it becomes progressively more difficult to interpret educational achievements and to match requirement profiles with the competencies of individual persons or groups. The computational support with regards to keeping the information up to date, communication, search and analysis is limited if the competencies are described in natural language only. Thus, it seems advantageous to model competencies in a formal and machine-readable specification language. The following article suggests the notion of a generic formal syntax for learning outcomes. We outline how this would allow expressing intricate learning outcomes in a machine-readable ontology and their further processing with the Linked Data- and Semantic Web-approaches.

In manual assembly, assistance systems are applied for the informational and physical support of employees. So far, assistance mainly focuses on some process-related aspects of assembly processes, while system acceptance, motivational perspectives are not considered. This article presents the gamification approach as a possibility to support the motivation of the workers. To facilitate a successful implementation of gamification, this paper presents a structured and method-based selection approach for game design elements.

The paper describes a modular, AR-based assistance system that guides the user through a maintenance task by displaying components and meta-information step by step. By supplementing a learning success control, the system can also be used for continuing education of service technicians and operating personnel. Special emphasis was placed on an integrated information system that allows maintenance information and training tasks to be created with little effort and at the same learning and work tasks to be teached on the systems used in practice.