Concept development and implementation of a trend-based work analysis using digital tools and studies to identify load peaks

Abstract

As part of the “Perspectives on labour research Lusatia” (PAL) project, five chairs at Zwickau University of Applied Sciences are working with industrial partners to develop low-threshold methods and tools for simplified screening of work characteristics. Traditionally, the assessment of work systems requires extensive specialist knowledge in the areas of occupational safety, ergonomics and operational design. Creating a hazard and stress register as a basis for work system design is therefore time-consuming and most of the times cost-intensive, which leads to a wait-and-see attitude, especially among small and medium-sized companies. However, innovations in the field of work analysis are now enabling the use and integration of smart, digital assistance systems, such as smartwatches or fitness trackers, combined with portable, intelligent environmental measurement technology. This combination allows an autonomous, in-house assessment of the stresses occurring without the need for external specialists and expensive equipment. The protection of personal rights is guaranteed by anonymized and pseudonymized data transmission. The departmental or process-specific evaluation of the collected data using machine learning creates an indicative stress assessment that enables work to be organized in line with all requirements. The resulting rough classification of key areas for action serves to define priorities for action and supports targeted decision-making processes for further measures, in which experts are involved on a selective basis. As a result, companies can carry out a focus-oriented and therefore economically sensible optimization of work design. Of particular importance, however, are the expected positive effects on employees, such as increasing motivation as well as higher job satisfaction.

Keywords: Work Analysis, Digital Assistance System, Occupational Safety, Health Management, Stress Examination, Digital Competence, Digital Stress

DOI: 10.54941/ahfe1005370