Abstract:

The article addresses the management of ergonomic interventions in Industry 4.0 during the COVID-19 pandemic. Key tasks in the assembly process are identified through window production analysis. The method of recording human load indicators to manage variables in the assembly process chain is justified. The cognitive goal is to quantify operational and tactical variables affecting worker workload during the pandemic. The practical objective is to assess the relevance of variables for applying artificial neural network methods to support ergonomic interventions in semi- and non-automated assembly processes within Industry 4.0. The study examined 16 variable states such as noise, work pace, forced body position, position of information and control elements of the information system and personal protective equipment. Postural load, heart rate, and NASA-TLX assessments were conducted during bench tests, and pre-test and post-test metrics, including cognitive-motor skills and fatigue, were collected. The results were quantified using a comparative method, with individual scales developed for selected metrics.