AWARE – Arbeit 4.0: Analysis of Requirements and Support Services for Manufacturing Companies to Support the Digital Transformation
Digitisation involves the implementation of new and innovative technologies in a typical application context. This is accompanied by theorchestrationofthedimensions work, human, and technology in the course of embedding them in existing processes: Arbeit 4.0 is a synonym for the scientific research field of promoting a comprehensive and sustainable nature of holistic work.
In the project “AWARE - Arbeit 4.0” oftheleading-edgecluster“it’sOWL”, the participation of the inIT was aimed, among other things, at pursuing the participatory nature and design of digitised work with a special focus on human-centred work. Due to the involvement in three work packages of the cluster project, the concrete design of human-centred work with the help of assistance systems was considered a topic area in addition to the basic perspective of participatory technology development: The question arose as to how innovative and also integrative forms of cooperation can be established in often classically and conservatively designed structures of consistent process control.
Together with partners from industry, concrete questions from practice were approached with the helpofcreative,agile, and participative instruments. The decisive factor here was that all knowledge carriers necessary for the process under consideration were included on an equal footing: Right from the start, the “common understanding” and the accompanying transparency in dealing with the desired problem solution should be ensured. In addition to recommendations for action or concepts for the industrial companies, this also resulted in a pilot assistance system that demonstrated the use of Augmented Reality (AR) as a potential form of interaction for human-centred assistance.
Particularly in the current situation of “Covid-19”, the question arises as to how forms of work can be designed in an effect-oriented, flexible or ubiquitous way in accordance with digitalisation/automation/individualisation. This is particularly true when dealing with still young and little- established technological disciplines, such as Machine Learning and Artificial Intelligence.