Reliable Autonomous Production Systems: Combining Industrial Engineering Methods and Situation Awareness Modelling in Critical Realist Design of Autonomous Production Systems

Autonomous production needs to be reliable. Outputs from reliable production systems consistently conform to performance requirements. By contrast, outputs from unreliable production systems often do not conform to performance requirements. Unreliable production can lead to accidents, rework, scrap, loss of good will, etc. In this communication paper, comparative analyses are provided of work characteristics in the manufacturing and construction industries, which affect opportunities for reliable high-level autonomous production systems. Analyses indicate that there are strong opportunities and weak opportunities for reliable high-level autonomous production systems in these industries. In the strongest opportunities, there is repeated work certainty; the composition of work involves few materials/parts that have little variation; and work is carried out in settings that require no additional engineering to facilitate reliable autonomous production. In the weakest opportunities, work settings require extensive additional engineering; the composition of work involves many materials/parts that have lots of variation; the work to be done is not certain until completion and then it is never repeated. It is explained that when seeking to improve weak opportunities for reliable high-level autonomous production systems, industrial engineering methods and situation awareness modelling can be combined within a critical realist framework in order to address challenges in work setting, composition and uncertainty.