The Rαβγ categorisation framework for dexterous robotic manufacturing processes

Abstract

Dexterous robotics systems integrate advanced manipulation and perception capabilities, facilitating advanced process automation. However, the inherent complexities of such processes may induce vulnerabilities, impeding overall performance. A parsimonious categorisation of dexterous robotic processes can disambiguate process attributes and highlight intricacies. Existing robotic categorisations focusing on a single attribute (e.g. manipulator structure) lack a processes view. Existing production process categorisations lack valuation of robotic characteristics. The current work suggests Rαβγ, a holistic categorisation of dexterous robotic processes. Rαβγ integrates robotic concepts within the classical [α|β|γ] production process categorisation and is similarly divided into tiers: Workcell, Task, and Objective. Each tier is defined by qualitative descriptors and quantitative characteristics. The intricacies of each characteristic were quantified by an analytic hierarchical process (AHP), semi-structured interviews with robotic experts were conducted for validation, and utility is demonstrated by three case studies. The AHP results are consistent and interpretable. The interviewees determined that Rαβγ is valuable and comprehensive. The case studies demonstrate the categorisation’s ability to highlight major process attributes. The analysis asserts that Rαβγ can be valuable during different product life cycle phases, e.g. designing, commissioning, etc. Rαβγ uniquely integrates the manufacturing and robotic domains, offering a holistic mechanism for highlighting characteristics of dexterous robotic processes.