PoPCoRN - Plug & Produce with Configurable Resources inspired by Natural language

The vision of PoPCoRN (Plug & Produce with Configurable Resources inspired by Natural language) is to obtain flexible production systems, where the changeover time for new product variants can be measured in minutes rather than months for automated applications.

The expected industrial effect is a more balanced work environment for operators where ergonomically unsustainable tasks can be replaced by automation. Expected outcome from the project is a planning and control software for operator-robot assisted assembly based on the ontology.

The specific research question to be considered in PoPCoRN is; how can ontology and related semantics inspired by natural language, that encompasses Plug & Produce and operator-robot assisted assembly, be formulated to minimize waste time. Swedish industry calls for more flexible and automated production systems to keep cost-efficient manufacturing with high quality within Sweden. PoPCoRN will facilitate the transition into more flexible production systems with rapid reconfiguration abilities.

Artificial Intelligence is a promising technique to handle high flexibility from a control perspective. However, the industrial challenge is to program such an Artificial Intelligence-based controller that serves a Plug & Produce production system. The novelty of PoPCoRN is that it addresses how to configure Plug & Produce controllers based on natural language, implying that programming can be avoided.

PoPCoRN is in line with initiatives such as Industry 4.0, Smart Factories, Cyber Physical Systems, Artificial Intelligence and Digitalisation, which are aiming for a paradigm shift in the abilities and possibilities for production technology. International standards for automation, such as AutomationML, will be evaluated, compared and utilised. PoPCoRN will provide the industrial community with a configuration tool and an industrial method for Plug & Produce aimed for short changeover and rapid reconfiguration.

The research deliveries focus on how to formulate an ontology and related semantics to be used as a configuration for an intelligent online controller.