Cognitive engine for augmented human decision-making in manufacturing process control

A pre-planned production workflow may need to adapt to instantaneous states of resources, materials, and workpieces. This adaptation poses an additional challenge when multiple custom workpieces are enmeshed in complex processes. This paper presents a novel framework, Cognitive Engine Process Controller (CEPC), which realizes a human-centric manufacturing system by augmenting the human in workflow selection and providing the flexibility in using alternative methods in the workflow. The CEPC streamlines overwhelming information for the human to select the next manufacturing steps via dynamic web ontology language (OWL) ontologies, a conflict checker, and a learner. The CEPC can monitor the completion of each step, determine the effect of a failed step, and suggest a set of suitable steps. Simulation results showed the potential of the CEPC via demonstrations. The CEPC has also been compared with an existing cognitive engine framework for workflow planning.