Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An Industrial Knowledge Graph- and Graph Embedding-Enabled Pathway

Based on advanced information and communication infrastructures and enabled with the cutting-edge information processing of cognitive computing, existing smart manufacturing systems have foreseen a prevailing tendency that approaches a higher automation level, i.e., Self-X (e.g., Self-configuration/optimization/adaptation). However, the readiness of ‘Self-X’ levels is still far to reach, encountering the practical challenges of semantics-based networking and human-machine untrust in the manufacturing scenario. To mind these gaps, the authors envision an industrial knowledge graph (IKG) and graph embedding (GE) enabled pathway, to flourish today’s smart manufacturing paradigms towards cognitive mass personalization. To pave it, three promising IKG and GE enabling techniques in the ‘Self-X’ cognitive manufacturing network are described. Potential opportunities and challenges are also pointed out to invite more opinions to refine and innovate the exploitation of IKG and GE for the future of smart manufacturing.