Utilization of synthetic system intelligence as a new industrial asset

System knowledge and reasoning mechanisms are essential means for intellectualization of cyber-physical systems (CPSs). As enablers of system intelligence, they make such systems able to solve application problems and to maintain their efficient operation. Normally, system intelligence has a human-created initial part and a system-produced (extending) part, called synthetic system intelligence (SSI). This position paper claims that SSI can be converted to a new industrial asset and utilized as such. Unfortunately, no overall theory of SSI exists and its conceptual framework, management strategy, and computational methodologies are still in a premature stage. This is the main reason why no significant progress has been achieved in this field, contrary to the latent potentials. This paper intends to contribute to: (i) understanding the nature and fundamentals of SSI, (ii) systematizing the elicitation and transfer of SSI, (iii) exploration of analogical approaches to utilization of SSI, and (iv) road-mapping and scenario development for the exploitation of SSI as an industrial asset. First, the state of the art is surveyed and the major findings are presented. Then, four families of analogical approaches to SSI transfer are analyzed. These are: (i) knowledge transfer based on repositories, (ii) transfer among agents, (iii) transfer of learning resources, and (iv) transfer by emerging approaches. A procedural framework is proposed that identifies the generic functionalities needed for a quasi-autonomous handling of SSI as an industrial asset. The last section casts light on some important open issues and necessary follow-up research and development activities.