Toward smart manufacturing scheduling from an ontological approach of job-shop uncertainty sources

An integral application of the enabling technologies of Industry 4.0 in the job-shop scheduling problem (JSSP) must contemplate the automation and autonomy of the involved decision-making processes as a goal, which is the main purpose of the smart manufacturing scheduling (SMS) paradigm. In a real production context, uncertainty acts as a barrier that hinders this goal being met and, therefore, any SMS model should integrate uncertainty generators in one way or another. This paper proposes an ontological framework that identifies and structures the entities shaping the joint domain formed by the job-shop scheduling process in its itinerary toward the SMS paradigm, the sources of uncertainty that it faces, and the interrelationship type that link these entities. This ontological framework will serve in future research as a conceptual basis to design new quantitative models that, from a holistic perspective, will address the stochasticity of manufacturing environments and incorporate the management of disturbances into the realtime resolution of automatic and autonomous job-shop scheduling.The research leading to these results received funding from grant RTI2018-101344-B-I00 of MCIN/AEI/10.13039/501100011033 and "ERDF A way of making Europe", from the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana entitled "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/2021/065)"