Smart Manufacturing and Industry 4.0 production environments integrate the physical and decisional aspects of manufacturing processes into autonomous and decentralised systems. One of the main aspects in these systems is production planning, in particular scheduling operations on machines. We introduce here a new decision-making schema, Smart Scheduling, intended to yield flexible and efficient production schedules on the fly, taking advantage of the features of these new environments. The ability to face unforeseen and disruptive events is one of the main improvements in our proposed schema, which uses an efficient screening procedure (Tolerance Scheduling) to lessen the need of rescheduling in the face of those events.

The study of scheduling procedures has generated important contributions to the improvement of productivity in different industrial branches. In recent years, the incorporation of high technology to production systems brought the advent of a ‘fourth industrial revolution’, Industry 4.0. One of the mainstays of Industry 4.0 is the application of Cyber-Physical Systems (CPS), which are physical production systems that incorporate sophisticated computational tools. This implies embedding computers, enabling a real-time connection between workstations and Decision Support Systems. It seems natural, in this setting, to associate scheduling schemes to CPS. This allows streamlining the decision-making process, allowing more flexible and lean production lines. We review here the most salient contributions on scheduling in these environments. We distinguish between work on the basic issues of scheduling and that on scheduling as part of higher-level production planning activities. To frame correctly this distinction we analyse how CPS can embody the different levels of the ISA-95 structure and how this relates to the classical structure of production planning. Our review suggests that the real-time availability of information will have a significant impact in this area and that scheduling will be solved in the future in decentralised decision processes.