The rise of Industry 4.0 has brought about a new wave of digitalized manufacturing. Connected technologies now form the Smart factory, having the ability to transmit data to help with process analysis and control during the production process.
Sensors and microchips are added to machines, tools and even to the products themselves. This means that 'smart' products made in the Industry 4.0 factory can transmit status reports throughout their journey, from raw material to finished product.
Increased data availability throughout the manufacturing process means greater flexibility and responsiveness, making the move towards smaller batch sizes and make-to-order possible.
In order to capitalize on this adaptivity, an Industry 4.0 scheduling system needs to:
With IoT devices, big data and cloud computing as features of Industry 4.0, the scheduling system needs more than ever to bridge the gap between the physical and digital worlds.
Traditionally, there are three approaches to scheduling: manual, constraint-based and simulation.
Manual scheduling becomes an impossibility in such a highly dynamic production environment, due to the sheer volume and complexity of data.
Constraint-based scheduling involves the solution of equations that are formulated to represent all of the system constraints. A mathematical model could be built of all the elements of a Smart factory, however, it would be highly complicated to populate and solve, probably taking a long time to do so. Key aspects would have to be ignored or simplified to allow for a solution which, when found, would be difficult to interpret, visualize and implement.
Simulation-based scheduling stands out as the best solution for Industry 4.0 applications. Each element of the system can be modeled and data assigned to it. The resources, in terms of equipment, tools and workers, can be represented, as well as the materials consumed and produced in the process.
In this way, the flow of jobs through the system can be simulated, showing exact resource & material usage at each stage for real-time status updates.
Decision logic can be embedded in the model, for example to select minimum changeover times, as well as custom rules added from worker experience. These equations combine to produce a range of rules that accurately model the actual flow of materials and components through the system.
This means that simulation-based scheduling software can perform calculations and permutations on all aspects of the production process. This ability, combined with the large volume of real-time data provided by the digitalized workstations, means that scheduling is fast, detailed and accurate.
Thus the three main requirements for scheduling in Smart factories are satisfied by simulation-based scheduling software: