Flow Shop Scheduling Problems in Industry 4.0 Production Environments: Missing Operation Case

ROSSIT, DIEGO GABRIEL; TONCOVICH, ADRIÁN; ROSSIT, DANIEL ALEJANDRO; NESMACHNOW, SERGIO

Handbook of Smart Materials, Technologies, and Devices

Springer

Año: 2021; p. 1 - 23

The Fourth Industrial Revolution or Industry 4.0 is forcing a completely reorganization of the manufacturing systems in order to implement increasingly automatized processes and customized products. Within this context, advanced computer-aid tools can contribute to give support to decision-makers in this increasingly complex conditions. As a contribution to this process, this chapter addresses an optimization problem that has become progressively common within the Industry 4.0 context: the missing operations flow shop scheduling problem. Conversely, to the traditional flow shop, this problem considers the customization of the final products based on the requirements of the clients. Thus, several operations of the manufacturing cell can be skipped. Moreover, the missing operations can vary from one client to another, increasing the difficulty of the decision-making process. In this chapter we revise the missing operations flow shop scheduling problem under two of the main paradigms of the scheduling literature: considering only permutative schedules, i.e., the same job sequence is used for all the machines involved, and the more computationally expensive case of allowing the optimization problem to consider non-permutative schedules, i.e., different job schedules can be used for different machines in the production line. For these two cases, mathematical formulations that aim at minimizing total tardiness are presented. Furthermore, a two-echelon resolution approach is discussed. This involves firstly a Genetic Algorithm (GA), which only considers permutative schedules, and secondly, a Simulated Annealing algorithm, which taking as an input the solution of the GA it expands the search space by considering non-permutative schedules. Computer experimentation was performed on a set of instances with different proportions of missing operations in order to represent a large variety of the situations that occur in practice at real-world manufacturing cells.