Abstract:

One of the most complex domains in the field of industrial process planning that a professional can face is the job shop. Machines, parts, jobs, routing, orders, batches, machining phases, set-up times, machining times, or delivery times, among others, make up a very unique issue, known as the job shop scheduling problem (JSSP) which, in real environments, acquires a remarkable level of complexity. For a first-time industrial engineering student taking on the challenge of gaining a deeper understanding of the JSSP, theoretical training is essential to establish the basic concepts, but practice can be an eye-opener in terms of grasping the true dynamics of the process, although technological and economic restrictions may put a brake on this endeavour. In this regard, one of the Industry 4.0 enabling technologies that researchers and managers have shown most interest in over the last decade is the digital twin (DT), which allows objects or processes to be virtually replicated to simulate their characteristics and behaviour during the interaction with the surrounding environment. The virtualisation of processes with a high degree of fidelity is not restricted today to the scope of research laboratories or industrial plants, as open source libraries such as SimPy, a process simulation environment based on the Python programming language, facilitate the implementation of DTs, also in educational contexts with limited means, boosting the possibilities of practical laboratory training to a new level that brings it closer, from the perspective of its study, to the experience acquired within real environments. This article proposes the use of a DT programmed in SimPy to carry out simulation practices of the JSSP in two of the subjects of the Master Degree in Industrial Engineering and Logistics (MIEL) currently taught at the Alcoy Campus of the Universitat Politècnica de València: "Quantitative Methods" and "Production Management", so that, on the one hand, students learn to use SimPy as a simulation tool and, on the other hand, they use it to experiment with scheduling priority rules for the allocation of jobs to manufacturing resources. This learning project is based on cooperative learning (CL) and project-based learning (PBL) methodologies and is expected to upgrade student understanding and stimulate their motivation during the learning process.

The contribution of this study is twofold:
1) to bring the DT technology closer to the teaching context; and
2) to provide a reference for the development of teaching materials for subjects related to the JSSP.

Keywords:

Job shop, job scheduling, digital twin, simulation environment, SimPy, project-based learning, cooperative learning, industrial engineering master degree.