Simulation models and mathematical programming techniques can deal with manufacturing systems which call for complex decisions concerning daily issues as well as middle and long horizon strategies (e.g. the introduction of new machines, new products, etc.). Among the most recent computing algorithms, artificial and swarm intelligences have demonstrated their capability of solving scheduling, programming, and maintenance problems in manufacturing complex systems.
The team of Laboratory of “Intelligent Computation for Manufacturing and Manufacturing Systems” have matured a considerable experience in resolving optimization problems for advanced technologies like welding and additive fabrication ones, and modelling the overall manufacturing system. The same approach can be potentially applied to a variety of processes that involve low resources availability and necessity of a high degree of efficiency, like processes in the health care systems.
The team can design a screening experiment and explore the process to be simulated by enquire its actors. The information is structured as an input to the process and several solutions are found by means of commercial software and customer programming. Then, they will discuss until the better solution, if not the best, is selected.
The capability of the team embraces also the use of Statistical Process Control (SPC) with the aid of Design of Experiment technique (DoE).