Identification and health-aware economic control of production systems: A fuzzy logic max plus algebraic approach

The first objective of this paper is to settle the practical problem pertaining to the modelling and identification of the production system performance, which is defined a discrete event one. For that purpose the Internet of Things tools are employed, which are located at each manufacturing machine. As a result, a set of time-driven data is obtained, which measure the metal processing time of the shot blasting machines. These result constitute the base for the development of the state-space model designed with fuzzy logic and max-plus algebraic paradigms. The appealing property of the processing time model is that it is designed with the experimental design strategy, and hence, a minimum number of metal plates is required for its design. It should be noted that the system considered contains concurrent machines, which are redundant, and hence, cause the need for appropriate scheduling and control. Apart from that the system has an associated economic and health-aware indicators, which express the cost of possible degradation of using them over a specified time horizon. Thus, the proposed strategy allows finding a trade-off between general performance of the entire system and these indicators. The proposed strategy is illustrated with a practical proof-of-concept production system, which clearly exhibits the benefits concerning the application of the proposed approach.

Automated summary

The first objective of this paper is to solve the practical problem of modeling and identifying the performance of a discrete event production system. Internet of Things tools are used to obtain time-driven data on the metal processing time of shot blasting machines, which are used to develop a state-space model using fuzzy logic and max-plus algebraic paradigms. The proposed strategy allows for a trade-off between overall system performance and economic and health-aware indicators. A practical proof-of-concept production system is used to illustrate the benefits of the proposed approach.