ABSTRACT
This article presents a novel comprehensive model about productivity, reliability and safety prediction of a Flexible Manufacturing Cell (FMC), and an innovative and accurate reliability analytical method of machines’ and robots’ failures is also proposed in this model. Probabilistic model checking, an automatic formal verification technique for analyzing quantitative properties of systems which exhibit stochastic behaviors, is applied to the productivity, reliability and safety analysis of different FMCs, by using the probabilistic model checking tool PRISM, manufacturing processes of a FMC example are modeled as Continuous-Time Markov Chains (CTMCs) with a simple and state-based language called PRISM language. In this model, failure rates of equipments are identified as positively related elements to their actual operating time, because the machine or robot processes work-pieces in discrete jobs with different frequencies and cycle time, failures are considered to occur only when they are really “working” (the machine is machining and the robot is loading or unloading a part) in the model. Reliability analysis without consideration of production benefit and maintenance cost is unpractical in manufacturing industry, so the influences of reliability indexes such as Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR) are studied, besides, there is a potential safety risk in this FMC, when the robot drops a part, the operator will be struck by the robot if both the power source and interlock fail during this period, and the probability of the operator being stuck by the robot is calculated as the guide to safety production of this system.
