Search Results

Although increased machine automation is crucial for higher productivity, it also leads to higher susceptibility of component failures. Such failures may be caused by a variety of issues. This paper focuses on a technique that can be embedded in the software module that the particular component is interfaced with, to arrive at more specific information for determination of unanticipated usage modes causing component fatigue and consequent failure. Thus this may be used to guide component redesign if warranted. The paper proposes the use of finite state machines (FSMs) to implement software used to read the components. The FSM method used as a software architectural construct in conjunction with Markov chains can determine the limiting state distribution as a probability vector. This gives the maximum proportion of time the failed component would end up being in a particular state, along with information about source state and destination state from the Markov transition matrix.