Total failure of a system due to time-dependent complexity- an identification framework

Abstract Axiomatic Design theory claims for using universal principles that allow classifying a design and choose the best one. Moreover, it helps to anticipate problems in the performance of a system. This design theory develops the design in four design domains and has two axioms: the independence axiom, and the information axiom. The probability of fulfilling the set of functional requirements allows determining the information content of the design, a measure of the complexity of a system. Complexity may change over time, called time-dependent complexity. Time-dependent complexity can be reduced using functional periodicity, a way to periodically reset the system ensuring the functionality of the system at the former design levels. System maintenance provides periodical functionality allowing to reduce the complexity of the system. However, interferences between parts or systems are often not taken into account in the design, making possible the complexity to increase until a total failure of the system. The authors propose to use the Design Structure Matrix, to help to define the changes in the physical domain over time. Thus, computing the distributions of the functional requirements in a fuzzy environment allows calculating the probability of success of a system along the time. It was found possible to compute the time-dependent complexity using ranges of lifetime of compounds and to identify the probable failure of a system by the pick increase of information at a certain time.