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Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design - Part 17 studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modelling, mathematical algorithmic modelling, evolutionary algorithmic modelling, symbolic logic modelling, artificial intelligence modelling, and object-oriented computer modelling, in a logically structured approach to determining the integrity of engineering design. . | 3.3 Analytic Development of Reliability and Performance in Engineering Design 143 presence of non-linear properties for example in the modelling of performance characteristics of relief valves non-return valves end stops etc. . Secondly the solutions may be very specific. They are typically produced for a system at a certain pressure flow load condition etc. In engineering design and in particular in the FMEA it is common not to know the precise values of quantities especially in the early design stages. It would thus be more intuitive to be able to relate design criteria in terms of ranges of values as considered in the labelled interval calculus method for system performance measures. b Order of Magnitude The problem of how to address complicated failure modes can be approached through order of magnitude reasoning developed by Raiman 1986 and extended by Mavrovouniotis and Stephanopoulis Mavrovouniotis et al. 1988 . Order of magnitude is primarily concerned with considering the relative sizes of quantities. A variable in this formalism refers to a specific physical quantity with known dimensions but unknown numerical values. The fundamental concept is that of a link the ratio of two quantities only one of which can be a landmark. Such a landmark is a variable with known and constant sign and value. There are seven possible primitive relations between these two quantities A B A is much smaller than B A B A is moderately smaller than B A -- B A is slightly smaller than B A B A is exactly equal to B A -- B A is slightly larger than B A B A is moderately larger than B A B A is much larger than B. The formalism itself involves representing these primitives as real intervals centred around unity which represents exact equality . They allow the data to be represented either in terms of a precise value or in terms of intervals depending upon the information available and the problem to be solved. Hence the algorithmic model will encapsulate all the known features of the