Abstract :
A “high level”, deductive-reasoning-based (“holistic”), approach is aimed at the direct analysis of the behavior of a system as a whole, rather than with an attempt to understand the system´s behavior by conducting first a “low level”, inductive-reasoning-based, analysis of the behavior and the contributions of the system´s elements. The holistic view on treatment is widely accepted in medical practice, and “holistic health” concept upholds that all the aspects of people´s needs (psychological, physical or social), should be seen as a whole, and that a disease is caused by the combined effect of physical, emotional, spiritual, social and environmental imbalances. Holistic reasoning is applied in our analysis to model the behavior of engineering products (“species”) subjected to various economic, marketing, and reliability “health” factors. Vehicular products (cars, aircraft, boats, etc.), e.g., might be still robust enough, but could be out-of-date, or functionally obsolete, or their further use might be viewed as unjustifiably expensive. High-level-performance functions (HLPF) are the essential feature of the approach. HLPFs are, in effect, “signatures” of the “species” of interest. The HLPFs describe, in a “holistic”, and certainly in a probabilistic, way, numerous complex multi-dependable relations among the representatives of the “species” under consideration. ;umerous inter-related “stresses”, both actual (“physical”) and nonphysical, which affect the probabilistic predictions are inherently being taken into account by the HLPFs. There is no need, and might even be counter-productive, to conduct tedious, time- and labor-consuming experimentations and to invest significant amount of time and resources to accumulate “representative statistics” to predict - he governing probabilistic characteristics of the system behavior, such as, e.g., life expectancy of a particular type of products. “Species” of military aircraft, commercial aircraft and private cars have been chosen in our analysis as illustrations of the fruitfulness of the “holistic” approach. The obtained data show that both commercial “species” exhibit similar “survival dynamics” in compare with those of the military species of aircraft: lifetime distributions were found to be Weibull distributions for all “species” however for commercial vehicles, the shape parameters were a little higher than 2, and scale parameters were 19.8 years (aircraft) and 21.7 (cars) whereas for military aircraft, the shape parameters were much higher and the mean time to failure much longer. The difference between the lifetime characteristics of the “species” can be attributed to the differences in the social, operational, economic and safety-and-reliability requirements and constraints. The obtained information can be used to make tentative predictions for the most likely trends in the given field of vehicular technology. The following major conclusions can be drawn from our analysis: 1) The suggested concept based on the use of HLPFs reflects the current state and the general perceptions in the given field of engineering, including aerospace technologies, and allows for all the inherent and induced factors to be taken into account: any type of failures, usage profiles, economic factors, environmental conditions, etc. The concept requires only very general input data for the entire population. There is no need for the less available information about individual articles. 2) Failure modes are not restricted to the physical type of failures and include economic, cultural or social effects. All possible causes, which might lead to making a decision to terminate the use of a particular type
