عنوان مقاله [English]
The process of development and expansion of advanced industries with abundant industrial production in the current era reveals the necessity of the implementation of preventive methods in dealing with possible failures. This
necessity becomes more evident in industries whose real value of produce encompasses a large volume of potential assets (e.g. the munitions industry). Reliability is one of the most important qualitative characteristics of
components, products, and large, complex systems that play a crucial role in the performance of such equipment.
Modern engineered products, from each component to large systems, must be designed and produced in such a way as to have the necessary reliability. In every industry, especially the aerospace industry, it would be dangerous and
harmful from different economic, human, and political aspects when a system fails or becomes dysfunctional. The current trends in various industries indicate that establishing a system capable of quickly referring the failure
rate of a product, or estimating its reliability, is a requirement for each industry. The reliability of a system is the probability that the system will perform a given task under certain conditions and at certain time intervals.
According to this definition, it is obvious that reliability indicates the continuation of functionality without failure (e.g. in accomplishing a mission). Therefore, reliability is defined as the probability that a system or component remain functional without failure. Reliability is of crucial importance in the arms industry. One of the products of the arms industry is the anti-aircraft missile, which is used against enemy threats. If such a product is functional or becomes functional late, there will be irreparable damage, which itself adds to the importance of the product.
In this study, first FFBD and FBD are used in order to calculate reliability and improve the functionality of munitions and weapon systems. Then, higher levels of FTA are identified using a FBD. After that, RBD is prepared, and
reliability is estimated using the Fuzzy-Bayesian technique. Finally, design errors are identified and improved using a Fuzzy FMEA.
MODELING OF MULTI-RESPONSE PROBLEMS WITH NON-DETERMINISTIC NON-NORMAL
DISTRIBUTED RESPONSES USING GENETIC PROGRAMMING}
Dept. of Industrial Engineering
Design of experiments, multi response variables, non-deterministic residuals
distribution, genetic programming, genetic algorithm.}