Replacement optimization of industrial components subject to technological obsolescence using artificial intelligence

Abstract

Nowadays, rapid technological change influences the dependability of industrial components by the phenomenon of “obsolescence.” The technological obsolescence of a unit is characterized by the existence of a new-generation unit possessing identical functionalities, but with improved performances. The industrial firms seek to optimally replace the old-generation units by maximizing the number of replaced items, in order to deal with obsolescence of the plant. This paper presents the applicability of a flexible model for thirty components, using a modern bio-inspired and evolutionary computational algorithm called “Cuckoo Optimization Algorithm (COA).”