Cuckoo-Entropy Algorithm Based Quality Function Deployment for Replacement Analysis

The replacement of machinery is one of the major challenges faced by medium scale industries in developing countries like India. The decision of replacement, if initiated, by aspects like lifetime, major repair, breakdown or similar unforeseen problems, is easy for the management but replacement based on product design, competition or competitor machinery upgradation etc lands as a heavy burden for decision makers to act quickly. This research proposes a Quality Function Deployment (QFD) approach for replacement analysis incorporating cuckoo and entropy algorithms. This framework is built on the strong platform of QFD that captures customer voices and transfers it into product features. This framework first establishes the relevance of a product design/development change, which is validated through algorithms to prove the necessity to outrun competitors to stay ahead in the market. The core area of this work is competitor analysis of QFD using algorithms that encapsulates cuckoo algorithm ably supported by entropy equations. The paper concludes with a validation by conventional replacement analysis on a sesame oil mill machine investigating the need of replacing the existing one with a new higher end machine.