Statistical Study of Product Obsolescence Detection Techniques
Manasvi Gurnaney
Manasvi Gurnaney, Shri Ramdeobaba College of Engineering and Management, Nagpur (Maharashtra), India.
Manuscript received on 24 March 2019 | Revised Manuscript received on 05 April 2019 | Manuscript Published on 18 April 2019 | PP: 556-558 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03070376S19/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Obsolescence indicates the lifespan for which a product under study will be viable to sustain a particular market condition. This viability depends on the product features, the timing of product launch, the cost of the product and other secondary parameters. Researchers from various fields have proposed algorithms and techniques which utilize the product’s parameters in order to predict and justify the product’s obsolescence in the given market conditions. This study is based on statistically evaluating the product obsolescence detection methods and concluding as to which methods can be used for a particular application. This study also suggests some future research work which can be done on these algorithms in order to enhance the quality of obsolescence detection.
Keywords: Obsolescence, Lifespan, Market, Product, Application.
Scope of the Article: Software Product Lines