Skip to main content
Article
Ontology-Based Knowledge Representation for Obsolescence Forecasting
Journal of Computing and Information Science in Engineering
  • Liyu Zheng, Virginia Polytechnic Institute and State University
  • Raymond Nelson, III, University of Maryland, College Park
  • Peter Sandborn, University of Maryland, College Park
  • Janis P. Terpenny, Iowa State University
Document Type
Article
Disciplines
Publication Version
Published Version
Publication Date
3-1-2013
DOI
10.1115/1.4023003
Abstract

Sustainment refers to all activities necessary to keep an existing system operational, continue to manufacture and field versions of the system that satisfy the original requirements, or manufacture and field revised versions of the system that satisfy evolving requirements [3].

The sales data is mainly in the form of number of units shipped. If it is not available, sales in market dollars or percentage market share may be used, as long as the total market does not increase appreciably over time [6].

For some products, within the same type of the product, life cycle curves characterized by parameters k, μ, and σ can vary with some primary attributes of the product. Examples are memory chips whose life cycle curves vary with different memory sizes. Memory size is the primary attribute describing the memory chip that evolves over time [6-8]. For these products, if the primary attributes of the product are not considered, the parameters k, μ, and σ obtained from the sales data of the product are only average values for that product.

The time range of the zone of obsolescence can be determined using data mining of historical data (e.g., last-order or last-ship dates) to achieve more accurate obsolescence forecasting [8].

Comments

This article is from Journal of Computing and Information Science in Engineering 13 (2012): 014501, doi:10.1115/1.4023003. Posted with permission.

Copyright Owner
American Society of Mechanical Engineers
Language
en
File Format
application/pdf
Citation Information
Liyu Zheng, Raymond Nelson, Peter Sandborn and Janis P. Terpenny. "Ontology-Based Knowledge Representation for Obsolescence Forecasting" Journal of Computing and Information Science in Engineering Vol. 13 Iss. 1 (2013) p. 041501
Available at: http://works.bepress.com/janis_terpenny/2/