Artificial neural networks as cost engineering methods in a collaborative manufacturing environment

Wang, Q.

Abstract

To support the complexity of the modern manufacturing environment it is vital that cost modeling under a collaborating network of companies is developed. In this paper a cost model development process is described and a novel cost modeling technology artificial neural networks (ANN) is developed. The ANN have the ability to learn and respond in producing cost estimates for manufacturing processes and also seek to find new patterns within existing cost data for forecasting and ranking which makes intelligent computing a viable option in moving the modeling process forward. A series of experiments were undertaken to select an appropriate network structure for estimating the cost within the production network and the model is validated through a case study. Trial and error cost estimating would possibly be made easier within a linguistic and intuitive framework.

Citation

Wang, Q. (2007). Artificial neural networks as cost engineering methods in a collaborative manufacturing environment. International Journal of Production Economics, 109(1-2), 53-64. https://doi.org/10.1016/j.ijpe.2006.11.006

• Journal Article Type: Article
• Publication Date: 2007
• Deposit Date: Jan 16, 2007
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Electronic ISSN: 1873-7579
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 109
• Issue: 1-2
• Pages: 53-64
• DOI: https://doi.org/10.1016/j.ijpe.2006.11.006
• Keywords: Artificial neural networks, Cost modelling, Design of experiment.
• Public URL: https://durham-repository.worktribe.com/output/1575932