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Parametric and neural methods for cost estimation of process vessels

International Journal of Production Economics, ISSN: 0925-5273, Vol: 112, Issue: 2, Page: 934-954
2008
  • 53
    Citations
  • 0
    Usage
  • 120
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    53
    • Citation Indexes
      53
  • Captures
    120

Article Description

In this paper, a comparison is made between artificial neural networks and parametric functions for estimating the manufacturing cost of large-sized and complex-shaped pressure vessels in engineer-to-order manufacturing systems. In the case of large equipment built to customer's design, in fact, it is hard to estimate the production cost owing to the wide variability of vessel's size and configuration and the often scarce previous experience with similar units. However, when cost estimates are to be used for bidding purposes, a poor accuracy may have detrimental financial consequences. A cost overestimation bears the risk of making the firm uncompetitive and losing a customer, while underestimating the cost leads to winning a contract but incurring a financial loss. Furthermore, a precise knowledge of prospective resources utilization is critical for project management purposes when passing to the actual manufacture phase.

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