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A Statistical Activity Cost Analysis of the Relationship Between Physical and Financial Aspects of Fixed Assets

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Engineering Asset Management
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Abstract

In this paper, Statistical Activity Cost Analysis (SACA) is used to identify the interaction of mutually dependent physical and financial aspects of a fixed asset-like system configuration. The novelty of the approach is, having established a rational description of the uncertainty inherent in both domains, the analysis of their interaction. Little research to date has investigated the duality of engineering and accounting aspects, in a statistical setting. Our approach is conceptual rather than empirical. We use an illustrative 4-component model, a) to explain the concept of SACA by means of a software demonstration tool, b) to relate financial issues of cost to engineering asset capacity to perform specified tasks, and c) to demonstrate how to produce quantified measures of return and risk, both of which are relevant in areas of life-cycle analysis, budgeting and planning decision-making.

This work is sponsored by the Australian DSTO (Defence Science and Technology Organisation) through the Australian CRC for Integrated Engineering Asset Management as Projects MD101 and MD105.

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4 Bibliography

  1. Bergerson, J. A., & Lave, L. B.; 2005; “Should We Transport Coal, Gas, or Electricity: Cost, Efficiency, and Environmental Implications” Environmental Science & Technology; 39,16, 5905

    Article  Google Scholar 

  2. Davis, D. J.; 1952; “An Analysis of Some Failure Data” Journal of the American Statistical Association; 47,258, 113–150

    Article  Google Scholar 

  3. Dogramaci, A., & Fraiman, N. M.; 2004; “Replacement Decisions with Maintenance Under Uncertainty: an Imbedded Optimal Control Model” Operations Research; 52,5, 785

    Article  MathSciNet  MATH  Google Scholar 

  4. Engelhardt, M. O., Skipworth, P. J., Savic, D. A., Saul, A. J., & Walters, G. A.; 2000; “Rehabilitation Strategies for Water Distribution Networks: a Literature Review with a UK Perspective” Urban Water; 2, 153–170

    Article  Google Scholar 

  5. Falta, M.; 2005; “Statistical and Computational Methods to Assess Uncertainty and Risk in Accounting” http://adt.caul.edu.au

    Google Scholar 

  6. Falta, M., & Wolff, R.; 2004; “Recent Developments of Statistical Approaches in Aspects of Accounting: a Review” International Statistical Review; 72,3, 377–396

    Article  Google Scholar 

  7. Gibbins, M., & Willett, R. J.; 1997; “New Light on Accrual, Aggregation and Allocation, Using an Axiomatic Analysis of Accounting Numbers’ Fundamental and Statistical Character” ABACUS; 33,2; 137–167

    Article  Google Scholar 

  8. Hsieh, C. C.; 2005; “Replacement and Standby Redundancy Policies in a Deteriorating System with Aging and Random Shocks” Computers & Operations Research; 32,9, 2297

    Article  MATH  Google Scholar 

  9. Jiang, R., Zhang, W. J., & Ji, P.; 2003; “Required Characteristics of Statistical Distribution Models for Life Cycle Cost Estimation” Int. J. Production Economics; 83, 185–194

    Article  Google Scholar 

  10. Kumar, U. D., Crocker, J., Knezevic, J., & El-Haram, M.; 2000; “Reliability, Maintenance and Logistic Support: A Life Cycle Approach” Kluwer Academic Publishers

    Google Scholar 

  11. Lamson, S. T., Hastings, N. A. J., & Willis, R. J.; 1983; “Minimum Cost Maintenance in Heavy Haul Rail Track” The Journal of the Operational Research Society; 34,3, 211

    Article  Google Scholar 

  12. Monga, A., & Zuo, M. J.; 2001; “Optimal Design of Series-Parallel Systems Considering Maintenance and Salvage Value” Computers & Industrial Engineering; 40, 323–337

    Article  Google Scholar 

  13. Pham, H.; 2003; “Software Reliability and Cost Models: Perspectives, Comparisons, and Practice” European. Journal of Operational Research; 149,3, 475

    Article  MATH  MathSciNet  Google Scholar 

  14. Vaurio, J. K.; 1995; “Optimization of Test and Maintenance Intervals Based on Risk and Cost” Reliability. Engineering and System Safety; 49,23

    Google Scholar 

  15. Willett, R. J.; 1987; “An Axiomatic Theory of Accounting Measurement” Accounting and Business Research; 155–171

    Google Scholar 

  16. Willett, R. J.; 1988; “An Axiomatic Theory of Accounting Measurement-Part II” Accounting and Business. Research; 19,73; 79–91

    Google Scholar 

  17. Willett, R. J.; 1991; “Transaction Theory, Stochastic Processes and Derived Accounting Measurement” ABACUS; 27, No. 2; 117–134

    Article  Google Scholar 

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Correspondence to M. Falta .

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Joseph Mathew Jim Kennedy Lin Ma Andy Tan Deryk Anderson

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© 2006 CIEAM/MESA

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Colin, A., Falta, M., Su, S., Turner, L., Willett, R., Wolff, R. (2006). A Statistical Activity Cost Analysis of the Relationship Between Physical and Financial Aspects of Fixed Assets. In: Mathew, J., Kennedy, J., Ma, L., Tan, A., Anderson, D. (eds) Engineering Asset Management. Springer, London. https://doi.org/10.1007/978-1-84628-814-2_43

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  • DOI: https://doi.org/10.1007/978-1-84628-814-2_43

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-583-7

  • Online ISBN: 978-1-84628-814-2

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