A Decision-Support Methodology for Asset Management

2003 ◽  
Author(s):  
E. Lalonde ◽  
C. Bergeron
Keyword(s):  
Decision Support ◽  
Asset Management

A Decision Support Tool for Wastewater Catchment Management

2007 ◽  
Vol 2 (2) ◽  
Author(s):  
S.E. Walters ◽  
D. Savic ◽  
R.J. Hocking
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Capital Investment ◽  
Management Strategies ◽  
Sewage Treatment ◽  
Decision Support Tool ◽  
Catchment Management ◽  
Clean Water ◽  
Support Tool ◽  
South West

The water industry over the years has primarily focussed on upgrading and investing in clean water provision. However, as research into the science and management of clean water services has progressed rapidly, wastewater provision and services has been slower. Focus, though, is now shifting within Industry and Research into wastewater services. The water regulator, Ofwat, for England and Wales demands the Sewerage Undertakers demonstrate efficient management of wastewater systems in order to obtain funding for Capital Investment projects. South West Water, a Water Service Provider and Sewerage Undertaker located in the South West of England, identified a need gap in their asset management strategies for wastewater catchments. This paper will introduce the production of a Decision Support Tool, DST, to help SWW proactively manage their Wastewater Catchments, examining Sewage Treatment Works, Pumping Stations and Networks. The paper will discuss some concepts within the DST, its production, testing and a brief case study. The DST provides a framework for prioritising catchments to optimise investment choices and actions. The Tool ranks catchments utilising Compromise Programming, CP, as well as AHP Pair-wise comparisons for preference weights. The DST incorporates Asset models, a Whole life Costing Module, as well as a Decay and Intervention Module.

Performance Indicators and Multicriteria Decision Support for Sewer Asset Management

2007 ◽  
Vol 13 (2) ◽  
pp. 105-114 ◽  
Author(s):  
Pascal Le Gauffre ◽  
Claude Joannis ◽  
Elisio Vasconcelos ◽  
Denys Breysse ◽  
Claire Gibello ◽  
...  
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Performance Indicators ◽  
Multicriteria Decision ◽  
Multicriteria Decision Support

Knowledge Management for Electric Power Utility Companies

2010 ◽  
pp. 97-122
Author(s):  
Campbell Booth
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Electric Power ◽  
Asset Management ◽  
Effective Practices ◽  
Power Utility ◽  
Utility Company ◽  
Utility Companies ◽  
Power Utilities ◽  
Behavioural Aspects

This chapter will present an overview of the challenges presented to modern power utility companies and how many organizations are facing particularly pressing problems with regards to an ageing workforce and a general shortage of skills; a situation that is anticipated to worsen in the future. It is proposed that knowledge management (KM) and decision support (DS) may contribute to a solution to these challenges. The chapter describes the end-to-end processes associated with KM and DS in a power utility context and attempts to provide guidance on effective practices for each stage of the described processes. An overview of one particular power utility company that has embraced KM is presented, and it is proposed that the function of asset management within power utilities in particular may benefit from KM. The chapter focuses not only on KM techniques and implementation, but, equally, if not more importantly, on the various cultural and behavioural aspects that are critical to the success of any KM/DS initiative.

Asset-management decision-support modeling, using a health and risk model

2015 ◽  
Author(s):  
Mischa Vermeer ◽  
Jos Wetzer ◽  
Peter van der Wielen ◽  
Evert de Haan ◽  
Ebbo de Meulemeester
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Risk Model ◽  
Management Decision ◽  
Management Decision Support

scholarly journals Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

Water ◽  
2017 ◽  
Vol 9 (2) ◽  
pp. 68 ◽  
Author(s):  
Franz Tscheikner-Gratl ◽  
Patrick Egger ◽  
Wolfgang Rauch ◽  
Manfred Kleidorfer
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Economic Value ◽  
Urban Infrastructure ◽  
Water Systems ◽  
Urban Water ◽  
Management Scheme ◽  
Support Methods

The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM) methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE) for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged.

A Multiple Decision Support Metrics Method for Effective Risk-Informed Asset Management

2004 ◽  
Author(s):  
James K. Liming ◽  
James E. Salter
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Probability Distributions ◽  
Heat Rate ◽  
Electric Utility ◽  
Cost Ratio ◽  
Net Benefit ◽  
Utility Company ◽  
Power Stations ◽  
Effective Decision Support

The objective of this paper is to provide electric utilities with a concept for developing and applying effective decision support metrics via integrated risk-informed asset management (RIAM) programs for power stations and generating companies. RIAM is a process by which analysts review historical performance and develop predictive logic models and data analyses to predict critical decision support figures-of-merit (or metrics) for generating station managers and electric utility company executives. These metrics include, but are not limited to, the following: profitability, net benefit, benefit-to-cost ratio, projected return on investment, projected revenue, projected costs, asset value, safety (catastrophic facility damage frequency and consequences, etc.), power production availability (capacity factor, etc.), efficiency (heat rate), and others. RIAM applies probabilistic safety assessment (PSA) techniques and generates predictions probabilistically so that metrics information can be supplied to managers in terms of probability distributions as well as point estimates. This enables the managers to apply the concept of “confidence levels” in their critical decision-making processes.

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