Building Asset Management Research Articles

Towards an Economic Decision Methodology for Remaining Asset Life: Research Roadmap

This report is an output of the fourth research track (Track 4) of WERF's strategic asset management research program Asset Management Communication and Implementation (RFPP #06SAM1CO). Track 4 was developed to address “remaining asset life,” with the overall objective of contributing to the development of techniques, tools, and methods for estimating residual life of wastewater assets. Track 4 research was planned to be undertaken in a staged manner, in order to provide a stepwise development of concepts and protocols. To this end, the research team previously produced a synthesis of knowledge in relation to end of life and remaining asset life. This report builds on this material and presents a roadmap for building asset management capacity through the development of a practitioners guide to economic decision making. This title belongs to WERF Research Report Series . ISBN: 9781780400501 (eBook)

MOST‐FIT: Support Techniques for Inspection and Life Cycle Optimization in Building Asset Management

Abstract: Among the various asset management functions that support capital renewal decisions, both inspection and fund‐allocation are very challenging in terms of time, cost, and technology. To support these functions, this article introduces two unique techniques that can be implemented, individually or combined, into any asset management system: (1) Focused‐Inspection Technique (FIT); and (2) Multiple Optimization and Segmentation Technique (MOST). FIT improves inspection by incorporating an analysis of reactive‐maintenance data to predict components’ conditions, thus saving the time and cost of indiscriminate inspections. The MOST technique, on the other hand, has a unique formulation for large‐scale optimization involving thousands of assets simultaneously, thus maximizes the return of renewal dollars. The article provides a description of the MOST‐FIT techniques and discusses their implementation in a prototype system that suits a large school board in North America. The proposed techniques are innovative and help organizations with large building assets improve the overall condition of their inventory with highest return on the limited renewal budget.

Editorial: integrating “infrastructure project management” with its “built asset management”

PurposeThis paper aims to convey the rationale underpinning this new journal and its timeliness in addressing emerging imperatives in our built environment, to highlight the range of the papers in this first issue and to encourage readers and potential contributors to join theBEPAMjourney, towards improved built infrastructure.Design/methodology/approachDrawing attention to the silos within which “project management” research and practice have been largely isolated from those in “asset management”, recent initiatives to bridge this divide are spotlighted, synerigised and built upon.FindingsA critical need is identified for a niche one‐stop forum to address increasingly important interfaces between project management and asset management of building and civil engineering infrastructure. It is also found to be important to link leading‐edge research to cutting‐edge practice in physical infrastructure development, while empowering and inspiring authors and readers from many relevant disciplines and diverse regions towards synergistic research, development and dissemination.Originality/valueArticulating theBEPAMvision in supplying the missing link between built environment project management and asset management, this paper aims to attract researchers and practitioners from hitherto compartmentalised sub‐sectors to engage with, learn from and improve each other in a common mission to efficiently deliver and sustain better built infrastructure worldwide.

Two condition indicators for building components based on reactive‐maintenance data

PurposeSustaining the safety and operability of the civil infrastructure assets, including buildings, is a complex undertaking that requires a perpetual cycle involving inspection, and further decisions for renewal fund allocation. Inspection, which is the basis for all subsequent decisions, however, is subjective, costly, and time‐consuming. To circumvent inspection problems, this paper aims to develop indicators of the condition of building components, without inspection, using reactive‐maintenance data.Design/methodology/approachFor that purpose, sample reactive‐maintenance data of 88 schools are obtained from the Toronto District School Board in Canada. The data are then analysed to identify two condition indicators for building components: the number of reactive‐maintenance work orders per year; and the cost of reactive‐maintenance work orders per year. The analysis then identifies threshold values that differentiate the good, fair, poor, and critical conditions of components. Accordingly, a condition prediction system has been developed and discussed in this paper.FindingsThe system has great potential benefits in saving the time and cost associated with indiscriminate inspections, and in providing accurate and timely data for asset renewal decisions.Originality/valueThe paper introduces an essential component of a comprehensive framework for building asset management: condition prediction and inspection planning.

Financial management of planned maintenance for housing associations

Since the Housing Act 1988, UK housing associations (HAs) have been responsible, with the removal of government grants, for funding all maintenance necessary for the upkeep of new stock over its lifespan. Sinking funds (SFs) have to be created, out of rental income, that are adequate to finance the long term projected maintenance demand. This paper reviews the use of SFs for building asset management with particular reference to the requirements being made of HAs. Current assumptions of what constitutes an adequate level of SF investment by their funding agencies are questioned with an analysis of case study data. Using linear-programming, the benefits of modelling an SF over merely calculating it are demonstrated. The technique is used to formulate SF strategies, some of which admit the possibility of going into deficit in the future, and these are compared with results from conventional SF projections. Finally, the effect that varying element and component lifespans can have on SF projections are investigated by using Monte Carlo methods to simulate profiles of long term maintenance expenditure, and observing how well funds projected with the original SF strategy match them. The results show the importance of reviewing regularly the SF policy in order that it remains relevant to the needs of the stock.