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Innovations in infrastructure asset management: the need for business process re-engineering
Vanier, D. J.; Lacasse, M. A.; Danylo, N.
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Innovations in Infrastructure Asset Management:
The Need for Business Process Re-engineering
By
D.J. Vanier1, M.A. Lacasse2 and N.H. Danylo3
Abstract
RÉSUMÉThe paper describes the immediate need for business process re-engineering related to infrastructure asset management. The paper uses the “Municipal Infrastructure
Investment Planning” (MIIP) project to describe potential opportunities to improve the efficiency of maintaining constructed assets. The MIIP is a research project employing the following enabling technologies: maintenance management, life cycle economics, service life prediction, user requirement modeling, risk analysis and product modeling. The project focuses on a proactive approach to maintenance, repair and renewal of municipal infrastructure assets. In each of these enabling technologies, there are
opportunities for business process re-engineering. The authors discuss other technologies available today to assist infrastructure asset managers, including innovative techniques and information technology tools. Techniques such as capital renewal/deferred
maintenance planning, engineered management systems, level of investment studies and condition assessment surveys are described, as are tools such as computerized
maintenance management systems, CD-ROM, the Internet, computer aided facilities management and mobile computing.
1. Dr. Dana J. Vanier is a Senior Research Officer at the National Research Council Canada whose current activities relate to service life prediction and asset management. In the past, he specialized in the application of information technology to construction domains such as standards processing. 2. Dr. Michael A. Lacasse is a building science engineer and Associate Research Officer at the National
Research Council Canada specializing in jointing systems for building facades and the service life of related components. He is also the convenor of CIB W80/RILEM-SLM dealing with the prediction of service life of building materials
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Introduction
Managers of mixed urban infrastructure assets such as federal departments, state or provincial governments, municipalities and universities have to manage a diversified set of built assets, from complex underground networks (e.g. water distribution, sewers) to buildings, as well as roadway systems, parks and any other equipment necessary to maintain all these infrastructures. These built assets, however, are not protected from deterioration due to age, climate, geological conditions, and changes in use. Furthermore, and in particular, because of a lack of adequate funding and appropriate support technologies, certain components of the urban infrastructure have been neglected and receive only remedial treatments.
Consequently, these built assets will not last their originally predicted service life unless there are major maintenance and rehabilitation investments. Indeed, even if Canadian cities, for example, spent between $12 and $15 billion every year on maintaining and rehabilitating their infrastructure (bridges, streets, water systems, sewers, tunnels, and sidewalks), there is an accumulated shortfall estimated in 1996 at $44 billion to return these assets to an acceptable condition.
Added to the physical deterioration of an organization’s built assets is the associated financial situation faced by many: reductions in revenues caused by urban sprawl and relocation of industries to suburbs, and the ever-increasing burden of new responsibilities from higher-levels of government. One can also add to this scenario, the vigorous competition for businesses and industries among cities and regional municipalities. Managers of municipal infrastructure assets must make difficult technical decisions as to when and how to repair, rehabilitate or reconstruct their assets, while working with continuously shrinking budgets. These managers do not have an easy task; they must allocate funds among competing yet deserving needs, often having to make decisions based on incomplete data.
A portion of the problems associated with the financial situation and technical decisions can be directly attributed to recent history and the recession: notably escalating maintenance deficits and ever-increasing repair backlog (Lacasse and Vanier, 1996). In addition, the asset managers’ resources are being challenged from all sides: managers are also being asked to cut cost, privatize operations, outsource responsibilities and reduce maintenance expenditures. These problems are exacerbated by the lack of usable data, information and knowledge related to maintenance and repair. In addition, these are few commercial tools to assist the asset manager make the proper inspection, maintenance, repair and renewal choices.
Definitions
The asset manager, by definition in this paper, is responsible for major maintenance, repair and renewal decisions, as well as the long-term strategic planning of a corporate real estate portfolio. A property or facility manager primarily deals with day-to-day accommodation issues and the implementation of the strategic plan. Therefore, asset managers are responsible for managing a substantial amount of construction and maintenance work. In many instances, the initial design and construction costs are small
compared to the asset maintenance costs throughout the infrastructure’s life: this makes the asset manager a major player in the construction game.
In this paper, service life is defined as “the actual period of time during which the building or any of its components performs without unforeseen costs of disruption for maintenance and repair” (CSA 1995). The term “unforeseen” is a key word in the definition: all components and materials require maintenance and they must be maintained to ensure that the service life is reached. Durability, on the other hand, is defined by the authors as “the rate of change of performance”; the authors discourage its use as durability has so many different meanings to so many different people.
Since this paper deals with business process re-engineering, the authors have selected the following definition for BPR: “Re-engineering is the fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service and speed” (MacIntosh and Francis 1996).
Problem Identification
The Office of the Auditor General of Canada has already commented on the poor state of Canadian government assets: “The consequences of not carrying out adequate building maintenance and repairs are loss of asset value, poor quality of working space, potential health and safety problems, the probability of higher repair costs in the future, and increasing reliance on more costly leased accommodation. Without proper maintenance, facilities will deteriorate to the point that extensive investment is required to restore or replace them. The result, ultimately, will be increased federal costs” (OAG 1994).
It is estimated that there is over $ 1.7 billion in deferred maintenance in the Canadian Department of National Defence alone, which equals approximately 13 percent of its plant replacement value: “The Department [of National Defence] should introduce life cycle management for major individual elements of infrastructure to determine the most appropriate balances between capital and maintenance spending, monitor the amount of deferred maintenance of those individual elements as well as in total, and use the information in infrastructure planning” (OAG 1994).
The OAG recommends that departments have appropriate management information on asset condition, infrastructure costs and performance, and the consolidated requirements for repairs and maintenance, as well as appropriate maintenance standards that are consistently applied in each region. The OAG (1994) also identified traits of strong and weak real estate management; specific traits relating to service life and asset management are listed in Table 1. It is evident from the information in Table 1 that proper data collection, information management and performance evaluations are key to success in asset management. This would also hold true for municipal infrastructure assets.
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Table 1
Real Estate Management
Strong Weak
Appropriate management information systems for real estate operations.
Property-by-property accounting methods. Availability of information and methods for evaluating real estate performance and use. Performance of real estate assets in
comparison with overall corporate assets.
Failure to maintain adequate information systems on real estate assets.
Management attitude: “we do not manage our real estate in a business like manner”.
Operational concerns unduly influencing decision-making.
Failure to take property costs into account in making program decisions. Many other organizations have recognized the scope of the problems facing asset managers (NACUBO 1990; NRC 1990; CERF 1996). However, there is still need for considerable research and development in asset management today as many simple, practical questions related to day-to-day infrastructure maintenance, repair and renewal are still unanswered: (1) how much maintenance is really required; (2) is it more cost-effective to maintain, repair or renew a component or system; (3) how can the remaining service life of a component or system be calculated; (4) will the maintained, repaired or renewed component or system meet the desired performance requirements; (5) what are the risks of failure for individual components or systems and what are the consequences of failure, and finally (6) how can an asset manager make a logical, cost-effective and objective decision with so many unknowns?
In addition to these many questions regarding components and systems, there is a parallel set of questions for asset manager at the corporate level: (1) what are the organization’s maintenance deficit and maintenance debt; (2) what are the projected maintenance, repair and renewal requirements for each of the next 10 years; (3) will aggressive maintenance extend the predicted service life of specific infrastructure systems or networks; (4) can adequate services be maintained despite reduced operational budgets; (5) what is the corporate exposure to the technical, financial or judicial risk of failure, and finally (6) how can an asset manager/strategic planner make logical, cost-effective and objective decisions with so many unknowns?
Alongside these practical questions facing asset managers every day are parallel research questions that have also gone unanswered: (1) what maintenance data are required to predict the remaining service life of components or systems; (2) what are the life cycle costs of maintenance, repair or renewal alternatives; (3) what methods are required to predict the service life of materials, components or systems; (4) how can performance be quantified using objective, repeatable, and representative indicators; (5) how can the risk of failure be calculated and how can the consequences of asset failure be identified, and finally, (6) how can we integrate all these new data and information to allow the asset
manager to make logical, cost-effective and objective decisions regarding maintenance, repair and renewal alternatives?
It is evident from the itemization of these questions that asset managers face an intractable dilemma and that current financial situations have exacerbated the situation.
Proposed Solution
Project Objectives
The National Research Council Canada and the City of Montreal are addressing some of these service life questions with their “Municipal Infrastructure Investment Planning” (MIIP) Project. The MIIP project will attempt to build on the existing service life and asset management information (Lacasse and Vanier, 1996; Vanier and Lacasse, 1996), will endeavour to provide a clearinghouse for service life and asset management research for urban infrastructure, and will provide tools and techniques for asset managers to better manage their facilities.
This consortium between the National Research Council of Canada (NRCC), the City of Montreal and other interested parties proposes to develop a methodology to assist in the investment planning for municipal infrastructure assets. NRCC researchers, the City of Montreal’s technical services and representatives of other organizations will work together on developing and validating a framework for the management of municipal infrastructure assets. This will include assessing existing condition of the inventory, prioritizing maintenance and repairs, analysing the associated maintenance and repair risks and assisting decision-makers to optimize investment strategies. The ultimate goal is to improve the quality of services while working within fiscal constraints.
This methodology to assist the investment planning of municipal infrastructure assets will integrate innovations such as condition assessment and diagnosis, computerized management, risk assessment and financial analysis. In addition, to ensure the quality of the final product, the methodology will be developed in accordance with the ISO 9000 family of standards for quality management and quality assurance
Project Benefits
The benefits associated with developing methodologies to assist investment planning of mixed urban infrastructure assets are numerous:
• sound management of built assets;
• investment optimization on maintenance expenses;
• reduction of emergency interventions;
• life cycle analysis of investment decisions;
• evaluation of the risks and impacts associated with maintenance decisions;
• introduction of the IS0 9000 concept;
• in the vanguard of North American and European organizations, and development of local expertise..
DEVELOPMENT OF A METHODOLOGY TO ASSIST MUNICIPAL INFRASTRUCTURE
INVESTMENT PLANNING S ep . 1 99 7
Expected Results: analysis and integration of existing knowledge; extension of research and integration of results in order to develop the requisite methodology for asset surveys; evaluation of the type, quantity and quality of the existing data within the City’s services in order to identify any gaps in informationthat may need tobefilled; the decision-making method prototype will be ready for validation in target sectors.
Expected Results: collection and analysis of data from statistically representative sectors to produce a report on the condition and needs (both physical and financial) of the sectors and systems being evaluated; methodology validated on target sectors and a proposal for evaluation and analysis strategies for the remainder of the City’s built assets.
Expected Results: Depending on the strategies selected in the preceding phase, a larger sample of buildings, networks and other assets will be evaluated.
Expected Results: This phase will integrate the data collected in Phase 3 and analyse this data in order to estimate the maintenance needs, the potential impact of investment, and the associated financial and technical risks for different levels of investment in maintenance and repair.
Schedule 6 mths 6-8 mths 8-18 mths 6-10 mths Start: Sep 1997 Phase I Development of the Method Phase II Prototype Validation Phase III Generalized Data Phase IV Analysis
End Ph. II: Sep 1998 End Ph. I: Mar 1998
End Ph. III: Sep 1999
End Ph. IV: Mar 2000 NRCC / IRC –
City of Montreal
City of
Montreal-NRCC / IRC
Investment Planning
Figure 1. MIIP Project Schedule
CPWA I N N O VATI O N S I N U RBAN I N F RA S T R UCT URE NRCC
Project Work Plan
The project will evolve in four phases as indicated in Figure 1. These successive phases will allow the consortium partners to evaluate the results obtained at each stage and to modify the plans for the remainder of the project, where necessary. A description of each stage follows:
Phase I - Development of the method
This phase analyses and integrates the existing knowledge in condition assessment surveys and decision-making models. Although extensive research has been completed in this area, it is necessary to analyze and evaluate this research and integrate the findings in the proposed methodology. To identify any evident gaps in the data, this phase will also evaluate the type, quantity and quality of existing asset data.
At the end of Phase I, the methodology to assist investment planning of mixed urban infrastructure assets will be ready for validation on representative data.
Phase II - Validation on a prototype
In this phase, statistically representative sectors forming part of the City of Montreal’s built assets will be selected and will serve to prototype the previously developed methodology. Once the sectors have been identified, the team will collect and analyse the data to produce a report on the condition and needs (physical and financial) of the sectors and systems evaluated.
Phase II will result in a methodology validated on target sectors, and in a proposal for evaluation and analysing strategies for assessing the condition of mixed urban infrastructure assets.
Phase III - Generalized data
Depending on the strategies selected in the preceding phase, and depending on the cost of the condition assessment survey, a large portion of the City of Montreal’s buildings, networks and other assets will be evaluated. The same type of evaluation can place for other partners in the consortium. All these costs will be borne by the individual organizations.
Phase IV - Analysis and recommendations
This phase will integrate the data collected in Phase III and analyze this data in order to estimate the maintenance needs, the potential impact of investment, and the associated financial and technical risks for different levels of investment in maintenance and repair. Analyzing the data collected in Phase III will determine whether or not there is need to expand the extent of condition assessment surveys with respect to the number of sectors, facilities or assessment level. These costs will be borne by the individual organizations.
Project Integration Model
The BELCAM project (Vanier and Lacasse 1996; Lacasse and Vanier 1996), a project dealing with service life prediction of roofing systems, has identified the six enabling technologies, illustrated in Figure 2, that can help asset managers predict the service life
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of building envelope components. This BELCAM integration model will be used in the MIIP project, as it exemplifies the complex interrelationships of disciplines within investment planning. Product Modelling Risk Analysis Service Life Research User Requirement Models Life Cycle Economics Maintenance Management
Product Modeling manages and integrates data and information related to service life
prediction and asset management. determines the probability of failure
and consequences of damage
establishes criteria for evaluation of performance and quantifies desired
performance levels
collects necessary laboratory and field data to develop performance curves
records and predicts operation and maintenance costs from cradle to grave
records and monitors condition of building elements and systems
Figure 2. BELCAM Integration Model (Vanier and Lacasse, 1996)
It is no coincidence that the six enabling technologies shown in Figure 2 address many of the problems enumerated in the previous section. In fact, there is a one-to-one correlation between these questions and the BELCAM Integration Model. Although all the enabling technologies identified in Figure 2 are well-established research domains in their own rights, there is little evidence of intercommunication between individual areas or the integration and standardization of data in general.
Maintenance Management
In North America, the importance of asset management programs is well understood in both the private and public sectors (NRC, 1990; 1996, CERF, 1996). Hence, there is considerable literature available in this area from which a standard and systematic approach to maintenance management can readily be developed. However, only general numbers for the amount of maintenance are indicated and no specifics are provided for specific domains (e.g. paving).
Response Programmed Emergency
Normal Response
Condition Independent Programmed Condition-Based
Annual Cyclical
Inspection Type Action
Inspection Cycle Maintenance
Service Life Prediction
The body of knowledge encompassing service life of construction materials is evidently quite large (Lacasse and Vanier 1996). Numerous studies have been undertaken to report on the service life of construction systems, components, or materials in particular those elements identified as having failed prematurely.
Statistical methods have been used to evaluate the long-term performance of roofing and parking garage systems (Cheung and Kyle 1992; 1996; Kyle, 1997); however, few comprehensive methods combining field studies, laboratory accelerated test methods and modeling have been developed. In the roofing area for example, Paroli and Baskaran (1996) are providing insight towards developing a comprehensive evaluation program for roofing membranes. This approach is based on an understanding of the most significant factors causing degradation of low-slope roofing systems and encompasses the use of a dynamic wind test facility together with modeling expertise. More recently, an integrated approach has been proposed that takes into account the variability of information used to make service life predictions (Lounis et al, 1998a; Lounis et al., 1998b).
Figure 4. Service Life Prediction
Life Cycle Economics
In the engineering domain, life cycle costing has been typically used to assess the economic feasibility and benefits of different design or retrofit options. Fundamental components of an analysis include: unit costs to replace, repair, inspect and maintain the asset, as well as design service life and anticipated frequency of inspection and routine maintenance. Time Performance indicators • Tensile strength • R-value (insulation) • Thickness (mm) Defect Maintenance & operations Repair Failure Limit state Service life
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In Figure 5, the schematic clearly shows that Product A has a considerably higher life cycle cost. In addition, because the performance curve comes close to the Limit State level on a number of occasions, it is more susceptible to failure at those times.
Time Initial Costs Maintenance Displacement Costs Interest Costs Performance Indicators
Initial Costs Interest Costs Maintenance
(a) Product 'A' (b) Product 'B'
Repair Time Life Cycle Costs Limit State
Figure 5. Life Cycle Economics
Risk Analysis and Reliability Assessment
The reliability-based approach is often utilized in assessing the long-term performance of various types of structures or materials (Attwood et al 1989; Thoft-Christensen 1994). It is based on two concepts, the first of which is related to the loss in performance with time (Pt) of a product, or built system, when subjected to a series of loads (including environmental as well as structural) causing deterioration (St). The second concept defines failure that arises when the level of performance of the system can no longer sustain the loads to which it is subjected. In other words, failure occurs when St ≥ Pt. The margin of safety of a given system is simply the difference between Pt and St at any time, t, and, as a system degrades in time, its margin of safety is reduced. Risk represents the probability of failure of a system in a given period of time, and, the consequences of the failure, whether they be repair or incidental costs. What is important in systems that are to perform in difficult environmental conditions over extended periods of time is maintaining the reliability of these systems, not their condition. Thus, data collected in a condition assessment survey should reflect the change in the reliability of the system as a whole. This implies that the state or condition of a system being inspected should then be linked to the change in reliability of the system or its components. In this way, programmed maintenance and repair for a given system can be based on updated reliability estimates. These techniques represent a valuable tool for maintenance managers to minimize their maintenance costs and maximize the value of their assets. This method is gaining acceptance in areas such as concrete bridge maintenance and repair strategies, and has been successfully applied to assessing the long-term performance of parking garage structures and to determine the probability and consequences of repair and rehabilitation decisions (Cheung and Kyle 1992; 1996).
User Requirement Models
User requirements and their relationship to functional requirements for building elements have been derived from work on the performance concept in building technology. Although a proposed structure for the performance concept has been available for more than two decades (Sneck 1973), there has since been considerable research in this field, much of which has evolved within the CIB Working Commission on the Performance Concept in Building (CIB W60 1976, 1993). The definition of the performance concept “takes as a starting point a recognition of the needs expressed in terms of human and user’s requirements”. This CIB Working Commission also supplements the earlier work in the field with clear definitions for terms such as “stress”, “functional performance requirement”, and “performance assessment”. CIB W60 has worked to provide more depth to the vocabulary and structure and has promoted the development of performance standards. Indeed, the construction industry now has concise descriptions of the performance concept included in ISO documents that provide clear and concise examples and classifications for components of the performance models. A number of formats and templates for the development of performance standards (ISO6240, 1980; ISO6241, 1984; ISO7162, 1984) are available and this work has been applied in a number of domains (ISO6242-2, 1992).
The BELCAM project is developing a user requirement model for the roofing domain called FRAME (Functional Requirement Analysis and Modeling Environment) (Vanier
et al 1997). The FRAME model provides an opportunity to disassociate functional requirements from performance requirements, while taking into account the extraneous concepts that affect service life prediction, such as Agent (Stress) and Occupancy (Use). However, a serious re-engineering will have to take place in the construction industry regarding performance-based specifications, standards and codes before FRAME can be used effectively to establish criteria for evaluation of performance and to quantify desired performance levels. FunctionalElement delegated_to dictated_by Occupancy (Use) evaluated_by affects Agent (Stress) FunctionalRequirement PerformanceRequirement affects
Figure 6. FRAME Product Model (Vanier et al, 1997)
Product Modeling
It is envisaged that product modeling will be used to manage and integrate data and information related to service life prediction and asset management. Product modeling is a means of expressing notional concepts describing different ‘products’ and their interrelationships in a ‘computer-interpretable’ format. ISO10303 (1993) is the international standard for the “computer-interpretable representation and exchange of product data”. EXPRESS is its specifications language that provides the necessary
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language elements for an unambiguous definition of concepts. Text-based representations such as EXPRESS are easily understood by computers, but are difficult for humans. As an alternative, graphical notations, such as EXPRESS-G (please refer to Figure 6, as an example), have been successfully developed to represent the complex relations typical of construction components and materials (Luiten 1993).
Opportunities in Infrastructure Asset Management
These six enabling technologies provide a philosophical framework for research and development for the MIIP project; in addition, there are a number of opportunities applicable in infrastructure asset management. These opportunities have been divided into two areas for discussion purposes: innovative techniques and information technology tools.
Innovative Techniques
Included in the category of innovative techniques are managerial-type tools that can assist asset managers classify, store and retrieve the vast amount of information needed to make service life decisions. This includes techniques such as computerized maintenance management systems, engineered management systems and condition assessment survey systems.
Computerized Maintenance Management – There now exists a large selection of “fully commercialized” computerized maintenance management systems (CMMS). Many of these are relational database applications that have been developed to meet the data handling needs of asset managers. The field, at this time, is quite mature and many stable, comprehensive, useful tools exist. For example, any number of database applications can manage work orders, trouble calls, equipment cribs, stores inventory and preventive maintenance schedules, and many include features such as time recording, inventory control and invoicing. Their capability to store inventory data is well understood; however, their usefulness with respect to life cycle economics, service life prediction and risk analysis is less well known. These systems are currently not able to assist the manager in analysing data or offering scenarios of long-term system readiness, capability, or performance; but are becoming an essential tool for the asset manager of the 1990’s. A quick search on the Internet (e.g. www.altivista.dignital.com, www.excite.com) using the terms “computerized maintenance management system” or “CMMS” will instantly produce thousands of sites to browse.
Engineered Management Systems – The US Army Construction Engineering Research Laboratory (CERL) has pioneered the use of engineered management systems in many construction sectors including paving, roofing and rail maintenance (www.cecer.army.mil). Engineered management systems (EMS) attempt to assign a condition index (CI) of an asset based on a number of factors including the number of defects, physical condition and quality of materials or workmanship. Research studies have estimated the potential degradation of the CI based on loads on the system or external agents acting on materials. With all these data in hand, it is therefore possible to predict the CI well into the future, given the degradation curve and the effect of remedial
action. In infrastructure asset management a number of systems exist including PAVER (Shahin et al, 1987), ROOFER (Bailey et al 1989), BUILDER (www.cecer.army.mil/ facts/sheets/FL25.html), and RAILER (www.cecer.army.mil/facts/sheets/FL44.html).
Condition Assessment Survey System – A condition assessment survey (CAS) establishes the existing condition of the asset (IRC, 1994); and hence is a benchmark for comparison, not only between different assets, but also for the same asset at different times (www.fm.doe.gov/fm-20/cais.htm). “Using CAS, a maintenance manager can formalize the assembly of basic planning elements such as deficiency-based repair, replacement costs, projected remaining life and planned future use.” (Coullahan and Siegfried 1996). CAS provides asset managers with the data necessary to quantify the current state of their assets. CAS records the deficiencies in a system or component, the extent of the defect, as well as the urgency of the repair work; in some cases the estimated cost of repair is provided at the time of inspection. “Management, as a result of the data generated by CAS, is better able to develop optimal plans for maintenance and repair of their buildings” (Coullahan and Siegfried 1996). This type of systematic inspection is essential for asset management in general, and to the MIIP project specifically as it provides data for the “maintenance management”, “service life prediction” and “risk analysis” enabling technologies, described earlier. The US Department of Energy has a significant program dealing with life cycle asset management/condition assessment surveys (LCAM/CAS) and has started to publish newsletters on the topic (Jones, 1997; www.fm.doe.gov/fm-20/read.htm) and hold regular technology transfer conference calls (Christie, 1997).
Level of Investment – Level of investment (LOI) studies (NRC, 1990; CERF, 1996) have indicated that maintenance expenditures should be between two and four percent of the capital replacement value (CRV) of a facility. Unfortunately for practitioners, these numbers are speculative and based on experiential information only; in addition, they provide too wide range of variance (100% increase) and have not been fine-tuned for specific construction systems (e.g. roads versus buried systems versus roofs). Furthermore, the CRV is difficult to calculate (Lemer and Wright, 1997), it is open to interpretation and will change over time. Nonetheless, LOI provides a good start from which maintenance costs can be estimated.
In this regards, The National Association of College and University Business Officers (NACUBO 1990) has proposed a detailed process consisting of separating costs attributed to capital renewal from that which is deferred maintenance. In this process, the asset manager first identifies maintenance that has been postponed, phased or deferred, and then attempts to provide an estimate of the cost for that deferred maintenance. NACUBO uses the term “facility condition index” or FCI to provide a comparison metric between different facilities or systems. The FCI is the amount of deferred maintenance divided by the CRV. NACUBO (1990) indicates that facilities with FCI’s higher than 0.15 are problematic. The second portion of the process is capital renewal (CR) analysis, and it involves the identification of the replacements that will be required at the end of the service life of various parts, components or systems. The CR analysis includes estimating the renewal costs in five-year lumps, and spreads these costs equally over each year. In this way, costs for the CR for each system or facility can be calculated well into
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the future, and can be brought forward as a present value or calculated as an annuity expense.
IMPACT (Installation Maintenance Prioritization, Analysis, and Co-ordination Tools) – The goal of this CERL research project is to provide the capability to identify effective installation-wide strategies for managing the maintenance and repair of facilities and infrastructure through multi-year plans. The approach follows operations research models: the facilities are modeled as a systems network, initial states are established by EMS and CAS, “what if” scenarios are simulated based on predicted deterioration curves, user requirements and budget allotments, and maps, graphs and point-and-click provide the user interface. Although still in the prototype stage, IMPACT is providing a view of the potential of information technology as it relates to investment planning (Subick, 1997)
Project CITY (Civil Infrastructure Technology) – “The objective of this project is to support the sustainable management of civil infrastructure via (1) a principled methodology for the study of work practices, problem solving, co-ordination, and use of technology in an organization, (2) the integration and further development of existing information technology to support team decision making and information sharing, and (3) the application of the methodology and information technology to the civil infrastructure system (specifically, gas pipeline and road systems) of Fort Gordon, Georgia.” (www.tec.spcomm.uiuc.edu/projcity/cityprop.html)
SimCity – SimCity is a popular computer game (www.maxis.com/games/simcity2000) that allows the user to build and manage a growing municipal infrastructure. The user is given a barren plot of land to zone into residential, recreational, industrial or commercial and also to lay roads, subways, highways and railroads. In addition, the user has control over taxes, education and health issues. As the city grows the user is faced with more controversial issues including re-elections, riots, earthquakes, fires and strikes. Although this “IT infrastructure opportunity” is a computer game, it gives a realistic vision of tools that municipal officials and professionals could use in the not-too-distant future.
Information Technology
Information technology (IT) such as CD-ROM, Internet, computer aided facilities management, Global Positioning Systems (GPS) and mobile computing provide an information infrastructure to supply and manage the vast and diverse data collected in a “business process re-engineered” asset management.
Compact Disks, Read Only Memory – CD-ROMs are available from many product manufacturers and this media can provide a cornucopia of information on products, including colour images, product specifications, CAD detail drawings and installation videos. CD-ROMs also provide quick access to many of the codes, standards and specifications required by asset managers. Most new computer systems are sold with built-in CD ROM readers.
Internet – The Internet is fast becoming the search tool of choice in the information age; good infrastructure examples include those at Purdue University (ce.ecn.purdue.edu/~iims). The Internet’s user-friendliness, low cost, quick response time and graphical interface all contribute to its recent and continuing popularity. At one
time, only librarians had access to electronic literature search; now it can be on everyone’s desktop. For example, a simple search using the AltaVista (www.altavista.digital.com) search engine and the search strategy “infrastructure” AND “service life” produced 223 documents, the large majority directly relating to the topic at hand and some providing extra information for this paper. As a comparison, Excite (www.excite.com) provided an additional 300 related hits. The Internet is an excellent tool for finding information about new publications, innovative companies and products or computer software, but fails miserably when looking for older documents which will not be in electronic form.
Computer Aided Facilities Management – Computer aided facilities management (CAFM) is the graphical side of the maintenance management. Initially used by the facility designers as a computer aided design and drafting tool, CAFM now provides the opportunity to integrate the design information to some of the facilities management data. This graphical interface is invaluable for infrastructure inspection and maintenance. Although CAFM concentrates on building information, similar tools could be used for infrastructure. (For more information, you can search for “CAFM” on your favorite search engine.)
GIS – Geographical Information Systems relate technical information to geographical information. This domain is evolving rapidly and has strong ties to infrastructure asset management. Many commercial CMMS, EMS or CAFM application lay claim to interfaces to GIS. How this is done, or how easily it is integrated is application-specific and extremely difficult to ascertain, test or compare. (For more information, you can search for “GIS” AND “infrastructure” on your favorite search engine.)
Mobile Computing – Mobile computing is opening many new possibilities for asset management. Portable computers (four to eight pounds in weight) and personal digital assistants (PDAs) provide the input and output required for asset managers who are on-site or in the field. These devices can tie directly to the CMMS and CAFM systems, permit the operator to upload or download data in the field, access the Internet, and in general increase both the accuracy and the speed of data collection, searching and retrieving. Handheld computers are becoming more and more popular, miniaturized and powerful. Windows™ operating systems using pen-based systems will dramatically increase our capability to capture data and search information bases.
Global Positioning Systems – Another related technology that will assist infrastructure asset managers is global positioning systems or GPS. Opportunities abound for rapid and accurate data collection using GPS: precise building or service locations can be identified, areas and lengths can be calculated, building height can be estimated, and the physical location of identified defects and potential problems can be easily, clearly and unambiguously documented.
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Conclusions
In summary, asset managers face many difficult tasks to maintain their assets in the existing economic times, but fortunately, there are many opportunities to assist them with their problems.
The technological solutions to the problems of deferred maintenance and capital renewal are neither imminent nor obvious. However, the problem is not intractable provided asset managers have a comprehensive suite of tools to help them manage their facilities; the MIIP project attempts to address such problems in infrastructure asset management. The enabling technologies described in this paper provide the research framework for developing tools to collect, classify and analyse service life and asset management data. Techniques described in this paper such as capital renewal/deferred maintenance, condition assessment surveys and level of investment studies provide systematic ways of dealing with rapidly increasing maintenance backlog. Tools such as information technology provide accurate, standardized and rapid ways to collect service life and asset management data.
Unfortunately, the opportunities listed above are only partial solutions to many of the problems in asset management identified earlier. However, the authors, being optimists, believe that the rapidly changing field of information technologies will provide both an opportunity and a mechanism for business process re-engineering. None of this will happen automatically, in the humble opinion of the authors; everyone will have to work progressively in order to design, implement, test and use these enabling technologies, innovative techniques and information technologies efficiently and effectively.
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