Asset Management and Asset Maintenance

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YOU CANNOT MANAGE WHAT YOU CANNOT MEASURE: AN INFORMATION SYSTEMS BASED ASSET MANAGEMENT PERSPECTIVE
Abrar Haider, Andy Koronios, Gerald Quirchmayr School of Computer and Information Science, University of South Australia, Mawson Lakes, Adelaide 5095, Australia.

Abstract: Measuring the impact of implementation of information systems for asset management is a complex issue; due to the stochastic nature of process variables, substantial effects of information systems on the way users embrace these systems and consequently execute the business processes, and the high expectations that asset managing businesses associate with the use of information systems. This complexity can partly be attributed to the technology push strategy, rather than technology pull strategy, that asset managing businesses adopt to introduce information systems in to the business. Therefore, in order to take optimum advantage of information systems with regards to process efficiency, effective control, and management, it is important to have effective measurement mechanisms that help managers to measure Information systems utilisation for asset management process. This paper presents a measurement framework that assesses the impact of information systems at each stage of asset lifecycle management. The proposed framework based on generative learning, such that it examines the interpretation of asset management strategy through the use of information systems within the business and its assessment provides for strategic indicators for recalibration of asset management strategy as well as highlights the roadmap for future technology investments. This assessment allows for asset management processes and their stakeholders to adopt a technology pull strategy, which provides the strategic fit between processes and technology; thereby allowing the business to leverage optimum advantage of technology through rationalized investments. Key Words: Asset Management, Asset Maintenance, Performance Evaluation, Information Systems.

1

INTRODUCTION

Rationalising size and quality of investments in information technologies along with improvements in organisational performance is on the strategic agenda of businesses around the globe. Nevertheless, businesses also take a few aspects for granted when it comes to adoption and implantation of information technologies. A common example is the massive investment in enterprise resource planning systems that carries the belief that its adoption would become a driver of operational excellence and an important source for business value. However, adoption of information technologies, particularly that of information systems (IS), entails taking stock of existing competencies, business architectures and processes that may be impacted by technology adoption [1]. This has particular relevance for the high risk and capital intensive businesses, such as engineering enterprises (see for example [2]). Generally, a fundamental issue with engineering enterprises is that they do not match their competencies, critical resources, and systems, with investments in technology. Consequently, there is little fit between the adopted technology and the way business is executed. This technology push strategy hampers the organisational adaptation to technology and the same time does not allow the business to take optimum advantage of technology. Nevertheless, in order to achieve this the business requires appropriate evaluation mechanisms that assess process performance, such that the assessment provides an understanding of the underperforming areas along with the reasons that contribute to the below par performance and the impact this underperformance man have on other areas of the business. This not only provides for the review of the performance of existing technology, but also provides for the useful indicators for future investments in technology. There are various advantages of having such a generative learning based performance measurement mechanism. Most significantly, it provides a holistic view of the whole business area and therefore highlights a road map for continuous improvement, whereby it facilitates the right choice of technology that best suits the business environment and ensures that the investments in technology are not just aimed at facilitating isolated business processes, rather each process contributes towards the overall strategic aims and objectives of the business. This paper focuses on the IS utilised for asset life cycle management processes. It takes an asset lifecycle perspective and proposes a performance measurement framework for asset management, which assists engineering enterprises to evaluate the effectiveness of the IS utilised in the asset management lifecycle. The framework provides a cyclical approach to performance measurement such that it assesses and informs the role of IS in translating and informing the asset management strategy in a single cycle, thereby allowing for generative double loop strategic learning to enhance competitiveness of asset managing engineering enterprises.

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2

PERFORMANCE ISSUES IN ASSET MANAGEMENT

An asset is the physical component of a manufacturing, production or service facility, which has value, enables services to be provided, and has an economic life of greater than twelve months [3], such as manufacturing plants, railway engines and carriages, aircrafts, water pumps, and oil and gas rigs. Accordingly, management of these assets represents a set of disciplines, methods, procedures and tools to optimise the whole life business impact of costs, performance and risk exposures associated with the availability, efficiency, quality, longevity and regulatory/safety/environmental compliance of a company’s assets [4]. British Standards Institute [5] terms asset management as “combination of management, financial, engineering, and other practices applied to physical assets in pursuit of economic life-cycle costs. Its practice is concerned with specification and design for reliability and maintainability of plant machinery, equipment, buildings, and structures with their installation, commissioning, maintenance, modification, and replacement, and with feedback of information on design, performance, and costs”. Nevertheless, the fundamental aim of asset management processes is the continuous availability of service, production and manufacturing provisions of assets. Consequently, asset management processes interact with a variety of other business processes, such as enterprise planning and product development, which necessitates timely and quality information interchange and coordination of activities with other functions within the business as well as with business partners, in order to allow for activities such as materials procurement, logistics, maintenance and repairs of assets, and customer relationship management. In crux, asset management is policy driven, information intensive, and is aimed at achieving cost effective peak asset performance. Asset management is not a set of isolated processes that support the life cycle of assets utilised by engineering enterprises, but these processes are actually embedded with the strategic processes of the business and have a direct impact on the overall profitability and efficiency of the businesses, as shown in Figure 1.
External Factors

Auditors Contract management Contractors

Operational level

Regulations Operation management Legislation

Tactical level Customer service Assets management Maintenance management

Suppliers

Work management

Inventory control External consultants

Strategic Purchasing Resource level planning AM goals & policies, Strategic level AM planning , Human Ownership resource definition Engineering Marketing Finance

Condition monitoring

Government agencies

Registry management Business stakeholders

Location management Pressure groups Risk management

Reliability management Economic forecast

Figure 1: Asset Management Overview (source [3]) An asset lifecycle starts at the time of designing the manufacturing or production system, and typically illustrates, stages such as, asset commissioning, operation, maintenance, decommissioning and replacement. Market demand and supply dynamics derive product and services design, and this product and services design derives production. Production specifies the operational workload of an asset. Operational workload and asset design generate maintenance demands to keep the assets in running condition, whereas maintenance determines the future production capacity of the assets as well as their remnant life span. Table 1 summarises the processes and the activities involved in asset lifecycle management.

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Table 1 Asset Management Lifecycle Management Actions Strategic Planning Focus Description
Planning of asset management objectives, functions, processes, technology, lifecycle costing, level of service, support infrastructure, and activities to meet business goals, stakeholder requirements, and demands management. Strategic planning aims to provide the strategic fit between the overall business objectives and each activity performed in asset lifecycle management. Focus of strategic planning is to enhance competitiveness of the businesses through effective management of asset lifecycle. Creation or procurement, operation, condition assessment, maintenance, refurbishment, replacement, and disposal assets. Ensuring availability, efficiency, quality, longevity and regulatory/safety/environmental compliance an asset at minimal costs Capital investment to acquire, construct, or improve an asset to satisfy or improve level of service, stakeholders’ demand management, and production or manufacturing efficiency. To ensure asset reliability, compliance and increased availability through effective design and best possible economic tradeoffs; for example high development costs might be traded off against lower maintenance costs through improved reliability. Development costs themselves may be offset through increased asset availability leading to increased production output. Smooth asset operation through close collaboration with maintenance function, and providing

Core Asset Management Actions Focus
a. Asset creation/acquisition Focus

b.

Asset Operation Focus

feedback on asset operational behavior to design function.
Efficiency and quality, regulatory/safety/environmental compliance of asset operation through conformance with planned operating conditions, as designed instructions, and environmental regulations. Asset operation condition monitoring to assess the ability of asset to meet required service levels and mitigate operational risks, including continuous or periodic inspection, assessment, measurement, reporting and interpretation of resulting information to indicate the condition of the asset in order to specify the nature and timing of maintenance. To ensure asset longevity by proactively assessing asset condition in order to predict developing failure conditions, such that the subsequent maintenance execution and resources could be planned. Sustain and where necessary performance necessary repair and maintenance on assets in such a way that they continue to fulfil their functions and make the required value adding contribution to the manufacturing or production process, including actions such as spare supply chain management, maintenance planning and maintenance workflow execution, routine repairs, and testing. Ensuring efficiency and longevity of asset by taking necessary actions to retain an asset to near original asset configuration and condition by decreasing its rate of deterioration, thereby minimising asset downtime. Rehabilitation of an asset through technology refresh, end of need, or maintenance; including actions such as treatments for improving condition either to attain as designed/as constructed condition or to exceed the as designed/as constructed condition in order for the asset to function at a satisfactory level of service for a prolonged time frame. Review of asset configuration, type, location, and service delivery aspects, and their fit with the strategic business objectives. Investment aimed at replacing or reconstructing an existing asset in order to enhance level of service, and/or improved configuration, and/or change in physical location. Asset disposal or retirement means rationalisation of an asset according to safety/regulator requirements when it is no longer in service. Continuous improvement opportunities in asset design and configuration, in order to provide elevated level of service.

c.

Asset Operation Assessment

Focus d. Asset Maintenance

Focus e. Asset Rehabilitation

Focus f. Asset Replacement/Disposal

Focus

Continued

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Actions Asset Lifecycle Support Focus
Asset Lifecycle Costing

Description Asset lifecycle support is aimed at having requisite infrastructure supporting life cycle decisions of an asset, whereby the essential gaol is to identify all available options and select the most efficient and cost effective option. Financial and non financial infrastructure aimed at enhancing the quality of asset lifecycle management.
Calculation of asset lifecycle cost benefit analysis including asset design, asset procurement and/or construction, asset operation, asset maintenance and support, and asset retirement and disposal costs. It also contributes to assessment of high-cost contributors; cause and effect relationships; potential areas of risk; and identification of areas for cost reduction. A systematic approach to recording and analysing costs associated with each stage of asset life cycle, so as to provide asset lifecycle management decision support in terms of economic tradeoffs and cost benefit analyses. Availability of complete, current, and accurate information on each asset, including its design, construction, configuration, location, workload, health status and history, cost benefit analysis, and the physical environment that it operates in. An integrated approach to economic and performance tradeoffs and lifecycle decisions, through organization of information relating to asset design, operation, condition, maintenance, refurbishment; skills and support infrastructure to ensure asset reliability, availability, and quality; analytic models that predict future changes in asset design, operation, condition, as well as the variations in support mechanisms to forecast and plan for resources; and cost benefit analysis for tradeoffs regarding asset design, operation, maintenance, renewal, and decommissioning etc. Combination of hardware; software; information acquisition, processing, communication and storage infrastructure; and skills of employees to process information with the hardware and software; to accomplish various asset management processes and providing required outputs for effective asset management. Strategic fit between technology and asset management processes, aimed at availability of timely, consistent, complete, accurate, and reliable information. Review and assessment of asset lifecycle management actions to measure their effectiveness in satisfying business needs. Audit and assessment of implementation and execution of planned activities against documented gaols, objectives, strategies, and stakeholder requirements aimed at continuous improvement of the asset management process. Profiling asset operation, managing lifecycle knowledge, and feedback for cost effective, better understanding, and continuous improvements in asset design, operation, maintenance, reinvestment, compliance, and asset lifecycle support infrastructure and resources. Preservation and use/reuse of asset management knowledge for subsequent strategic planning cycles.

Focus Asset Lifecycle Decision Support Focus

Asset Lifecycle Technology Support

Focus

Asset Management Performance Assessment Focus

Asset Lifecycle Learning Focus

(Adopted from [3], [4], [6-10]) It is clear from the above that IS utilised in asset management not only have to provide for the decentralized control of maintenance tasks but also have to act as instruments for decision support. An important aspect of asset lifecycle management is the learning or knowledge gained at each stage, which provides for the feedback to other processes. For example, asset operation profiling has significance for asset redesign as well as asset maintenance and asset operation cost benefit analyses and lifecycle decision support. Therefore, the most crucial feature of IS for asset management is their ability to provide an integrated view of asset specific information, such that engineering enterprises are able to leverage the full potential of the IS utilised for asset management. This requires appropriate hardware and software applications; quality, standardised, and interoperable information; appropriate skill set of employees to process information; and the strategic fit between the asset management processes and the IS. 3 INFORMATION SYSTEMS FOR ASSET MANAGEMENT

Information technologies are utilised at three levels for asset lifecycle management; firstly, they are used in assets, such as microcontroller operated motors. Secondly, information technologies that are used in facilitating asset lifecycle management support processes, such as digital sensors and other condition monitoring equipment, and process control infrastructure, such as Supervisory Control And Data Acquisition system (SCADA). Thirdly, the IS that not only facilitate execution of each stage of asset lifecycle but also provide for decision support for asset life cycle management, such as asset design, maintenance planning and execution, resource allocation, and maintenance workflow execution. Standardised and quality information, therefore, is the most important ingredient of effective asset lifecycle management. Having its origin in mass production aimed at capturing market share, quality management calls for standardization of processes managed by standardised data and facts that focus on certain targets set by informed choices. However, value of

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these informed choices cannot be guaranteed in business areas where such positivist assumptions are invalid (see [11], [12]). Asset maintenance is one such area within asset management, which has by and large routine processes, yet these processes operate in unpredictable environments and function on basically non-market transactions. Hence, the basic issue in asset management IS is not just the quality of converting input to output, but also the control of information guiding it and the eventual use and reuse of the resulting knowledge for decision support and enterprise wide planning. In simple words, the issue is not only doing things right, but also to have knowledge of what are the right things to do. On the contrary, while maintenance activities have been carried out ever since advent of manufacturing; modelling of an all inclusive and efficient maintenance system has yet to come to fruition ([13], [14]). This is mainly due to continuously changing and increasing complexity of asset equipment, and the stochastic nature or the unpredictability of the environment in which assets operate, along with the difficulty to quantify the output of the maintenance process itself [15]. At the same time, in response to the competitive pressures, maintenance strategies that once were run-to-failure are now fast changing to being condition based, thereby necessitating integration of asset management decision systems and computerized maintenance management systems in order to provide support for maintenance scheduling, maintenance workflow management, inventory management, and purchasing [16]. Businesses are now aiming for ways to providing direct connections from their asset management systems to Maintenance, Repair, and Overhaul/Operations procurement systems, which may allow for paperless purchasing of parts and offer considerable time and cost savings compared with traditional purchasing methods. Nevertheless, in order to leverage the advantages of technology asset managing organisations need to find the fit between technology and the processes. For example, a typical water pump station in Australia is located away from major infrastructure and has considerable length of pipe line that brings water from the source to the destination. In this situation, assets are deployed over an area of various kilometres; however, the demand for water supply is continuous for twenty four hours a day, seven days a week. Although, the station may have some kind of an early warning or process control and condition monitoring system installed, such as Supervisory Control and Data Acquisition (SCADA), maintenance labour at the water stations and along the pipeline is limited and spares inventory is generally not held at each station. Therefore, it is imperative to continuously monitor asset operation (which in this case constitutes equipment on the water station as well as the pipeline) in order to sense asset failures as soon as possible and preferably in their development stage. However, early fault detection is not of much use if it is not backed up with the ready availability of spares and maintenance expertise. The expectations placed on water station by its stakeholders are not just of continuous availability of operational assets, but also of the efficiency and reliability of support processes. Elimination and control of production irregularities and disturbances is, therefore, necessary for continuous production and service provision, and customer satisfaction. However, situation on ground is far from being perfect, for example, data is captured both electronically and manually, in a variety of formats, shared among an assortment of off the shelf and customized operational and administrative systems, communicated through a range of sources and to an array of business partners and sub contractors; and consequently any disparity in data at the acquisition level leads to the inability of quality decision support for asset lifecycle management [17]. In the prevailing circumstances, existing asset management IS could best be described as useful pools of isolated data that are not being put to effective use to create information and business intelligence. Most engineering enterprises mature technologically along the continuum of standalone technologies to integrated systems, and in so doing aim to achieve the maturity of processes enabled by these technologies and the skills associated with their operation [1]. Konradt et al [18] further assert that engineering enterprises adopt a traditional technology-centred approach to asset management, where technical aspects command most resources and are considered first in the planning and design stage. Processes, human and other organisational factors are only considered relatively late in the process, and sometimes only after the systems are operational. Consequently, engineering enterprises struggle to implement cost effective asset management strategies that best suit the business; develop lifecycle asset management competencies; plan an effective exit strategy for assets rendered obsolete through technology refresh or through end of need; and provide a credible chargeback system to allocate costs to the business lines and thus ensure that everyone is involved in avoiding redundancy and wastage of efforts [1]. In order to make an effective investment into technology, it is important for the business to take stock of the existing IS and the asset management processes that they enable. This highlights the need for a comprehensive performance measurement system that not only provides insights into the effectiveness of the IS used for asset lifecycle management, but also provide feedback on their fit with other business information systems so as to provide a lifecycle perspective of asset management to asset managers. Such a performance measurement system needs to be three dimensional (as shown in Figure 2), with each asset lifecycle management process being measured against the four dimensions of an IS, i.e. information, staff skills, software, and hardware; as well as the impact of each asset lifecycle process in terms of asset efficiency, availability, longevity, quality and reliability, and compliance with the environmental and operating legislations.

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Asset Management Processes

Asset Management Objectives

Efficiency Quality & Reliability Availability Longevity Compliance

Figure 2: Measurement dimensions for IS based Asset Management 4 PERFORMANCE MEASUREMENT SYSTEMS

There has been numerous business improvement methodologies developed and implemented. These methodologies represent a blend of theory and practice, with each having its own way of performance measurement that is largely dependent upon the target business area. Some of the leading initiatives in this regard include Benchmarking, total quality management, Six Sigma, European Foundation for Quality Management Business Excellence Model (EFQM), business process reengineering, and balanced scorecard. These methodologies constitute the basis of the most of performance measurement and management initiatives tailored by businesses to meet their needs. Remenyi et al [19] summarise the methodologies developed for performance assessment, and suggest that their focus has been on a. b. c. d. e. f. g. h. j. k. l. m. Strategic match analysis and evaluation, Value chain assessment (organisation and industry), Relative competitive performance, Proportion of management vision achieved, Work-study assessment, Economic assessment - I/O analysis, Financial cost benefit analysis, User attitudes, User utility assessment, Value added analysis, Return on management, and Multi-objective, multi-criteria methods.

Engineering enterprises have adopted these methodologies in a variety of ways aimed at different business areas and processes, such as for manufacturing planning and control [20], product development process [21], human resources development ([22], [23]) and service or facility management [24]. Although research has paved the way for major developments in the filed of business improvement, yet it is interesting to note that asset performance measurement has been largely limited to physical inspection of plant and equipment for its health assessment. Nevertheless, role of IS in asset management is not just of a process enabler, but also of translating strategic business goals and objectives into action. Therefore, it is important to have a performance measurement mechanism that provides for assessment of this strategic translation and also highlights the gaps such that corrective actions could be taken to enhance the competitive of the overall business. These characteristics entail that an appropriate performance measurement system for asset management should: a. b. [27]); Focus on business processes as well as the structures that deliver value [25]; Integrate different aspects of asset management, such that they constitute a chain for business competitiveness ([26],

c. balance the needs of various stakeholders, such as business partners or third party service providers, customers, employees, regulatory agencies, and society at large ([20]; [25]); d. be information driven such that it provides inputs to strategy re-calibration rather than being steered by the business strategy alone ([28], [29], [25]);

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People Applications Technology Information

IS Resources

e.

Conform to business objectives ([[28], [30]);

f. Aim at competency development and business intelligence infrastructure development in order to create and sustain value for asset management processes ([27], [25]; and g. Provide financial [27] as well as non financial assessments [25].

In engineering enterprises strategy is often built around two principles competitive concerns and decision concerns. Competitive concerns set the gaols of manufacturing, whereas decision concerns deal with the way these goals are to be met [48]. It is therefore, important to assess the role of IS in providing strategic executive decision support for value added asset management, in terms of the choice of assets, their demand management, support infrastructure to ensure smooth manufacturing or service provision, and efficient ways of doing business. These efficient ways mean choices of the business such as business partners, outsourcing of asset management functions, and service provision to third parties [47]. Fundamental requirement of IS at this stage is to provide decision support in terms of indications on economic tradeoffs and/or alternatives that help senior management in making strategic decisions. These decisions are not made in isolation; in fact, they are made in conjunction with the asset demand and stakeholders requirements. Therefore at the strategic level it is important to assess the effectiveness and ability of the IS in terms of enabling strategic asset management planning, goals, objectives and executive decisions. A usual manufacturing cycle starts with specification of the products and services that the business aspires to offer its customers in conformance with its business strategy. Any mismatch between what the market demands, manufacturing process design, and planning has a detrimental effect on the overall performance of the business [49]. Nevertheless, this specification illustrates the types of assets and processes that the business needs to put in place to produce services and products, also called asset demand specification. At this stage, it is important to assess if the designers have access to integrated information in order to process it to obtain knowledge of factors such as, the characteristics of the environment that the business operates in; design, configuration, and workload of each asset; asset and/or site layout design and schematic diagrams/drawings; asset bill of materials; analysis of maintainability and reliability design requirements (e.g. HAZOP); and failure modes, effects and criticality identification for each asset. Planning choices at this stage drives asset behaviour, therefore it is important to assess if the existing information systems are capable of providing the right information, such that choices could be made to ensure asset availability, reliability and quality of its operation, and efficiency. Design of an asset has a direct impact on its productivity. Productivity, itself, is concerned with minimising the disturbances relating to production or service provision of an asset. A production or service provision disturbance is an unplanned or undesirable function or failure of an asset [55]. It can be classified as asset downtime, speed or operation, and quality losses. It is important to note that disturbances do not only occur due to a mechanical or electrical fault, they can also occur due to some process and procedural issues. Disturbances occur in one of the three ways, as suggested by El-Haram [56], i.e., when an asset become inoperable suddenly, and can no longer perform its required operations; when an asset cannot fulfil some or all of its operations at the same performance standard as originally specified; or when an asset gradually deteriorates to an unsatisfactory level of performance or condition, and its continued operation is unsafe, uneconomical or aesthetically unacceptable. These disturbances can further be attributed to many causes. According to one study, more than one third of the production disturbances were caused by design errors [57]. Therefore, at this stage it is important to assess if the IS are capable of providing integrated feedback to maintenance and design functions regarding factors such as asset performance profiling; detection of manufacturing or production process defects; asset condition monitoring and inspection; asset failure notifications; quality control and assurance at each stage of asset operation; and processes, tests, analysis (FMECA etc) and standards to be applied for the validation of asset performance. Every asset generates some maintenance during its lifecycle. The aim of asset lifecycle support is to keep or restore and asset to its original or near original condition and service levels. This requires integration of technical, administrative, and operational information of asset lifecycle, such that informed and cost effective choices could be made about maintaining an asset and its remnant lifecycle. Therefore, the IS should be capable of handling the maintenance workflow execution as well as project management along with processing and providing information on factors such as, Asset failure and wear pattern; routine maintenance work plan generation; emergency maintenance scheduling and follow up actions (such as disaster containment, maintenance resources allocation etc); asset shutdown scheduling; maintenance simulation; testing after servicing/repair treatment; identification of asset design weaknesses; and asset operation cost benefit analysis. Maintenance, however, influences many areas of the business, such as asset availability in supporting just in time manufacturing principles [50], relationship between technology and operations [58], product quality [7], and achieving and sustaining a safe workplace and environment [38]. Therefore, it is important to assess the role of IS in providing for the up-to-date information on each asset’s health to other functions such as asset design and asset operation. This information is extremely important in asset improvements/refurbishments as well as in finding optimal ways of operating an asset. Nevertheless, an important aspect of effectiveness of asset management initiatives is the efficiency with which different processes are executed and the competencies of employees who carry out these processes. This efficiency comes from a variety of factors such as application of appropriate socio-technical systems principles and techniques make asset management creative and more productive; availability of asset lifecycle information and knowledge throughout the organisation; and

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development of employees skills to effectively use technologies associated with asset lifecycle management. IS provide for this value chain integration of asset management, therefore, it is important to assess the effectiveness of IS in terms of operational efficiency, and the ability of employees to operate IS and process information contained in them. A common trend among engineering enterprises is the outsourcing of core activities such as maintenance. This trend is quite common among for complex assets, such as aircrafts, and oil and gas rigs. In these circumstances neither the asset owning business, and nor the asset maintaining business has a complete understanding of asset behaviour, which obviously impacts asset lifecycle decision support. It is important to assess the level of integration that the IS provide in bringing together business stakeholders, such as business partners, customers, and regulatory agencies like environmental and government organisations. The idea behind this is to assess the level of information and knowledge being shared among the stakeholders to enhance the efficiency and competencies of the asset management process, by examining the IS maturity for factors such as third party services management; contract management; integration of inter organisational applications and processes; customer feedback and satisfaction measurement; and sharing common coding and databases with business partners. 5 IS BASED ASSET MANAGEMENT EVALUATION

From the discussion above, two characteristics stand out. First, IS based asset management performance evaluation entails taking stock of effectiveness of IS in facilitating each asset management lifecycle process; and second, how the IS provide for the functional integration between various asset management processes. Table 2 illustrates an evaluation framework for IS utilised for asset management. In this framework asset management process has been decomposed into seven perspectives, which cover the whole of asset lifecycle as well as provide for the functional interrelations; thereby forming a value chain that provides value added asset management. Table 2 IS based Asset Management Performance Measurement Perspectives Perspective
Design

Description
Planning of design and/or improvements in asset design and manufacturing processes according to feedback from asset installation, commissioning, operation, maintenance and replacement; and aimed at demand management as per stakeholders’ expectations. Asset availability and reliability by managing quality of operations, and mitigating risks posed to assets and to their operating environment; ensuing flow of information to maintenance and design regarding asset operation feedback. Financial and non financial resources support for asset lifecycle aimed at enhancing the quality of asset operation; decision support for effective asset health management; integration of technical, administrative, and operational information of asset lifecycle aimed at keep it, or restore it to original or near original condition and service levels. Measure of the factors that contribute to the overall effectiveness and integration of asset lifecycle processes and functions; application of appropriate socio-technical systems principles and techniques make asset management creative and more productive; business value chain integration; skills development of employees to effectively use technologies associated with asset lifecycle management; availability of asset lifecycle information and knowledge throughout the organisation. Integration of business stakeholders to achieve higher levels of asset management through communication and collaboration, sharing of information on asset lifecycle with subcontractors and business partners, and compliance to regulatory and environmental regulations. Availability of executive decision support indicators such as, asset lifecycle cost benefit analysis, operation profile, asset register to better manage asset demand and needs of stakeholders ; ability to measure the actual performance of asset lifecycle management processes against planned gaols and objectives to enhance competitiveness of the business. Profiling asset lifecycle, and managing lifecycle knowledge for better understanding of/and improvements in asset design, operation, maintenance, reinvestment, and compliance.

References
[3], [14], [32], [33], [34]

Productivity

[3], [4], [16], [20], [33], [34], [35], [37] [3], [6], [7], [8], [14], [20], [32], [36], [38], [39], [44], [50]

Support

Operational Efficiency

[3], [4], [7], [13], [16], [34], [36], [40], [41], [42], [43], [44]

Stakeholders

[2], [3], [20], [37], [38], [45], [46]

Competitiveness

[3], [6], [7], [8], [9], [14], [20], [33], [38], [47], [48], [49]

Learning

[3], [6], [7], [8], [10], [43], [51], [52], [53], [54]

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Figure 3 provides the graphical representation of the evaluation framework. Here IS act as the bonding glue that provides for the functional integration of asset management process. This framework provides double loop generative learning, as it allows for assessment of IS in terms of translation of strategy into action; and also highlights the gaps between the existing and desired levels of performance, thereby informing the business strategy in the same cycle. In so doing, the organisation learns from one cycle, applies the learnings to the same paradigm and assesses its results in the next cycle. At the same time highlighting of the underperforming areas creates the need for investment in technology, which not only allows for the right choice of technology but also helps in its acceptance in the organisation. This framework is learning centric that provides for preserving the asset lifecycle knowledge, such that it is accessible to every function within the organization. This learning perspective illustrates assessing the way IS are utilised in an engineering enterprise to preserve the knowledge that it creates through other perspectives regarding asset performance and operational knowledge; asset health history; asset operation cost benefit analysis; and historic asset lifecycle performance information. IS evaluation at this perspective means assessing the ability of the existing IS to provide multi dimensional analyses on asset lifecycle information, such that asset managers can take better informed decisions about the asset lifecycle and asset management processes. These analyses provide triggers for change regarding asset design, operation, maintenance, risk management, and other aspects of asset lifecycle management, thereby allowing for creativity in asset lifecycle management. In so doing, this framework provides for continuous improvement based on generative learning.

How well do the existing ICTs enhance competitiveness of the Asset Managing Businesses?

Strategic Control

Competitive Perspective
Innovation and Changes in Asset Design; Lifecycle Processes; Work Design; and Services

Goals

Measures
Collaboration and Information Sharing

Capacity Scheduling and Asset Demand Management

Business Intelligence Management

Organisational Responsiveness

Management Control

How well do the existing ICTs aid in Asset Design, installation, and commissioning?

Design Perspective
Business need definition

Learning Perspective Goals Measures

Goals

Measures Disturbance Management
Asset Operation Risk Management

Business Value Chain Integration

Stakeholders Perspective Goals Measures

How well do the existing ICTs integrate stakeholders in Asset Management Processes?

Integrated Resource Management

Business Value Chain Integration
socio-technical systems fit and integration

Asset Workload Definition

Operational Control
Horizontal Integration

.

Operational Quality Management

Competencies Development

Productivity Perspective Goals Measures
Asset Health Management

Support Perspective Goals Measures
Cost control and Budgetability

Operational Efficiency Perspective Goals Measures

How well do the existing ICTs ensure optimum asset operation?

How well do the existing ICTs manage financial and non financial resources to keep the asset to original or near original state?

How well do the existing ICTs ensure process efficiency and organisational integration?

Figure 3: IS Based Asset Management Performance Evaluation Framework

6

DATA COLLECTION

In order to provide an integrated assessment of IS based asset management, as suggested in figure 2, an assessment approach as illustrated in Table 3 could be adopted. Processes under each perspective could be assessed for dimensions of IS, i.e. information, people, software, and technology on a scale of 1 to 5. In the same way, depending upon the characteristics of the process, its purpose, i.e. primary or secondary, could be assessed. This information could be collected though surveys and with the help of Analytic Hierarchy Process (AHP) (Saaty 1990) and Multi-Attribute Utility Theory (MAUT) (Goicoechea et al. 1982) it could be aggregated to provide performance measurement of IS for processes relating to each of the perspectives identified for asset management process.

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Table 3 Data Collection Tool for the Proposed Framework
Asset Performance Criteria Efficiency Longevity Availability Compliance Reliability People IS Dimensions Software Technology Information

Design Perspective Asset bill of materials Naming and numbering of assets for configuration management Use of test and historical maintenance data of similar assets in establishing and evaluating operational tasks Identification of risks posed to asset operation (environmental, OH&S) Analysis of maintainability and reliability design requirements (e.g. HAZOP) Failure modes, effects and criticality identification ……………………………….. Productivity Perspective Processes Support Perspective Processes Operational Efficiency Perspective Processes Stakeholders Perspective Processes Competitiveness Perspective Processes Learning Perspective Processes

7

CONCLUSION

This research provides the basis for research into comparative analysis of IS based asset management for industrial and infrastructure assets to be conducted through the Cooperative Research Centre for Integrated Engineering Asset Management (CIEAM). This paper has proposed and theocratically demonstrated an approach for linking asset management to strategic competitiveness of an engineering enterprise through IS maturity assessment and control. It has particularly emphasised the use of IS for functional integration by providing a strategic fit between the structure and infrastructure of asset lifecycle management process. It has also shown how asset managing businesses could benefit by taking a lifecycle perspective of asset management, such that assets are treated as business enablers rather than just production or service provision enablers. 8 REFERENCES [1] [2] 1. Haider, A, and Koronios, A., (2005), “ICT Based Asset Management Framework”, International Conference on Enterprise Information Systems (ICEIS), 3, pp. 312-322. 2. Liyanage, J.P., Kumar, U., (2000), Utility of maintenance performance indicators in consolidating technical and operational health beyond the regulatory compliance, Doerr, W.W., Safety Engineering and Risk Analysis: The International Mechanical Engineering Congress and Exposition-2000, pp.153-160. 3. IIM, ( 2002), International Infrastructure Manual, National Asset Management Steering Group, Australia New Zealand Edition, Thames, ISBN 0-473-09137-2

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Acknowledgments This paper is a part of the research conducted for CRC Integrated engineering Assets Management (CIEAM), at the University of South Australia. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the CIEAM.

WCEAM 2006 Paper 047 Page 13

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