CIEAM

• sensors for assessing the development of corrosion beneath coatings and surface treatments adjacent to or within joints in large structural components, i.e. shipping, draglines, aircraft, bridges, process plant etc.,
• sensors for assessing the structural significance of corrosion and stress corrosion cracking,
• a methodology for autonomous remote monitoring,
• fibre optic sensors for measuring local temperatures in components and in manufacturing processes,
• a greater understanding of corrosive processes and their relationships to stress, and
• a methodology for the monitoring and measurement of plant and pipe wall thickness, internal material or scale build-up and/or blockage location.

AS102: Integrated Prognosis Tools for Assessing the Effect of Corrosion on Structural Integrity and Fleet Management

Professor Rhys Jones (Monash) The deliverables of this project are to develop:

• a validated technology for assessing the effect of corrosion on the safe operation life of full scale structural components,
• a validated methodology for assessing the effect of the degradation of paint coatings on the safe operation life of structural components,
• a simple tool for fleet management of corrosion and fatigue damage,
• a simple validated process for ensuring compliance with government regulation, and
• empirical and/or analytical models that can be used to predict the effect of paint coating failures on the fleet and therefore form the basis of a fleet management decision making process.

AS301: Sensors for Crack and Disbond/Delamination Detection and Monitoring

Dr Steve Galea (DSTO) Capabilities will be developed in sensor technologies to address key issues in structural integrity, specifically it will:

• identify the limitations of a stress wave based methodology for integrity assessment of composite and composite bonded repaired structures,
• develop field demonstrators of stress wave based methodology for structural health monitoring of aircraft structures,
• establish a database on the performance and durability of piezotransducer devices for the excitation/reception of stress-wave,
• develop an understanding of the capabilities of numerical modelling to predict elastic stress wave propagation in complex structural forms,
• develop stress wave based methodologies for integrity assessment of composite and composite-repaired structures, and
• develop an ultrasonic phased array technology to assess the structural health of welds which should lead to improved tools for management of welded civil and defence assets.

AS302: Industrial Applications of Corrosion Sensing

Dr Tony Trueman (DSTO) and Dr Scott Wade (Monash) Key activities of this project are to develop:

• sensors for assessing the level of corrosion of industrial infrastructure,
• sensors to determine environmental conditions that influence the rate of infrastructure corrosion,
• devices and applications for autonomous sensor monitoring equipment,
• methodology for autonomous remote monitoring of corrosion and environmental sensors,
• reports and document methods for installation of sensors in industrial environments,
• models and/or algorithms that will calculate corrosion rates from corrosion sensors, and
• model/s that will predict corrosion rates of metals from environmental monitor data.

Software packages are being developed that manage and use sensor data to generate corrosion related information for maintenance/management staff.

ID201: Integrated Decision Support System for Asset Management in the Water Utility Industry

Professor Lin Ma The overall objective of the project was to integrate asset management and maintenance information with business operational process and to support effective and economical decision-making. A major case study was undertaken within a water utility company.

The deliverables of the project are to:

• develop a methodology for identifying true data requirements and improving data quality for asset management of pumping stations,
• integrate on-line and portable data collection systems,
• develop a diagnosis package for complete analysis of assets, such as pump systems,
• develop hybrid reliability prediction models at scheme, system and sub-system levels,
• develop a dynamic demand management model to consider both supply and maintenance requirements, and to
• develop a module based decision support system for asset management .

ID204: Integration of MIMOSA Compliant Condition Monitoring Information with the Mainet™ Asset Management System

Professor Lin Ma (QUT) The objective of the project is to integrate MIMOSA compliant condition monitoring information with the MainnetTM asset management system by developing a software prototype. The software prototype will contain a vibration analysis tool for preliminary condition assessment of general rotating machines, e.g. pumps. An interface will be developed using Web Services to enable the MainetTM system accessing the produced condition information. The main oiutputs from the project are:

• a software prototype for integration of MIMOSA compliant condition monitoring information with the Mainet™ asset management system, which features an FFT based vibration analysis tool and a MIMOSA compliant database, and
• an interface with the Mainet™ system.

ID205: Pneumatic Conveying Pipeline Management System for Wear Minimisation

Professor Mark Jones ( Uni Newcastle) This project is investigated the following primary objectives:

• to focus on a wide rage of alumina types including secondary alumina and to include fly ash as a major additional material,
• to enhance modelling and experimental validation to cover dilute bulk solid and dense phase,
• to undertake on-site trials of models at both RTA and Delta Electricity for verification of both the dilute and dense phase models at full industrial scale, and
• to develop software algorithms to assist in the design and troubleshooting of pneumatic conveying pipeline systems to manage and minimise wear,

Further it will investigate how the software algorithm might be integrated into a wider AM based system.

ID206: Integrated Asset Health Manager (AHM)

Professor Lin Ma (QUT) This project is well on the way to delivering a set of models and know-how for asset health assessment and prediction in the form of a software prototype (AHM). Specific deliverables include:

• reporting on critical failure modes and effects analysis, data requirement tables for selected assets, and action guidelines for data collection/storage processes for industrial participants,
• practical solutions to requirements for improving the SAP PM application towards better asset health assessment and life prediction,
• methodologies for asset health assessment based on condition monitoring data,
• failure and reliability analysis models at the component level, including models for combined condition and failure data analysis.
• Reliability analysis and prediction models at the system level.

Service oriented software modules and functional prototypes for selected asset systems.

D207: Health Monitoring System for Civil Infrastructure in Operational Environments

Professor Hong Hao (UWA) The project is developing an integrated health monitoring framework for civil infrastructure The deliverables of the project are to:

• embed piezoelectric sensing technology for damage detection,
• develop in-operation system identification techniques for civil infrastructure in varying environments,
• develop stochastic deterioration and damage models and an evaluation methodology by integrating the damage identification with reliability analysis and risk assessment,
• develop risk-based methods to optimise remaining service life or minimise maintenance or repair costs,
• develop a software package to use sensor data to evaluate the condition of civil infrastructure,
• report on data quality at point of generation and define processes for establishing data quality, and
• identity and review software options that ensure data quality addressing management issues such as transactional, organisational, technical and cultural.

ID208: Utilisation of Condition Monitoring/Diagnostics Software for Low Speed Machinery

Professor Andy Tan (QUT) Utilisations of a range of condition monitoring / diagnostics (CMD) techniques are being studied for low speed machinery generated. The project will:

• validate techniques developed on site at Rio Tinto Alcan an Gladstone,
• implement and enhance the CMD software by incorporating automatic diagnostics and by optimizing the signal processing to minimize the human involvement,
• build an on-line data acquisition system and install it on site machinery for continuous data acquisition via the web, and
• conduct further experimental tests on a custom built low speed test rig to characterise statistical baselines and fault information.

The outputs from this research will significantly improve maintenance efficiency and provide a safer and reliable operation which could eventually lead to massive saving in maintenance cost, increase machine usage and productivity.

ID301: Gas Turbine Asset Management

Dr Maxine Watson (MPT) The outputs from this project are to:

• develop an asset management system for hot gas path parts in industrial turbines,
• develop algorithms or techniques for gas turbine component fault progression/trending analysis and diagnosis/prognosis, and to
• document Gas Turbine Asset Management processes incorporating critical IP related to life/health assessment algorithms for critical hot gas components and coating systems, and advanced condition monitoring algorithm based upon data fusion techniques.

ID302: Transformer Remnant Life Estimation

Professors Gerard Ledwich (QUT), Jie pan (UWA) and Syed Islam (CUT) This project is developing non-destructive on-line monitoring techniques to assess the thermal, electrical and/or insulation ageing of power transformers, through various activities to:

• conduct a technology scoping study of currently available on-line techniques for condition monitoring,
• develop a transformer rate of ageing model to determine thermal, electrical and insulation criticalities,
• development of a remnant life-estimation model based on rate of ageing and snapshot monitoring data,
• development of an electrical-mechanical-acoustical model of a transformer system to relate the electro-magnetic excitation to the vibro-acoustical response,
• develop a transformer remnant life estimation model,
• testing models on an existing fleet of transformers based on available historical data,
• acquire data on a selected fleet of transformers using varied off-line and on-line measurement techniques,
• design and test the vibro-acoustic sensing and condition monitoring system, and
• applying the above to test a remnant life estimation model.

ID304: Development of integrated wear-fatigue-lubrication model for assessment of rail-wheel degradation & operational risks

Professor Gopi Chattopadhyay (CQU) This proposed research has developed a decision model based on predicted operational risks, with a view to establishing economic strategies for lubrication and grinding, inspection and rail replacements. Main outputs of this project are to:

• development of integrated wear-fatigue-lubrication models for predicting degradation for various curves, tonnage and traffic conditions,
• development of economic models and risk analysis for informed strategic decisions related to rail/wheel maintenance decision and operational risks, and
• assist the rail industry to reduce risk of derailment, enhance rail and wheel life, enhance knowledge of the most appropriate lubricants and provide information for smart industry procurement (eg. of lubricants).

SI101: Data Quality for Asset Management

Professor Andy Koronios (Uni SA) This project has delivered the following outputs:

• data quality assessments, complemented by recommended quality management practices to improve data collection and error checking as early as possible,
• domain-specific business rule catalogues for data cleaning,
• decision guide for choosing data cleaning tools under given quality problems,
• open problem list such as weakness and deficiencies of current data cleansing tools , and
• Data Quality Models and Frameworks.

SI102: Automated Configuration Management

Professor Andy Koronios (Uni SA) The deliverables from this project are:

• a framework for configuration management in a manufacturing enterprise, and
• a system through which a smart tag, attached to an asset, is read by a reader that has the ability to monitor and track both the passage and direction of the asset.

SI104: Maritime Systems Division Data Management and Exploitation (Transactional and Configurational)

Professor Andy Koronios (Uni SA) Two areas for outputs have been broadly identified as configurational and transactional. The project will produce specific deliverables covering the following issues:

1. Advise and recommendations on data requirements that need consideration in a database that support asset management tools and decision aids, namely:
   1. guidance for improved AMPS data quality with respect to: definition, cleansing, reliability, redundancy, priority and criticality, portability and security.
   2. report on data cleansing software and methods specific to information migration between inter- and intra- SPO systems.
2. Recommendations for the improvement of AMPS data flow and connectivity to support cost and performance analysis.
3. Recommendations on data flow process (concentrating on MSD systems) for financial and performance information for a specified Defence dataset.
4. Advice on and development of data analysis tools with specific reference to form, precision, accuracy, etc.
5. Assess and report on data quality at point of generation and define processes for establishing data quality and the implementation of data quality and software quality options.

SI203: Wireless Prognostics – Wireless capture of condition and operational environment data for real time fault detection and maintenance management

Professor Bruce Thomas (Uni SA) This project utilises embedded system technologies to develop a suite of application prototypes, initially linked into project AS302, by developing:

• A sensing the operating environment of an asset for critical variables such as temperature, pressures, humidity etc.,
• plug and play interface to analogue sensors,
• embedding health and maintenance history of an asset with the asset so that it carries the same throughout its life cycle,
• a sensor network to improve detection of failure and tracking of reliability and environmental risks,
• decision support modules for condition assessment and trend analysis, based on the data captured through ‘a’ and ‘b’ abov,
• open systems compliant remote online condition monitoring,
• an end to end integrated supply chain visibility of spares,
• a state of the art miniaturised sensory device that is capable of providing an integrated data acquisition system for condition monitoring to detect failure condition in its developing state.
• a mechanism for an integrated supply chain management, one in which information is available to all the partners of the supply chain, and logistics of an item are traceable at any stage.

SI204: Asset Management Data Analysis, Verification & Enrichment System

Professor Andy Koronios (Uni SA) This project is an extension of a Data Quality project and will use some of its outputs to:

• develop a data analysis, verification, enrichment suite of software applications and will draw upon the functional specifications for data quality in asset management information and data objects,
• design, develop, test and evaluate a suite of integrated software components, and
• develop an integrated system that will focus on providing insightful information about the quality of the data repositories in asset management organizations and greatly assist in data quality efforts in improving data quality in asset management information systems.

SI205: Integrated Information Model for Community Infrastructure and Asset Management

Professors Andy Koronios and Arun Kumar The objectives of the project are to:

• identify information requirements by local government organisations,
• identify third party agency informational requirements and data formats for reports,
• identify the level of consistency between measurement and recording practices,
• develop an “Integrated Information Framework” to establish a methodology and ontology for the exchange of community based asset data,
• develop an harmonised interface with spatial modelling standards (ICSM Spatial Reference Model) and Architectural and Civil Engineering (ACE) modelling standards (IAI IFC models), and
• Develop a model server to support the interoperable exchange of information between councils and other users, including shared service components and the extraction of data from backend systems.

SI302: Improved OPAL Monitoring and Management system

Professor Markus Stumptner (Uni SA) The project specification is deliver specific deliverables by developing:

• a specification and implementation of data transfer (likely to including notification execution) between 3D Model and SAP,
• and reporting on new system interfaces between OPAL monitoring systems, ANSTO reporting systems and third party systems (e.g., RMS),
• and reporting on data streams produced by OPAL and analyse data aggregation/warehousing options
• a comparative report of commercial condition monitoring tools, e.g. Definition of Model fragments for monitoring system, experiment outcomes with model fragments based on prototype implementation,
• a specification of Operational Limits and Conditions for implementation of a regulatory compliance checker.
• a specification for DW solution to be implemented and based on standard technology.
• and using frameworks to develop a condition monitoring description as a receptacle for other types of descriptions (other analysis methods) to build a specification for a library of models,
• a design and implement data transfers based on service-oriented protocols, and
• Implement a prototype regulatory compliance checker.

HD102: Development of a Toolbox of Best Practice Management tools for Australian Asset Management

Dr Howard Harris (Uni SA) The objectives of the project are to:

• develop guidelines for a series of best practice asset management tools which are relevant to the needs and maturity of Australian firms (initially CIEAM members), and
• develop the tools and conduct workshops for industry participants.

HD103: Strategic Work Design in Engineering Asset Environments

Drs Glen Murphy and Artemis Chang The aim of this project is to develop a strategic framework for the management of human resources operating in engineering asset (EA) intensive environments, and will provide the focal point for human factors in data quality, engineering information packaging and dissemination, and the management of culture change within EA organisations, and has the following objectives:

• Develop and test a multi-level model of data quality antecedents.
• Investigate, test and pilot optimum forms of implementing an “Integrated Asset Health Manager”.
• Investigate information feedback requirements of user categories, such as operators.
• Develop a contingency model of information packaging and dissemination.
• Develop a theoretical framework identifying the facilitators of culture change.
• Pilot and test the culture change model, and develop implementation strategies for industry.

HD201: Developing Maturity Measurement for Engineering Asset Management

Professor Peter Smith (CQU) The objectives of the project are to:

• develop a valid, rigorous and useful asset management maturity measure,
• assist industry to systematically assess asset management processes, to prioritize process improvements, and to direct resources appropriately, and to
• provide a common framework for measurement and benchmarking of best practice in asset management.

HD204: Asset performance: impact of stewardship and governance strategies

Dr Stephane Tywoniak This research project investigated;

• the proposition that the appropriate ‘high performance’ governance structure for an asset category is contingent on the centrality of the asset category in divisional business models,
• an asset category has varying degrees of centrality in different divisional business models in a large multi-divisional organisation,
• the determination of best management strategy for a mix of centralised and divisional control, and
• undertaking a pilot study of management and performance of a fleet of mobile assets.

HD505: Maritime Systems Division Materiel Logistics Strategy Development

Dr Peter Lambrineas (DSTO) The principal objectives of this project are to;

• Develop a gap analysis of the applicability and utility of currently existing generic EAM frameworks for organisations wishing to develop an engineering asset management strategy,
• Develop a strategy template for the management of science & technology research within a complex engineering asset environment,
• establish the requirements for a best practice computerised maintenance management systems as part of an integrated engineering asset management framework, and
• develop a “future directions” ten year Material Logistics Strategy for MSD.