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Engineering asset management encompasses all types of engineered assets including built environment, infrastructure, plant, equipment, hardware systems and components. Following the release of ISO 5500x set of standards, the 9th WCEAM addresses the hugely important issue of what constitutes the body of knowledge in Engineering Asset Management. Topics discussed by Congress delegates are grouped into a number of tracks including strategies for investment and divestment of assets, operations and maintenance of assets, assessments of assets condition, risk and vulnerability, technologies and systems for management of asset, standards, education, training and certification. These proceedings include a sample of the wide range of topics presented during the 9th World Congress on Engineering Asset Management in Pretoria South Africa 28 – 31 October, 2014 and complements other emerging publications and standards that embrace the wide ranging issues concerning the management of engineered physical assets.
Two types of rolling-element bearings representing radial loaded and thrust loaded bearings were used for this study. Three hundred forty (340) virtual bearing sets totaling 31400 bearings were randomly assembled and tested by Monte Carlo (random) number generation. The Monte Carlo results were compared with endurance data from 51 bearing sets comprising 5321 bearings. A simple algebraic relation was established for the upper and lower L(sub 10) life limits as function of number of bearings failed for any bearing geometry. There is a fifty percent (50 percent) probability that the resultant bearing life will be less than that calculated. The maximum and minimum variation between the bearing resultant life and the calculated life correlate with the 90-percent confidence limits for a Weibull slope of 1.5. The calculated lives for bearings using a load-life exponent p of 4 for ball bearings and 5 for roller bearings correlated with the Monte Carlo generated bearing lives and the bearing data. STLE life factors for bearing steel and processing provide a reasonable accounting for differences between bearing life data and calculated life. Variations in Weibull slope from the Monte Carlo testing and bearing data correlated. There was excellent agreement between percent of individual components failed from Monte Carlo simulation and that predicted.Vlcek, Brian L. and Hendricks, Robert C. and Zaretsky, Erwin V.Glenn Research CenterBALL BEARINGS; ROLLER BEARINGS; MONTE CARLO METHOD; THRUST BEARINGS; FATIGUE LIFE; FATIGUE TESTS; SIMULATION; WEIBULL DENSITY FUNCTIONS; FAILURE; CONFIDENCE LIMITS
Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards. This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China. Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.