Organizational, direct support and general support maintenance manual : loader, scoop type, DED, 4x4 articulated, frame steer, 2-1/2 cubic yard, bucket (CCE) airborne/airmobile Caterpillar model 950BNS, non-sectionalized, NSN 3805-01-126-7915, Caterpillar model 950BS, sectionalized, NSN 3805-01-126-7914.

Vol. 2 title: Organizational, direct support and general support maintenance manual including supplemental operating, maintenance and repair parts instructions (SOMARPI): loader, scoop type, DED, 4x4 articulated, frame steer, 2-1/2 cubic yard, bucket (CCE) airborne/airmobile Caterpillar model 950BNS, non-sectionalized, NSN 3805-01-126-7915, Caterpillar model 950BS, sectionalized, NSN 3805-01-126-7914.

Market Structures in Air Conditioning Maintenance Activity

It is questionable whether activities like construction, including maintenance and repair, can be considered a single entity or industry - on the basis that different sectors of construction/maintenance use fundamentally distinct resource and skill bases. This creates a number of issues including the development of competition and reform policy. de Valance deployed the Structure-Conduct-Performance model (SCP) to delineate sectors of new/installation construction activity and, in doing so, proposes that there exists multiple market structures in a given project. The purpose of this paper is to apply the SCP model to a different sector of construction activity, that is air conditioning maintenance and test de Valance's proposition concerning the existence of multiple market structures in a supply chain but this time to a built facility. The research method combines secondary data concerning the "Structure" component of the SCP model and primary data with regard to the "Conduct" and "Performance" parts of the SCP model. The results provide further support (beyond de Valance's analysis of new/installation activity) that a sector system approach using the SCP model is a more effective way to analyse market structures in construction activity. This paper also supports de Valance's proposition concerning the existence of multiple market structures in a supply chain to a project/facility.

Final : report assessing risk and variation in maintenance and rehabilitation costs for road network

This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Failure analysis of engineering systems with preventive maintenance and failure interactions

Optimal operation and maintenance of engineering systems heavily rely on the accurate prediction of their failures. Most engineering systems, especially mechanical systems, are susceptible to failure interactions. These failure interactions can be estimated for repairable engineering systems when determining optimal maintenance strategies for these systems. An extended Split System Approach is developed in this paper. The technique is based on the Split System Approach and a model for interactive failures. The approach was applied to simulated data. The results indicate that failure interactions will increase the hazard of newly repaired components. The intervals of preventive maintenance actions of a system with failure interactions, will become shorter compared with scenarios where failure interactions do not exist.

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.).

An assessment for cost effective maintenance and operation of the Callide Power Station electrical system, using reliability evaluation

The reliable operation of the electrical system at Callide Power Station is of extreme importance to the normal everyday running of the Station. This study applied the principles of reliability to do an analysis on the electrical system at Callide Power Station. It was found that the level of expected outage cost increased exponentially with a declining level of maintenance. Concluding that even in a harsh economic electricity market where CS Energy tries and push their plants to the limit, maintenance must not be neglected. A number of system configurations were found to increase the reliability of the system and reduce the expected outage costs. A number of other advantages were identified as a result of using reliability principles to do this study on the Callide electrical system configuration.

Classification of railway bridges based on criticality and vulnerability factors

Bridges are currently rated individually for maintenance and repair action according to the structural conditions of their elements. Dealing with thousands of bridges and the many factors that cause deterioration, makes this rating process extremely complicated. The current simplified but practical methods are not accurate enough. On the other hand, the sophisticated, more accurate methods are only used for a single or particular bridge type. It is therefore necessary to develop a practical and accurate rating system for a network of bridges. The first most important step in achieving this aim is to classify bridges based on the differences in nature and the unique characteristics of the critical factors and the relationship between them, for a network of bridges. Critical factors and vulnerable elements will be identified and placed in different categories. This classification method will be used to develop a new practical rating method for a network of railway bridges based on criticality and vulnerability analysis. This rating system will be more accurate and economical as well as improve the safety and serviceability of railway bridges.

Head and neck squamous-cell cancer and its association with polymorphic enzymes of xenobiotic metabolism and repair

Tobacco smoking, alcohol drinking, and occupational exposures to polycyclic aromatic hydrocarbons are the major proven risk factors for human head and neck squamous-cell cancer (HNSCC). Major research focus on gene-environment interactions concerning HNSCC has been on genes encoding enzymes of metabolism for tobacco smoke constituents and repair enzymes. To investigate the role of genetically determined individual predispositions in enzymes of xenobiotic metabolism and in repair enzymes under the exogenous risk factor tobacco smoke in the carcinogenesis of HNSCC, we conducted a case-control study on 312 cases and 300 noncancer controls. We focused on the impact of 22 sequence variations in CYP1A1, CYP1B1, CYP2E1, ERCC2/XPD, GSTM1, GSTP1, GSTT1, NAT2, NQO1, and XRCC1. To assess relevant main and interactive effects of polymorphic genes on the susceptibility to HNSCC we used statistical models such as logic regression and a Bayesian version of logic regression. In subgroup analysis of nonsmokers, main effects in ERCC2 (Lys751Gln) C/C genotype and combined ERCC2 (Arg156Arg) C/A and A/A genotypes were predominant. When stratifying for smokers, the data revealed main effects on combined CYP1B1 (Leu432Val) C/G and G/G genotypes, followed by CYP1B1 (Leu432Val) G/G genotype and CYP2E1 (-70G>T) G/T genotype. When fitting logistic regression models including relevant main effects and interactions in smokers, we found relevant associations of CYP1B1 (Leu432Val) C/G genotype and CYP2E1 (-70G>T) G/T genotype (OR, 10.84; 95% CI, 1.64-71.53) as well as CYP1B1 (Leu432Val) G/G genotype and GSTM1 null/null genotype (OR, 11.79; 95% CI, 2.18-63.77) with HNSCC. The findings underline the relevance of genotypes of polymorphic CYP1B1 combined with exposures to tobacco smoke.

Optimal maintenance and replacement via a semi-Markov decision model

Optimal bang-coast maintenance policies for a machine, subject to failure, are considered. The approach utilizes a semi-Markov model for the system. A simplified model for modifying the probability of machine failure with maintenance is employed. A numerical example is presented to illustrate the procedure and results.