Melinda Hodkiewicz

Estimating Mean Residual Life for a Case Study of Rail Wagon Bearings

This paper develops a prognostics model to estimate the Mean Residual Life of Rail Wagon Bearings within certain confidence intervals. The prognostics model is constructed using a Proportional Hazards approach, informed by imperfect data from a bearing acoustic monitoring system, and a failure database. The model supports prediction within a defined maintenance planning window from the time of receipt of the latest acoustic condition monitoring information. We use the model to decide whether to replace a bearing, or leave it until collection of the next condition monitoring indicators. The model is tested on a limited number of cases, and demonstrates good predictive capability. Opportunities to improve the performance of the model are identified, and the processes necessary and time required to build the model are described. Lessons learned from dealing with real field data will assist those interested in using prognostics to support maintenance planning activities.

IoT-Based Prognostics and Systems Health Management for Industrial Applications

Prognostics and systems health management (PHM) is an enabling discipline that uses sensors to assess the health of systems, diagnoses anomalous behavior, and predicts the remaining useful performance over the life of the asset. The advent of the Internet of Things (IoT) enables PHM to be applied to all types of assets across all sectors, thereby creating a paradigm shift that is opening up significant new business opportunities. This paper introduces the concepts of PHM and discusses the opportunities provided by the IoT. Developments are illustrated with examples of innovations from manufacturing, consumer products, and infrastructure. From this review, a number of challenges that result from the rapid adoption of IoT-based PHM are identified. These include appropriate analytics, security, IoT platforms, sensor energy harvesting, IoT business models, and licensing approaches.

Goal Hierarchy: Improving Asset Data Quality by Improving Motivation

Many have recognized the need for high quality data on assets and the problems in obtaining them, particularly when there is a need for human observation and manual recording. Yet very few have looked at the role of the data collectors themselves in the data quality process. This paper argues that there are benefits to more fully understanding the psychological factors that lay behind data collection and we use goal hierarchy theory to understand these factors. Given the myriad of potential reasons for poor-quality data it has previously proven difficult to identify and successfully deploy employee-driven interventions; however, the goal hierarchy approach looks at all of the goals that an individual has in their life and the connections between them. For instance, does collecting data relate to whether or not they get a promotion? Stay safe? Get a new job? and so on. By eliciting these goals and their connections we can identify commonalities across different groups, sites or organizations that can influence the quality of data collection. Thus, rather than assuming what the data collectors want, a goal hierarchy approach determines that empirically. Practically, this supports the development of customized interventions that will be much more effective and sustainable than previous efforts.

The effect of change in flow rate on the vibration of double-suction centrifugal pumps

Abstract This investigation identifies changes in the character of vibration measured on a pump bearing housing resulting from flow below the best efficiency point for industrial double-suction single-stage units with different wear conditions. The paper develops a set of vibration features that will assist in identifying low flow conditions in double-suction pumps.

A conceptual framework and practical guide for assessing fitness-to-operate in the offshore oil and gas industry.

The paper outlines a systemic approach to understanding and assessing safety capability in the offshore oil and gas industry. We present a conceptual framework and assessment guide for understanding fitness-to-operate (FTO) that builds a more comprehensive picture of safety capability for regulators and operators of offshore facilities. The FTO framework defines three enabling capitals that create safety capability: organizational capital, social capital, and human capital. For each type of capital we identify more specific dimensions based on current theories of safety, management, and organizational processes. The assessment guide matches specific characteristics to each element of the framework to support assessment of safety capability. The content and scope of the FTO framework enable a more comprehensive coverage of factors that influence short-term and long-term safety outcomes.

A Framework to Assess Data Quality for Reliability Variables

This paper presents a framework for assessing the impact of the data collection process on the validity of key measures in reliability. The quality of data is affected by many organisational and behavioural factors. The aims of developing this framework are to (1) identify inputs/steps that have the most significant impact on the quality of key performance indicators such as MTTF (mean time to failure) and MTTR (mean time to repair), (2) identify ‘weak’ links in the data collection process, and (3) identify potential remedial actions. Development of this framework will assist the understanding of assumptions used in reliability calculations and improve the quality of underlying data and the data collection process. Consequently, this is a vital step in the continued development and use of data based decision-making models for reliability assessment.

A vibration cavitation sensitivity parameter based on spectral and statistical methods

Octave band analysis and PCA used on RMS velocity to obtain key indicators.Mahalanobis distance is used to set thresholds since data is normally distributed.Pump health separated into no cavitation, incipient, and fully formed condition.Method works on a range of types and sizes of centrifugal pumps. Cavitation is one of the main problems reducing the longevity of centrifugal pumps in industry today. If the pump operation is unable to maintain operating conditions around the best efficiency point, it can be subject to conditions that may lead to vaporisation or flashing in the pipes upstream of the pump. The implosion of these vapour bubbles in the impeller or volute causes damaging effects to the pump. A new method of vibration cavitation detection is proposed in this paper, based on adaptive octave band analysis, principal component analysis and statistical metrics. Full scale industrial pump efficiency testing data was used to determine the initial cavitation parameters for the analysis. The method was then tested using vibration measured from a number of industry pumps used in the water industry. Results were compared to knowledge known about the state of the pump, and the classification of the pump according to ISO 10816.

Are managerial pressure, technological control and intrinsic motivation effective in improving data quality?

Can data collectors be “pushed” into collecting high quality data or would being “pulled” be more effective? This paper finds that managers should be careful of the degree to which “push” factors, such as managerial pressure and technological input control, are relied upon. While they may be helpful for motivating those data collectors who are not intrinsically motivated, they are either not helpful or may discourage those data collectors who are intrinsically motivated. Instead, self-concordance may act as a longer-term, more stable approach to increasing the motivation of data collectors and thus increasing the quality of data that enter reliability systems. This study uses a sequential mixed-method approach involving interviews with 20 data collectors and a quantitative survey of 109 data collectors in a water utility. It examines the interactive effect of managerial pressure, technological input control and self-concordance on data collection performance.

Challenges and Opportunities for Simulation Modelling Integrating Mine Haulage and Truck Shop Operations

This paper discusses ongoing research to formulate, develop and test a reliability assessment model (GenRel) based on genetic algorithms (GAs). GAs are powerful and broadly applicable stochastic search techniques based on the principles of natural selection, heredity and genetics. The reason for selecting GAs is the fact that the reliability of mining equipment changes over time due to its dependence upon several covariates/factors (e.g. equipment age, operating environment, number and quality of repairs). These factors combine to create a complex impact on a piece of equipments reliability function. This impact encapsulates and inherits to some degree the individual characteristics of the factors as they evolve over time. 1 BestFit, Palisade Decision Tools (http://www.palisade.com/html/bestfit.asp) Theoretical probability distributions are commonly used to fit equipment failure data. GenRel uses the exponential probability distribution as its engine to generate predictive patterns based upon historical failure data. Overall, this paper suggests a methodology for applying GAs for reliability assessment of mining equipment. An example is given to demonstrate the effectiveness of using GAs in reliability studies. The research discussed in this paper was carried out by the Laurentian University Mining Automation Laboratory (LUMAL).This paper discusses ongoing research to formulate, develop and test a reliability assessment model (GenRel) based on genetic algorithms (GAs). GAs are powerful and broadly applicable stochastic search techniques based on the principles of natural selection, heredity and genetics. The reason for selecting GAs is the fact that the reliability of mining equipment changes over time due to its dependence upon several covariates/factors (e.g. equipment age, operating environment, number and quality of repairs). These factors combine to create a complex impact on a piece of equipments reliability function. This impact encapsulates and inherits to some degree the individual characteristics of the factors as they evolve over time. 1 BestFit, Palisade Decision Tools (http://www.palisade.com/html/bestfit.asp) Theoretical probability distributions are commonly used to fit equipment failure data. GenRel uses the exponential probability distribution as its engine to generate predictive patterns based upon historical ...

A Cost–Benefit Analysis of Electric Loaders to Reduce Diesel Emissions in Underground Hard Rock Mines

With recent developments in understanding the adverse health effects of diesel particulate matter (DPM) and growing emphasis on sustainability, zero-emission electric vehicles are becoming an increasingly common option in underground mining systems. As exposure regulations become stricter and with potential savings in the cost of ventilation, fuel, and consumables, there is also rising economic incentive to consider alternatives to diesel machinery. As a result, the diesel-electric debate is fundamental to any underground mining companys triple bottom line. A cost-benefit analysis for electric load haul dump units (eLHDs) was conducted in the context of Western Australian underground hard rock mines. This included a review of the issues affecting the diesel-electric debate and the development of a parametric life-cycle-cost model. The results indicate that eLHDs are not yet a universal solution to all underground mining systems. eLHDs can offer lower operating costs and do contribute many qualitative benefits, particularly with respect to reduced exposure to DPM. However, they also have several drawbacks, primarily associated with trailing cable management. Nevertheless, with a suitable mine design, eLHDs are a viable option and could provide a pathway for zero-emission electric machinery in the Australian mining industry. Preamble -Western Australia is one of the worlds leading mineral provinces. In the 2012-2013 financial year, Western Australias mineral and petroleum sales totaled A