The effective management of geological risk in long-term production scheduling of open pit mines

Investment in mining projects, like most business investment, is susceptible to risk and uncertainty. The ability to effectively identify, assess and manage risk may enable strategic investments to be sheltered and operations to perform closer to their potential. In mining, geological uncertainty is seen as the major contributor to not meeting project expectations. The need to assess and manage geological risk for project valuation and decision-making translates to the need to assess and manage risk in any pertinent parameter of open pit design and production scheduling. This is achieved by taking geological uncertainty into account in the mine optimisation process. This thesis develops methods that enable geological uncertainty to be effectively modelled and the resulting risk in long-term production scheduling to be quantified and managed. One of the main accomplishments of this thesis is the development of a new, risk-based method for the optimisation of long-term production scheduling. In addition to maximising economic returns, the new method minimises the risk of deviating from production forecasts, given the understanding of the orebody. This ability represents a major advance in the risk management of open pit mining.

Maintenance strategies affecting equipment performance

Proper maintenance of plant items is crucial for the safe and profitable operation of process plants, The relevant maintenance policies fall into the following four categories: (i) preventivejopportunistic/breakdown replacement policies, (ii) inspection/inspection-repair-replacernent policies, (iii) restorative maintenance policies, and (iv) condition based maintenance policies, For correlating failure times of component equipnent and complete systems, the Weibull failure distribution has been used, A new powerful method, SEQLIM, has been proposed for the estimation of the Weibull parameters; particularly, when maintenance records contain very few failures and many successful operation times. When a system consists of a number of replaceable, ageing components, an opporturistic replacernent policy has been found to be cost-effective, A simple opportunistic rrodel has been developed. Inspection models with various objective functions have been investigated, It was found that, on the assumption of a negative exponential failure distribution, all models converge to the same optimal inspection interval; provided the safety components are very reliable and the demand rate is low, When deterioration becomes a contributory factor to same failures, periodic inspections, calculated from above models, are too frequent, A case of safety trip systems has been studied, A highly effective restorative maintenance policy can be developed if the performance of the equipment under this category can be related to some predictive modelling. A novel fouling model has been proposed to determine cleaning strategies of condensers, Condition-based maintenance policies have been investigated. A simple gauge has been designed for condition monitoring of relief valve springs. A typical case of an exothermic inert gas generation plant has been studied, to demonstrate how various policies can be applied to devise overall maintenance actions.

Analytic hierarchy process analyses risk of operating cross-country petroleum pipelines in India

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Decision-making in product quality based on failure knowledge

Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

Understanding the risk of hypoglycaemia in older individuals with diabetes

Introduction: Although older individuals are more prone to hypoglycaemia, it is not known if they have sufficient understanding of the risks of hypoglycaemia or the factors that predispose to it. We evaluated the effectiveness of hypoglycaemia education and examined the factors that increased susceptibility to hypoglycaemia among older people with diabetes. Methods: Forty-five patients (male/female) aged >65 years and known to have diabetes were identified through outpatient clinics at a secondary care hospital. Information relating to education received, awareness of hypoglycaemia and associated risk factors was collected using a standard questionnaire. Additionally, data regarding demographics, treatment regimes, patient attitudes, hypoglycaemic awareness and risks and barriers to self-management of diabetes was collected. Patients were categorised as low, moderate and high risk based on their responses. Independent sample t-tests and Analysis of Variance were carried out to identify factors contributing to high hypoglycaemic risk. Results: Overall, 70% of the patients reported receiving education about hypoglycaemia from health professionals and 95% of them reported good understanding of hypoglycaemia and were able to self-test. Proportion of women receiving education was, however, lower than men (52% women versus 88% men). Compared with men, women were less likely to recognise (59 versus 73%), or act appropriately to a hypoglycaemic episode (59 versus 78%). The mean number of hypoglycaemic episodes per year (41 versus 12) and the duration of hypoglycaemia (9.9 versus 6.3 min) was also greater among women compared with men. The duration of diabetes (P = 0.018), female gender, type 1 diabetes (0.002) and lack awareness of medications causing hypos (P = 0.006) were strong predictors of hypoglycaemia risk. Conclusions: There are significant gaps in education around hypoglycaemia in older people with diabetes. Women, people with longer duration and type 1 diabetes in particular, need additional attention and future educational initiatives need to address these issues.  

A kockázat szerepe a könyvvizsgálatban = The role of risk in external audits

A tanulmány a kockázatnak és a kockázatok felmérésének az éves beszámolók (pénzügyi kimutatások) könyvvizsgálatban betöltött szerepével foglalkozik. A modern könyvvizsgálat – belső és külső korlátainál fogva – nem létezhet a vizsgált vállalkozás üzleti kockázatainak felmérése nélkül. Olyannyira igaz ez, hogy a szakma alapvető szabályait lefektető nemzeti és nemzetközi standardok is kötelező jelleggel előírják az ügyfelek üzleti kockázatainak megismerését. Mindez nem öncélú tevékenység, hanem éppen ez jelenti a könyvvizsgálat kiinduló magját: a kockázatbecslés – a tervezés részeként – az audit végrehajtásának alapja, és egyben vezérfonala. A szerző először bemutatja a könyvvizsgálat és a kockázat kapcsolatának alapvonásait, azt, hogy miként jelenik meg egyáltalán a kockázat problémája a könyvvizsgálatban. Ezt követően a különféle kockázatalapú megközelítéseket tárgyalja, majd néhány főbb elem kiragadásával ábrázolja a kockázatkoncepció beágyazódását a szakmai szabályozásba. Végül – mintegy az elmélet tesztjeként – bemutatja a kockázatmodell gyakorlati alkalmazásának néhány aspektusát. ______ The study examines the role of risk and the assessment of risks in the external audit of financial statements. A modern audit – due to its internal and external limitations – cannot exist without the assessment of the business risk of the entity being audited. This is not a l’art pour l’art activity but rather the very core of the audit. It is – as part of the planning of the audit – a guideline to the whole auditing process. This study has three main sections. The first one explains the connection between audit and risk, the second discusses the different risk based approaches to auditing and the embeddedness of the risk concept into professional regulation. Finally – as a test of theory – some practical aspects of the risk model are discussed through the lens of former empirical research carried out mostly in the US. The conclusion of the study is that though risk based models of auditing have many weaknesses they still result in the most effective and efficient high quality audits.

Availability estimation and management for complex processing systems

“Availability” is the terminology used in asset intensive industries such as petrochemical and hydrocarbons processing to describe the readiness of equipment, systems or plants to perform their designed functions. It is a measure to suggest a facility’s capability of meeting targeted production in a safe working environment. Availability is also vital as it encompasses reliability and maintainability, allowing engineers to manage and operate facilities by focusing on one performance indicator. These benefits make availability a very demanding and highly desired area of interest and research for both industry and academia. In this dissertation, new models, approaches and algorithms have been explored to estimate and manage the availability of complex hydrocarbon processing systems. The risk of equipment failure and its effect on availability is vital in the hydrocarbon industry, and is also explored in this research. The importance of availability encouraged companies to invest in this domain by putting efforts and resources to develop novel techniques for system availability enhancement. Most of the work in this area is focused on individual equipment compared to facility or system level availability assessment and management. This research is focused on developing an new systematic methods to estimate system availability. The main focus areas in this research are to address availability estimation and management through physical asset management, risk-based availability estimation strategies, availability and safety using a failure assessment framework, and availability enhancement using early equipment fault detection and maintenance scheduling optimization.

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.

Percutaneous insertion of Dual Growth Rods using a new mobile bearing implant

Growth rods are commonly used for the treatment of scoliosis in the immature spine. Many variations have been proposed but breakage of implants is a common problem. Growth rod insertion commonly involves large exposures at initial insertion followed by multiple smaller procedures for lengthening. We present our early experiences using a percutaneous technique of insertion of a new titanium mobile bearing implant (Medtronic Inc). The implant allows some rotatory motion in the middle of the construct thus reducing construct stresses and thus possibly reducing rod breakage risk. Based on this small initial series with 12 months follow-up, percutaneous insertion of growth rods using the new implant is a safe and reliable technique although the infection rate in our sample was of note. This may be related to the titanium wear and inflammation seen in the soft tissues at time of operation and visualised on histology. No implants have required removal due to infection, and all infections were treated with debridement at next lengthening and suppressive antibiotics. Propionibacterium is one of the commonest infections seen with spinal implants and sometimes does not respond to simple antibiotic suppression. The technique allows preservation of the soft tissues until definitive fusion is needed and may lead to a decrease in hospital stay. The implant is low profile and seems to offer advantages over other systems on the market. Further follow up is needed to look at longer term outcomes with this new implant type.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Understanding how to enhance business creativity

This PhD study examines some of what happens in an individual’s mind regarding creativity during problem solving within an organisational context. It presents innovations related to creative motivation, cognitive style and framing effects that can be applied by managers to enhance individual employee creativity within the organisation and thereby assist organisations to become more innovative. The project delivers an understanding of how to leverage natural changes in creative motivation levels during problem solving. This pattern of response is called Creative Resolve Response (CRR). The project also presents evidence of how framing effects can be used to influence decisions involving creative options in order to enhance the potential for managers get employees to select creative options more often for implementation. The study’s objectives are to understand: • How creative motivation changes during problem solving • How cognitive style moderates these creative motivation changes • How framing effects apply to decisions involving creative options to solve problems • How cognitive style moderate these framing effects The thesis presents the findings from three controlled experiments based around self reports during contrived problem solving and decision making situations. The first experiment suggests that creative motivation varies in a predictable and systematic way during problem solving as a function of the problem solver’s perception of progress. The second experiment suggests that there are specific framing effects related to decisions involving creativity. It seems that simply describing an alternative as innovative may activate perceptual biases that overcome risk based framing effects. The third experiment suggests that cognitive style moderates decisions involving creativity in complex ways. It seems that in some contexts, decision makers will prefer a creative option, regardless of their cognitive style, if this option is both outside the bounds of what is officially allowed and yet ultimately safe. The thesis delivers innovation on three levels: theoretical, methodological and empirical. The highlights of these findings are outlined below: 1. Theoretical innovation with the conceptualisation of Creative Resolve Response based on an extension of Amabile’s research regarding creative motivation. 2. Theoretical innovation linking creative motivation and Kirton’s research on cognitive style. 3. Theoretical innovation linking both risk based and attribute framing effects to cognitive style. 4. Methodological innovation for defining and testing preferences for creative solution implementation in the form of operationalised creativity decision alternatives. 5. Methodological innovation to identify extreme decision options by applying Shafir’s findings regarding attribute framing effects in reverse to create a test. 6. Empirical innovation with statistically significant research findings which indicate creative motivation varies in a systematic way. 7. Empirical innovation with statistically significant research findings which identify innovation descriptor framing effects 8. Empirical innovation with statistically significant research findings which expand understanding of Kirton’s cognitive style descriptors including the importance of safe rule breaking. 9. Empirical innovation with statistically significant research findings which validate how framing effects do apply to decisions involving operationalised creativity. Drawing on previous research related to creative motivation, cognitive style, framing effects and supervisor interactions with employees, this study delivers insights which can assist managers to increase the production and implementation of creativity in organisations. Hopefully this will result in organisations which are more innovative. Such organisations have the potential to provide ongoing economic and social benefits.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Definition of airworthiness categories for civil Unmanned Aircraft Systems (UAS)

This paper introduces a novel strategy for the specification of airworthiness certification categories for civil unmanned aircraft systems (UAS). The risk-based approach acknowledges the fundamental differences between the risk paradigms of manned and unmanned aviation. The proposed airworthiness certification matrix provides a systematic and objective structure for regulating the airworthiness of a diverse range of UAS types and operations. An approach for specifying UAS type categories is then discussed. An example of the approach, which includes the novel application of data-clustering algorithms, is presented to illustrate the discussion.

Testing a tri-partite contingent model of engineering cultures : a pilot study

For some time there has been a growing awareness of organizational culture and its impact on the functioning of engineering and maintenance departments. Those wishing to implement contemporary maintenance regimes (e.g. condition based maintenance) are often encouraged to develop “appropriate cultures” to support a new method’s introduction. Unfortunately these same publications often fail to specifically articulate the cultural values required to support those efforts. In the broader literature, only a limited number of case examples document the cultural values held by engineering asset intensive firms and how they contribute to their success (or failure). Consequently a gap exists in our knowledge of what engineering cultures currently might look like, or what might constitute a best practice engineering asset culture. The findings of a pilot study investigating the perceived ideal characteristics of engineering asset cultures are reported. Engineering managers, consultants and academics (n=47), were surveyed as to what they saw were essential attributes of both engineering cultures and engineering asset personnel. Valued cultural elements included those orientated around continuous improvement, safety and quality. Valued individual attributes included openness to change, interpersonal skills and conscientiousness. The paper concludes with a discussion regarding the development of a best practice cultural framework for practitioners and engineering managers.