A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.

Strategic Management Practices in the Construction Industry : a Dynamic Capabilities View

This book is an empirical study of strategic management practices in the construction industry. It examines the dynamic capabilities paradigm within the context of the Indonesian construction industry. The characteristics of asset-capability combinations were found to be significant determinants of the competitive advantage of the Indonesian construction enterprises, and that such advantage sequentially contributes to organizational performance. In doing so, this study fills an important gap in the empirical literature and reinforces the dynamic capabilities framework’s recognition as a rigorous theory of strategic management. As the dynamic capabilities framework can work in the context of Indonesia, it suggests that the framework has potential applicability in other emerging and developing countries

The impact of organisational culture on project selection : what is the appropriate culture type?

Project selection is a complex decision making process that is not merely influenced by the technical aspects of the project. Selection of road infrastructure projects in the Indonesian public sector is generally conducted at an organisational level, which involves multiple objectives, constraints and stakeholders. Hence, a deeper understanding of the various organisational drivers that impact on such decisions, in particular organisational culture, is much needed for improving decision-making processes as it has been posited by some researchers that organisational culture can become either an enabler, or a barrier, to the process. One part of the cultural assessment undertaken as part of the research, identifies and analyses the cultural types of relevant and involved organisations in the decision making process. The organisational culture assessment instrument (OCAI) of Cameron and Quinn (2011) was utilized in this study and the data was taken from three selected provinces in Indonesia. The results can facilitate the surveyed (and similar) organisations to improve their performance by moving towards a more appropriate cultural typology that is arguably better suited to their operations and to improving their organisational processes to more closely align with their organisational vision, mission and objectives.

Factors contributing to design-build (DB) project delivery system implementation in road infrastructure projects in Indonesia

Design-build (DB) project delivery systems have increasingly been adopted by many private and public sector organizations worldwide due to the many advantages offered on projects by such systems. However, many Indonesian road infrastructure projects are still delivered using the traditional design-bid-build (DBB) project delivery system. In order to provide evidence of the benefits of DB, it is essential to identify the factors that can contribute to successful DB implementation and this paper aims to provide evidence of such factors that can promote the successful implementation of DB project delivery systems on Indonesian road infrastructure projects. Four main factors and 28 indicators were identified from an extensive literature review, and a Delphi questionnaire survey was conducted amongst 20 experts drawn from the Indonesian road infrastructure construction sector. The first round Delphi study found that regulation, competency of clients, ability to manage DB projects and external conditions were the major factors that can promote successful DB implementation.

Functional and advanced functional and causal relationship diagrams for remote condition monitoring

Analysing the condition of an asset is a big challenge as there can be many aspects which can contribute to the overall functional reliability of the asset that have to be considered. In this paper we propose a two-step functional and causal relationship diagram (FCRD) to address this problem. In the first step, the FCRD is designed to facilitate the analysis of the condition of an asset by evaluating the interdependence (functional and causal) relationships between different components of the asset with the help of a relationship diagram. This is followed by the advanced FCRD (AFCRD) which refines the information from the FCRD into a comprehensive and manageable format. This new two-step methodology for asset condition monitoring is tested and validated for the case of a water treatment plant. © IMechE 2012.

Diesel knock combustion and its detection using acoustic emission

This paper presents an experimental investigation into the detection of excessive Diesel knock using acoustic emission signals. Three different dual-fuel Diesel engine operating regimes were induced into a compression ignition (Diesel) engine operating on both straight Diesel fuel and two different mixtures of fumigated ethanol and Diesel. The experimentally induced engine operating regimes were; normal, or Diesel only operation, acceptable dual-fuel operation and dual-fuel operation with excessive Diesel knock. During the excessive Diesel knock operating regime, high rates of ethanol substitution induced potentially damaging levels of Diesel knock. Acoustic emission data was captured along with cylinder pressure, crank-angle encoder, and top-dead centre signals for the different engine operating regimes. Using these signals, it was found that acoustic emission signals clearly distinguished between the two acceptable operating regimes and the operating regime experiencing excessive Diesel knock. It was also found that acoustic emission sensor position is critical. The acoustic emission sensor positioned on the block of the engine clearly related information concerning the level of Diesel knock occurring in the engine whist the sensor positioned on the head of the engine gave no indication concerning Diesel knock severity levels.

Diesel engine problems, acoustic emission signals and simulated misfire faults

This paper discusses commonly encountered diesel engine problems and the underlying combustion related faults. Also discussed are the methods used in previous studies to simulate diesel engine faults and the initial results of an experimental simulation of a common combustion related diesel engine fault, namely diesel engine misfire. This experimental fault simulation represents the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank-angle encoder and top-dead centre signals. Using these signals, it was possible to characterise the diesel engine in-cylinder pressure profiles and the effect of different combustion conditions on both vibration and acoustic emission signals.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

The role of organisational culture, trust and mechanisms in inter-project knowledge sharing

Knowledge has been recognised as a powerful yet intangible asset, which is difficult to manage. This is especially true in a project environment where there is the potential to repeat mistakes, rather than learn from previous experiences. The literature in the project management field has recognised the importance of knowledge sharing (KS) within and between projects. However, studies in that field focus primarily on KS mechanisms including lessons learned (LL) and post project reviews as the source of knowledge for future projects, and only some preliminary research has been carried out on the aspects of project management offices (PMOs) and organisational culture (OC) in KS. This study undertook to investigate KS behaviours in an inter-project context, with a particular emphasis on the role of trust, OC and a range of knowledge sharing mechanisms (KSM) in achieving successful inter-project knowledge sharing (I-PKS). An extensive literature search resulted in the development of an I-PKS Framework, which defined the scope of the research and shaped its initial design. The literature review indicated that existing research relating to the three factors of OC, trust and KSM remains inadequate in its ability to fully explain the role of these contextual factors. In particular, the literature review identified these areas of interest: (1) the conflicting answers to some of the major questions related to KSM, (2) the limited empirical research on the role of different trust dimensions, (3) limited empirical evidence of the role of OC in KS, and (4) the insufficient research on KS in an inter-project context. The resulting Framework comprised the three main factors including: OC, trust and KSM, demonstrating a more integrated view of KS in the inter-project context. Accordingly, the aim of this research was to examine the relationships between these three factors and KS by investigating behaviours related to KS from the project managers‘ (PMs‘) perspective. In order to achieve the aim, this research sought to answer the following research questions: 1. How does organisational culture influence inter-project knowledge sharing? 2. How does the existence of three forms of trust — (i) ability, (ii) benevolence and (iii) integrity — influence inter-project knowledge sharing? 3. How can different knowledge sharing mechanisms (relational, project management tools and process, and technology) improve inter-project knowledge sharing behaviours? 4. How do the relationships between these three factors of organisational culture, trust and knowledge sharing mechanisms improve inter-project knowledge sharing? a. What are the relationships between the factors? b. What is the best fit for given cases to ensure more effective inter-project knowledge sharing? Using multiple case studies, this research was designed to build propositions emerging from cross-case data analysis. The four cases were chosen on the basis of theoretical sampling. All cases were large project-based organisations (PBOs), with a strong matrix-type structure, as per the typology proposed by the Project Management Body of Knowledge (PMBoK) (2008). Data were collected from project management departments of the respective organisations. A range of analytical techniques were used to deal with the data including pattern matching logic and explanation building analysis, complemented by the use of NVivo for data coding and management. Propositions generated at the end of the analyses were further compared with the extant literature, and practical implications based on the data and literature were suggested in order to improve I-PKS. Findings from this research conclude that OC, trust, and KSM contribute to inter-project knowledge sharing, and suggest the existence of relationships between these factors. In view of that, this research identified the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and knowledge sharing. Furthermore, this research demonstrated that characteristics of culture and trust interact to reinforce preferences for mechanisms of knowledge sharing. This means that cultures that facilitate characteristics of Clan type are more likely to result in trusting relationships, hence are more likely to use organic sources of knowledge for both tacit and explicit knowledge exchange. In contrast, cultures that are empirically driven, based on control, efficiency, and measures (characteristics of Hierarchy and Market types) display tendency to develop trust primarily in ability of non-organic sources, and therefore use these sources to share mainly explicit knowledge. This thesis contributes to the project management literature by providing a more integrative view of I-PKS, bringing the factors of OC, trust and KSM into the picture. A further contribution is related to the use of collaborative tools as a substitute for static LL databases and as a facilitator for tacit KS between geographically dispersed projects. This research adds to the literature on OC by providing rich empirical evidence of the relationships between OC and the willingness to share knowledge, and by providing empirical evidence that OC has an effect on trust; in doing so this research extends the theoretical propositions outlined by previous research. This study also extends the research on trust by identifying the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and KS. Finally, this research provides some directions for future studies.

Computational design of cyclic nitroxides as efficient redox mediators for dye-sensitized solar cells

Cyclic nitroxide radicals represent promising alternatives to the iodine-based redox mediator commonly used in dye-sensitized solar cells (DSSCs). To date DSSCs with nitroxide-based redox mediators have achieved energy conversion efficiencies of just over 5 % but efficiencies of over 15 % might be achievable, given an appropriate mediator. The efficacy of the mediator depends upon two main factors: it must reversibly undergo one-electron oxidation and it must possess an oxidation potential in a range of 0.600-0.850 V (vs. a standard hydrogen electrode (SHE) in acetonitrile at 25 °C). Herein, we have examined the effect that structural modifications have on the value of the oxidation potential of cyclic nitroxides as well as the reversibility of the oxidation process. These included alterations to the N-containing skeleton (pyrrolidine, piperidine, isoindoline, azaphenalene, etc.), as well as the introduction of different substituents (alkyl-, methoxy-, amino-, carboxy-, etc.) to the ring. Standard oxidation potentials were calculated using high-level ab initio methodology that was demonstrated to be very accurate (with a mean absolute deviation from experimental values of only 16 mV). An optimal value of 1.45 for the electrostatic scaling factor for UAKS radii in acetonitrile solution was obtained. Established trends in the values of oxidation potentials were used to guide molecular design of stable nitroxides with desired E° ox and a number of compounds were suggested for potential use as enhanced redox mediators in DSSCs. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Semi-parametric forecasting of realized volatility

Forecasts generated by time series models traditionally place greater weight on more recent observations. This paper develops an alternative semi-parametric method for forecasting that does not rely on this convention and applies it to the problem of forecasting asset return volatility. In this approach, a forecast is a weighted average of historical volatility, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in volatility across time (as a measure of market conditions) by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are significantly more accurate than a number of competing approaches at both short and long forecast horizons.

Effect of caffeine on adenosine-induced reversible perfusion defects assessed by automated analysis

Objectives This prospective study investigated the effects of caffeine ingestion on the extent of adenosine-induced perfusion abnormalities during myocardial perfusion imaging (MPI). Methods Thirty patients with inducible perfusion abnormalities on standard (caffeine-abstinent) adenosine MPI underwent repeat testing with supplementary coffee intake. Baseline and test MPIs were assessed for stress percent defect, rest percent defect, and percent defect reversibility. Plasma levels of caffeine and metabolites were assessed on both occasions and correlated with MPI findings. Results Despite significant increases in caffeine [mean difference 3,106 μg/L (95% CI 2,460 to 3,752 μg/L; P < .001)] and metabolite concentrations over a wide range, there was no statistically significant change in stress percent defect and percent defect reversibility between the baseline and test scans. The increase in caffeine concentration between the baseline and the test phases did not affect percent defect reversibility (average change −0.003 for every 100 μg/L increase; 95% CI −0.17 to 0.16; P = .97). Conclusion There was no significant relationship between the extent of adenosine-induced coronary flow heterogeneity and the serum concentration of caffeine or its principal metabolites. Hence, the stringent requirements for prolonged abstinence from caffeine before adenosine MPI—based on limited studies—appear ill-founded.