Current practice and challenges towards handling uncertainty for effective outcomes in maintenance

The combination of viable heuristic attributes with statistical measurements presents significant challenges in industrial maintenance for complex assets under through-life service contracts. Techniques to obtain and process heuristic attributes raise numerous uncertainties which often go undefined and unmitigated. A holistic view of these uncertainties may improve decision-making capabilities and reduce maintenance costs and turnaround time. It is therefore necessary to identify and rank factors that influence uncertainties originating from challenges in the above context. This, along with an identification of who contributes to such challenges and current practice to handle them, sets the focus for this study. The influence of 32 categorised factors on uncertainty is assessed through a questionnaire completed by nine experienced maintenance managers from a leading defence company. The pedigree approach is applied to score validity of respondents’ answers according to their experience and job role to normalise scores. Results are discussed in interviews with respondents along with current practice in and ways to improve uncertainty assessment. Scores are weighted through the Analytical Hierarchy Process (AHP) in order to identify the most influential factors on uncertainty in maintenance. The analysis revealed that these include: intellectual property rights (IPR), maintainer performance, quality of information, resistance to change, stakeholder communication and technology integration. These are verified with 40 practitioners from various industrial backgrounds. From the interviews, it is deemed that a holistic view of heuristic and statistical attributes ultimately allows for more accomplished decision-making but requires trade-offs between quality and cost over the asset’s life cycle

Conceptualising the impact of information asymmetry on through-life cost: case study of machine tools sector

Information asymmetry (IA) in terms of contextual variety and importance is one of the most challenging aspects of through-life costing in product-service systems (PSS). IA is an imbalance in the information, data and knowledge shared among the parties involved in a contractual agreement. In manufacturing systems under PSS, interaction and effective communication among several parties who are involved in a contractual agreement, rely on the continuity and accuracy of information and context. In such systems, contextual variety exhibits complexity and uncertainty in through-life costing and subsequently in PSS cost assessment. Although the economic aspect of PSS has been studied previously, the impact of IA on through-life cost and for different PSS solutions has not been detailed. Considering manufacturing value chains, this paper introduces a new concept of PSS-hierarchy to perform through-life costing in the presence of IA for various PSS solutions. Moreover, this paper proposes a generic life-cycle model for different PSS solutions to assess the total cost of ownership (TCO). The proposed model has been developed to support decisions on contract design in manufacturing systems. This study considers the manufacturer, service provider and customer perspectives to develop the TCO model using a machine tool manufacturing case study

Mindfulness and emotional regulation as sequential mediators in the relationship between attachment security and depression

Depression is a significant global health issue that has previously been associated with negative early care experiences and insecure attachment styles. This has led to much interest in identifying variables that may interrupt this relationship and prevent detrimental personal, social and economic outcomes. Recent research has indicated associations between the two seemingly distinct constructs of secure attachment and mindfulness, with similar positive outcomes. One hundred and forty eight participants completed an online survey exploring a possible sequential cognitive processing model, which predicted that higher levels of mindfulness and then emotional regulation would mediate the relationship between attachment and depression. Full mediation was found in regards to secure, preoccupied and dismissive attachment, whereas partial mediation was identified in the case of fearful attachment. The results support the possibility of an alternative cognitive processing pathway that may interrupt the association between negative early care experiences and concomitant negative mental health outcomes. Further exploration of this relationship is indicated

Brief intervention manual for personality disorders

This manual is designed to help services intervene early and better support young people and adults with personality disorders. It is particularly focused on clients in crisis, who have complex needs, by providing practical therapeutic techniques in the prevention and treatment of high-risk challenging behaviours. It describes a four session brief intervention that can act as the first step in a treatment journey for people with this disorder

Multistep prediction of dynamic uncertainty under limited data

Engineering systems are growing in complexity, requiring increasingly intelligent and flexible methods to account for and predict uncertainties in service. This paper presents a framework for dynamic uncertainty prediction under limited data (UPLD). Spatial geometry is incorporated with LSTM networks to enable real-time multistep prediction of quantitative and qualitative uncertainty over time. Validation is achieved through two case studies. Results demonstrate robust prediction of trends in limited and dynamic uncertainty data with parallel determination of geometric symmetry at each time unit. Future work is recommended to explore alternative network architectures suited to limited data scenarios.Engineering and Physical Sciences Research Council (EPSRC): 194431

Dynamic multistep uncertainty prediction in spatial geometry

Maintenance procedures for complex engineering systems are increasingly determined by predictive algorithms based on historic data, experience and knowledge. Such data and knowledge is accompanied by varying degrees of uncertainty which impact equipment availability, turnaround time and unforeseen costs throughout the system life cycle. Once quantified, these uncertainties call for robust forecasting to facilitate dependable maintenance costing and ensure equipment availability. This paper builds on the theory of spatial geometry as a methodology to forecast uncertainty where available data is insufficient for the application of traditional statistical analysis. To ensure continuous forecast accuracy, a conceptual dynamic multistep prediction model is presented applying spatial geometry with long-short term memory (LSTM) neural networks. Based in MATLAB, this deep learning model predicts uncertainty for the in-service life of a given system. The further into the future the model predicts, the lower the confidence in the uncertainty prediction. Forecasts are therefore also made for a single time step ahead. When this single step is reached in real time, the next step is forecast and used to update the long range prediction. The uncertainty here is contributed by an aggregation of quantitative data and qualitative, subjective expert opinions and additional traits such as environmental conditions. It is therefore beneficial to indicate which of these factors prompts the greatest impact on the aggregated uncertainty for each forecast point. Future work will include the option to simulate and interpolate input data to enhance the accuracy of the LSTM and explore suitable approaches to mitigate, tolerate or exploit uncertainty through deep learning

Illawarra Born cross-generational health study: feasibility of a multi-generational birth cohort study

Background: There is a strong interest in the concept of developmental origins of health and disease and their influence on various factors from cradle to grave . Despite the increasing appreciation of this lifelong legacy across the human life course, many gaps remain in the scientific understanding of mechanisms influencing these formative phases. Cross-generational susceptibility to health problems is emerging as a focus of research in the context of birth cohort studies. The primary aim of the Illawarra Born study is to make scientific discoveries associated with improving health and wellbeing across the lifespan, with a particular focus on preventable chronic diseases, especially mental health. This birth cohort study will follow and collect data from three cohorts representing different stages across the lifespan: infants, adults (parents) and older adults (grandparents). The multi-generational, cross-sectional and longitudinal design of this birth cohort study supports a focus on the contributions of genetics, environment and lifestyle on health and wellbeing. The feasibility of conducting a multi-generational longitudinal birth cohort project was conducted through a small pilot study. Methods/design: The purpose of this paper is to report on the feasibility and acceptability of the research protocol for a collaborative cross-generation health study in the community and test recruitment and outcome measures for the main study. This feasibility study included pregnant women who were intending to give birth in the Illawarra-Shoalhaven region in Eastern Australia. The area includes a large, regional referral hospital, with capacity to treat specialist and complex cases. Pregnant women were asked to participate in five data collection waves beginning at 22 weeks gestation and ending with a 6-month post-partum appointment. Recruitment was then extended, via the pregnant women, to also include fathers and maternal grandmothers. Discussion: This feasibility study focused on the perinatal period and collected data across three multi-disciplinary domains including mental health, diet, exposures to toxins and the role of these in maternal and infant outcomes. Forty-one families participated in extensive data collection from 22 weeks gestation to 6-months post-partum. Factors impacting on viability and feasibility including recruitment solutions provide the basis for a large-scale study

The shape of mammalian phylogeny: patterns, processes and scales

Mammalian phylogeny is far too asymmetric for all contemporaneous lineages to have had equal chances of diversifying. We consider this asymmetry or imbalance from four perspectives. First, we infer a minimal set of 'regime changes'-points at which net diversification rate has changedidentifying 15 significant radiations and 12 clades that may be 'downshifts'. We next show that mammalian phylogeny is similar in shape to a large set of published phylogenies of other vertebrate, arthropod and plant groups, suggesting that many clades may diversify under a largely shared set of 'rules'. Third, we simulate six simple macroevolutionary models, showing that those where speciation slows down as geographical or niche space is filled, produce more realistic phylogenies than do models involving key innovations. Lastly, an analysis of the spatial scaling of imbalance shows that the phylogeny of species within an assemblage, ecoregion or larger area always tends to be more unbalanced than expected from the phylogeny of species at the next more inclusive spatial scale. We conclude with a verbal model of mammalian macroevolution, which emphasizes the importance to diversification of accessing new regions of geographical or niche space

Human pregnancy zone protein stabilizes misfolded proteins including preeclampsia- and Alzheimer's-associated amyloid beta peptide.

Protein misfolding underlies the pathology of a large number of human disorders, many of which are age-related. An exception to this is preeclampsia, a leading cause of pregnancy-associated morbidity and mortality in which misfolded proteins accumulate in body fluids and the placenta. We demonstrate that pregnancy zone protein (PZP), which is dramatically elevated in maternal plasma during pregnancy, efficiently inhibits in vitro the aggregation of misfolded proteins, including the amyloid beta peptide (Aβ) that is implicated in preeclampsia as well as with Alzheimer's disease. The mechanism by which this inhibition occurs involves the formation of stable complexes between PZP and monomeric Aβ or small soluble Aβ oligomers formed early in the aggregation pathway. The chaperone activity of PZP is more efficient than that of the closely related protein alpha-2-macroglobulin (α2M), although the chaperone activity of α2M is enhanced by inducing its dissociation into PZP-like dimers. By immunohistochemistry analysis, PZP is found primarily in extravillous trophoblasts in the placenta. In severe preeclampsia, PZP-positive extravillous trophoblasts are adjacent to extracellular plaques containing Aβ, but PZP is not abundant within extracellular plaques. Our data support the conclusion that the up-regulation of PZP during pregnancy represents a major maternal adaptation that helps to maintain extracellular proteostasis during gestation in humans. We propose that overwhelming or disrupting the chaperone function of PZP could underlie the accumulation of misfolded proteins in vivo. Attempts to characterize extracellular proteostasis in pregnancy will potentially have broad-reaching significance for understanding disease-related protein misfolding.Wellcome Trust Programme Grant 094425/Z/10/