193 resultados para predictive maintenance
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Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.
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Background: There is currently no early predictive marker of survival for patients receiving chemotherapy for malignant pleural mesothelioma (MPM). Tumour response may be predictive for overall survival (OS), though this has not been explored. We have thus undertaken a combined-analysis of OS, from a 42 day landmark, of 526 patients receiving systemic therapy for MPM. We also validate published progression-free survival rates (PFSRs) and a progression-free survival (PFS) prognostic-index model. Methods: Analyses included nine MPM clinical trials incorporating six European Organisation for Research and Treatment of Cancer (EORTC) studies. Analysis of OS from landmark (from day 42 post-treatment) was considered regarding tumour response. PFSR analysis data included six non-EORTC MPM clinical trials. Prognostic index validation was performed on one non-EORTC data-set, with available survival data. Results: Median OS, from landmark, of patients with partial response (PR) was 12·8 months, stable disease (SD), 9·4 months and progressive disease (PD), 3·4 months. Both PR and SD were associated with longer OS from landmark compared with disease progression (both p < 0·0001). PFSRs for platinum-based combination therapies were consistent with published significant clinical activity ranges. Effective separation between PFS and OS curves provided a validation of the EORTC prognostic model, based on histology, stage and performance status. Conclusion: Response to chemotherapy is associated with significantly longer OS from landmark in patients with MPM. © 2012 Elsevier Ltd. All rights reserved.
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Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.
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The E&P sector can learn much about asset maintenance from the space and satellite industry. Practitioners from both the upstream oil and gas industry and the space and satellite sector have repeatedly noted several striking similarities between the two industries over the years, which have in turn resulted in many direct comparisons in the media and industry press. The similarities between the two industries have even resulted in a modest amount of cross-pollinating between the respective supply chains. Because the operating conditions of both industries are so extreme, some oil and gas equipment vendors have occasionally sourced motors and other parts from aerospace contractors. Also, satellites are now being used to assess oil fires, detect subsidence in oil fields, measure oil spills, collect and transmit operational data from oil and gas fields, and monitor the movement of icebergs that might potentially collide with offshore oil and gas installations.
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This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.
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The cost of surgical instrumentation is a major investment for any operating theatre. Repair or premature replacement of instruments is an additional financial burden. Although instrument care, handling, cleaning and sterilisation are usually components of orientation programs for instrument processing personnel, it should also be included in the scrub nurse orientation program. A thorough knowledge of the historical development of instruments; instrument classification and purpose; and careful use and handling will equip the scrub nurse in fulfilling a vital role in preventative maintenance of surgical instrumentation
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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.
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In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.
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An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.
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This study unveils causes of accidents in repair, maintenance, alteration and addition (RMAA) work. RMAA work is playing an increasingly important role in developed societies, including Hong Kong. Safety problems associated with RMAA work in Hong Kong has reached an alarming level. In view of rapid expansion of the RMAA sector and rising proportion of accidents in the construction industry, there is a pressing need to investigate causes of RMAA accidents. Structured interviews were conducted with RMAA contractors to explore causes of accidents in the RMAA sector. A two-round Delphi method with 13 safety experts was subsequently employed to verify the interview findings and rank the relative degree of importance for various causes of accidents. Accidents happen in RMAA work due to intersection of reasons. One of the root causes of accidents in RMAA works is low safety awareness of RMAA workers; however, wider organizational and industrial factors are not negligible. This study sheds light on why accidents happen in the RMAA sector. Only when the factors leading to accidents are identified can effective measures be made.
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Repair, maintenance, minor alteration, and addition work (RMAA) has become more and more important in developed societies, but its safety performance is alarming. For example, RMAA projects accounted for 53.2% of the total construction market and the percentage of RMAA accidents to all construction accidents in the Hong Kong Special Administrative Region (HKSAR) increased considerably in 2007. The RMAA sector has a huge potential for safety improvement. This study aims to explore and evaluate the difficulties of implementing safety practices in RMAA work. The mixed methods approach was adopted, and semistructured interviews and a two-round Delphi survey were conducted for the data collection. Major difficulties were identified, including limited safety resources for small and medium enterprises (SMEs), difficulty in changing the mindset of RMAA workers, and difficulty in performing safety supervision. These obstacles for implementing safety practices in the RMAA sector, if successfully removed, could significantly improve the safety performance of the RMAA sector and the construction industry as a whole.
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Software development settings provide a great opportunity for CSCW researchers to study collaborative work. In this paper, we explore a specific work practice called bug reproduction that is a part of the software bug-fixing process. Bug re-production is a highly collaborative process by which software developers attempt to locally replicate the ‘environment’ within which a bug was originally encountered. Customers, who encounter bugs in their everyday use of systems, play an important role in bug reproduction as they provide useful information to developers, in the form of steps for reproduction, software screenshots, trace logs, and other ways to describe a problem. Bug reproduction, however, poses major hurdles in software maintenance as it is often challenging to replicate the contextual aspects that are at play at the customers’ end. To study the bug reproduction process from a human-centered perspective, we carried out an ethnographic study at a multinational engineering company. Using semi-structured interviews, a questionnaire and half-a-day observation of sixteen software developers working on different software maintenance projects, we studied bug reproduction. In this pa-per, we present a holistic view of bug reproduction practices from a real-world set-ting and discuss implications for designing tools to address the challenges developers face during bug reproduction.
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Safety of repair, maintenance, alteration, and addition (RMAA) works have long been neglected because RMAAworks are often minute and only last for a short period of time. With rising importance of the RMAA sector in many developed societies, safety of RMAA works has begun to draw attention. Many RMAA contracting companies are small- and medium-sized enterprises (SMEs) that do not have comprehensive safety management systems. Existing safety legislation and regulations for new construction sites are not fully applicable to RMAAworks. Instead of relying on explicit and well-established safety systems, tacit safety knowledge plays an extremely important role in RMAA projects. To improve safety of RMAAworks, safety knowledge should be better managed. However, safety knowledge is difficult to capture in RMAA works. This study aims to examine safety management practices of RMAA contracting companies to see how safety knowledge of RMAA projects is managed. Findings show that RMAA contracting companies undertaking large-scale RMAA projects have more initiatives of safety management. Safety management of small-scale RMAA works relies heavily on the motivation of site supervisors and self-regulation of workers. Better tacit knowledge management improves safety performance. To enhance safety capability of RMAA contracting companies, a knowledge sharing culture should be cultivated. The government should provide assistance to SMEs to implement proper safety management practices in small-sized projects. Potentials of applying computer software technology in RMAA projects to capture, store, and retrieve safety information should be explored. Employees should be motivated to share safety knowledge by giving proper recognition to those who are willing to share.
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Purpose The repair, maintenance, minor alteration and addition (RMAA) sector has been expanding in many developed cities. Safety problems of the RMAA sector have attracted the attention of many governments. This study has the objectives of comparing the level of safety climate of workers, supervisors and managers in the RMAA sector; and explaining/ predicting the impact of safety climate on injury occurrence of workers, supervisors and managers. Design/methodology/approach A questionnaire survey was administered to RMAA contracting companies in Hong Kong. Findings When comparing the safety climate perception of workers, supervisors and managers in the RMAA sector, the supervisors group had the lowest mean safety climate score. Results showed that a positive workforce safety attitude and acceptance of safety rules and regulations reduced the workers’ likelihood of having injuries. A reasonable production schedule led to a lower probability of supervisors being injured. Management commitment and effective safety management reduced the probability of managers being injured. Originality/value This study revealed variations of safety climate at the different levels in the organizational hierarchy and their varying influence on safety performance of the RMAA sector. Safety of RMAA works could be improved by promulgating specific safety measures at the different hierarchy levels.