| 1. |
- Kansal, Yogita, et al.
(author)
-
Fixing of Faults and Vulnerabilities via Single Patch
- 2018
-
In: Quality, IT and Business Operations. - Singapore : Springer. - 9789811055768 - 9789811055775 ; , s. 175-190
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Book chapter (peer-reviewed)abstract
- Users’ demand of reliable software in zero time has made the software development more complex. If software industry fails in fulfilling the demands, then it may undergo big penalties and revenue loss. The developers are pressurized subject to resource constraints provided by the management. Despite such fact, software experiences various validation (testing) processes before its release; faults and vulnerabilities are still left undetected that later lack the quality of the product. The only feasible solution for resisting from the lack after the release of software is patch development. Generally, the patches developed for fixing faults and vulnerabilities are a separate process which requires extra resources that increases the total development cost and time. In this paper, we have proposed a cost framework that solves the problem of optimizing the patch release time with two different approaches. Here, the first approach has considered the release of a single patch that fixes both faults and vulnerabilities jointly. As the severity of vulnerabilities is much higher than the faults, the second approach considered the release of two patches where the first patch has fixed both faults and vulnerabilities jointly and other patch specifically fixed only vulnerabilities. The detailed illustration of the method is presented in the proposed paper. The case study is presented at the end for the validation purpose.
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| 2. |
- Kansal, Yogita, et al.
(author)
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Prioritizing Vulnerabilities using ANP and Evaluating their Optimal Discovery and Patch Release Time
- 2019
-
In: International Journal of Mathematics in Operational Research (IJMOR). - : InderScience Publishers. - 1757-5850 .- 1757-5869. ; 14:2, s. 236-267
-
Journal article (peer-reviewed)abstract
- Method for filtering and identifying a vulnerability class that has high probability of occurrence is needed by organisations to patch their software in a timely manner. In this paper, our first step is to filter the most frequently observed vulnerability type/class through a multi-criteria decision making that involves dependency among various criteria and feedback from various alternatives, known as analytic network process. We will also formulate a cost model to provide a solution to the developers facing high revenue debt because of the occurrence of highly exploited vulnerabilities belonging to the filtered group. The main aim of formulating the cost model is to evaluate the optimal discovery and patch release time such that the total developer's cost could be minimised subject to risk constraints. To illustrate the proposed approach, reported vulnerabilities of Google Chrome with high exploitability have been examined at its source level.
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| 3. |
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| 4. |
- Jena, Jajati K., et al.
(author)
-
Tunnel QRA : Present and Future Perspectives
- 2019
-
In: System Performance and Management Analytics. - Singapore : Springer. - 9789811073229 - 9789811073236 ; , s. 387-403
-
Book chapter (peer-reviewed)abstract
- With the vision of faster in-land transportation of humans and goods, long tunnels with increasing engineering complexities are being designed, constructed and operated. Such complexities arise due to terrain (network of small tunnels) and requirement of multiple entries and exits (network of traffics leading to non-homogenous behaviour). Increased complexities of such tunnels throw unique challenges for performing QRA for such tunnels, which gets compounded due to handful number of experiments performed in real tunnels, as they are costly and dangerous. A combined approach of CFD modelling of scaled down tunnels could be a relatively less resource intensive solution, nevertheless, associated with its increased uncertainties due to introduction of scaling multiplication factors. Further, with the advent of smart system designs and cheap computational cost, a smart tunnel which manages its own traffic of both dangerous goods carriers and other passenger vehicles based on continuously updated dynamic risk estimate, is not far from reality.
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| 5. |
- Kansal, Yogita, et al.
(author)
-
Effort and coverage dependent vulnerability discovery modeling
- 2018
-
Conference paper (peer-reviewed)abstract
- In this paper, our primary focus is to propose a generalized mathematical model that can discover potential vulnerabilities on the basis of two key factors: operational effort rate and operational coverage rate. Here, the term operational effort rate refers to the proportion of manpower required to discover vulnerabilities. The operational coverage rate refers to the proportion of software covered by the effort in discovering vulnerabilities. It is assumed that the proposed model follows the Non-Homogeneous Poisson process properties thus different distribution are used to formulate multiple cases. To evaluate the operational effort function, exponential and Weibull distribution are used considering coverage rate either to be a constant or logistic. For model validation, a case study of real commercial software data set has been used
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| 6. |
- Kansal, Yogita, et al.
(author)
-
User-dependent vulnerability discovery model and its interdisciplinary nature
- 2017
-
In: Life Cycle Reliability and Safety Engineering. - : Springer. - 2520-1352 .- 2520-1360. ; 6:1, s. 23-29
-
Journal article (peer-reviewed)abstract
- Software Vulnerability is a broad discipline that cannot be controlled only by the technologies. The holistic framework is required that statistically encompasses the entire security issues of IT organizations regardless of individual projects. Earlier researchers have developed several mathematical models that determined the vulnerabilities trend over time. Besides that, the most common victims of the vulnerabilities i.e., the software buyers or users were addressed theoretically without considering their impact on vulnerability discovery modeling. In this research paper, we examined the vulnerability discovery rate on the basis of potential users of commercial software. Here we propose an interdisciplinary model that highlights the relationship between the vulnerability intensity and the number of users of the software. The numerical illustration based on several real data sets is provided to validate the proposed user-dependent vulnerability discovery model.
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| 7. |
- Kumar, Uday, et al.
(author)
-
Preface
- 2016. - 1
-
In: Current Trends in Reliability, Availability, Maintainability and Safety. - : Springer International Publishing. - 9783319235967 - 9783319235974 ; , s. v-vi
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Book chapter (other academic/artistic)
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| 8. |
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| 9. |
- Mohan, Gowtham, et al.
(author)
-
Experimental investigation of a novel solar thermal polygeneration plant in United Arab Emirates
- 2016
-
In: Renewable energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 91, s. 361-373
-
Journal article (peer-reviewed)abstract
- The demands for space air conditioning and clean drinking water are relatively high in Middle East North African (MENA) countries. A sustainable and innovative approach to meet these demands along with the production of domestic hot water is experimentally investigated in this paper. A novel solar thermal poly-generation (STP) pilot plant is designed and developed for production of chilled water for air conditioning using absorption chiller, clean drinking water with membrane distillation units and domestic hot water by heat recovery. The STP system is developed with a flexibility to operate in four different modes: (i) solar cooling mode (ii) cogeneration of drinking water and domestic hot water (iii) cogeneration of cooling and desalination (iv) trigeneration. Operational flexibility allows consumers to utilize the available energy based on seasonal requirements. Performance of STP system is analyzed during summer months in RAKRIC research facility. Energy flows in STP pilot plant during peak load operations are analyzed for all four modes. STP system with trigeneration mode utilizes 23% more useful energy compared to solar cooling mode, which improves overall efficiency of the plant. Economic benefits of STP with trigeneration mode are evaluated with fuel cost inflation rate of 10%. STP plant has potential payback period of 9.08 years and net cumulative savings of $454,000 based on economic evaluation.
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| 10. |
- Patwardhan, Amit, et al.
(author)
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A Survey on Predictive Maintenance Through Big Data
- 2016
-
In: Current Trends in Reliability, Availability, Maintainability and Safety. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319235967 - 9783319235974 ; , s. 437-445
-
Conference paper (peer-reviewed)abstract
- Modern manufacturing systems use thousands of sensors retrieving information at hundreds to thousands of samples per second. The real time data being generated is mostly used for monitoring the processes and the equipment condition. Data processing techniques applied to this data to detect anomalies and thus applying preventive maintenance have been used in the industry. Currently available technologies which were developed during the last two decade for scanning the Internet and providing computational services, working at very large scale can be re-targeted to fulfil the requirements of maintenance of complex systems. These systems can support storage and processing of current as well as historical data. Ability to access and process these large data sets will lead from preventive to predictive maintenance and eventually to smart manufacturing..
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| 11. |
-
Quality, IT and Business Operations : Modeling and Optimization
- 2018
-
Editorial collection (peer-reviewed)abstract
- This book discusses action-oriented, concise and easy-to-communicate goals and challenges related to quality, reliability, infocomm technology and business operations. It brings together groundbreaking research in the area of software reliability, e-maintenance and big data analytics, highlighting the importance of maintaining the current growth in information technology (IT) adoption in businesses, while at the same time proposing process innovations to ensure sustainable development in the immediate future. In its thirty-seven chapters, it covers various areas of e-maintenance solutions, software architectures, patching problems in software reliability, preventive maintenance, industrial big data and reliability applications in electric power systems.The book reviews the ways in which countries currently attempt to resolve the conflicts and opportunities related to quality, reliability, IT and business operations, and proposes that internationally coordinated research plans are essential for effective and sustainable development, with research being most effective when it uses evidence-based decision-making frameworks resulting in clear management objectives, and is organized within adaptive management frameworks. Written by leading experts, the book is of interest to researchers, academicians, practitioners and policy makers alike who are working towards the common goal of making business operations more effective and sustainable.
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| 12. |
- Singh, Sarbjeet, et al.
(author)
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Applying human factor analysis tools to a railway brake and wheel maintenance facility
- 2015
-
In: Journal of Quality in Maintenance Engineering. - 1355-2511 .- 1758-7832. ; 21:1, s. 89-99
-
Journal article (peer-reviewed)abstract
- PurposeThis paper demonstrates three techniques to extract human factor information from specific railway maintenance tasks. It describes the techniques and shows how these tools can be applied to identify improvements in maintenance practices and workflow. Design/methodology/approachThree case studies were conducted on single group of technicians (N=19) at a railway maintenance workshop in Luleå, Sweden. Case study I examined the posture of the technicians while they were changing the brake shoes of freight wagons; the study employed the Standard Nordic Questionnaire and a videotape using the Ovako Working Posture Analysis System (OWAS). Case study II looked at maintenance repair times required to change the wheel axle on freight wagons at the workshop. A video filming method suggested by the European Agency for Safety and Health at Work was used to measure actual maintenance time. Finally, case study III considered the technicians’ (N=19) perception of work demands, their control over the work and their social support while performing maintenance tasks (brake shoe and wheel axle maintenance); to this end, the case study used a demand control support questionnaire. FindingsIn the first case study, the Standard Nordic Questionnaire confirmed that technicians at this particular railway vehicle maintenance workshop suffer from back and shoulder pain. The Ovako Working Posture Analysis showed that 21% of the working time required to fit the brake wedge and cotter pin fits into two OWAS categories: category 3, where “change is required as soon as possible,” and category 4, where “change is required immediately”. Problems stem from poor workplace layout, incorrect posture and inaccessibility of tools and components. In the second study, the video analysis indicated that the working time to change the wheel axle of a freight wagon is greatly affected by poor workplace layout. The third case study showed that the technicians have lower “psychological demands” (mean=13), “higher control over work” (mean= 16) and “high social support” (mean= 22).Practical implicationsThe objective of this study was to apply knowledge about human factors to the functional relationships between maintenance personnel, tasks and the working environment to improve safety. If the workplace layout, working posture, maintenance manuals and accessibility of tools are poorly planned, maintenance performance can be adversely affected. The results of this study should assist maintenance management to design new policies and guidelines for improving the work environment.Originality/valueThree case studies were conducted at a railway maintenance workshop in Luleå, Sweden, to collect data on how human factors affect various railway maintenance tasks.
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| 13. |
- Singh, Sarbjeet, et al.
(author)
-
Modelling factors affecting human operator failure probability in railway maintenance tasks : an ISM-based analysis
- 2015
-
In: International Journal of Systems Assurance Engineering and Management. - : Springer Science and Business Media LLC. - 0975-6809 .- 0976-4348. ; 6:2, s. 129-138
-
Journal article (peer-reviewed)abstract
- This paper investigates the factors affecting human operators’ probability of failure when performing railway maintenance tasks. The objective is to understand the interaction of the various factors and to identify driving and dependent factors. The factors are identified through a survey of the literature and ranked using a Likert scale. The reliability of measures is pretested by applying Cronbach’s alpha coefficient to responses to the questionnaire given to maintenance personnel. An interpretive structural model is presented, and factors are classified using matrice d’impacts croises-multiplication appliquéà un classement (MICMAC). The research may help maintenance management understand the interaction of factors affecting human failure probability in railway maintenance and help management devise policies and guidelines for railway maintenance related tasks.
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| 14. |
- Thaduri, Adithya, et al.
(author)
-
Analytics for Maintenance of Transportation in Smart Cities
- 2018
-
In: Quality, IT and Business Operations. - Singapore : Springer. - 9789811055768 - 9789811055775 ; , s. 81-91
-
Book chapter (peer-reviewed)abstract
- Cities typically face a wide range of management and maintenance problems. They are complex environments in which digital technologies are more and more pervasive; this digitization of urban environment provided a scope for enriched environment that has capability for data-driven methods. The connections and exchange of data increase and the need for data acquisition, processing, and management become an extremely important added value to the community. The inclusion of digitization and incorporation of predictive analytics provide a base for a sustainable smart city. This work considers an overview of different challenges that utilizes different technologies within a smart city maintenance with respect to transportation. A conceptual framework is proposed to handle the generated data for decision for control, monitoring, fault diagnosis, and maintenance of more and more complex systems.
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| 15. |
- Thaduri, Adithya, et al.
(author)
-
Comparison of failure characteristics of different electronic technologies by using modified physics-of-failure approach
- 2015
-
In: International Journal of Systems Assurance Engineering and Management. - : Springer Science and Business Media LLC. - 0975-6809 .- 0976-4348. ; 6:2, s. 198-205
-
Journal article (peer-reviewed)abstract
- The electronic components are used in several safety and maintenance systems that require accurate reliability prediction for higher availability. The traditional reliability prediction methods that draw on standard handbooks such as MIL-HDBK 217F, Telcordia, CNET etc., are inappropriate to determine the reliability indices of these components due to empirical methods does not comply with operating life cycle and technology advancements. The progressive reliability prediction methodology, the physics-of-failure (PoF), emphasizes the root cause of failure, failure analysis, and failure mechanisms based on the analysis of parameter characteristics. However, there is a limitation: it is sometimes difficult to obtain manufacturer’s details for failure analysis and quality information. Several statistical and probability modeling methods can be performed on the experimental data of these components to measure the time to failure. These experiments can be conducted using the accelerated-testing of dominant stress parameters such as voltage, current, temperature, radiation etc. In this paper, the combination of qualitative data from PoF approach and quantitative data from the statistical analysis is used to create a modified physics-of-failure approach. The critical electronic components used in certain safety systems from different technologies are chosen for reliability prediction: optocoupler, constant fraction discriminator, BJT transistor, voltage comparator, voltage follower and instrumentation amplifier is studied. The failure characteristics of each of the technologies are studied and compared according to operating conditions
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| 16. |
- Thaduri, Adithya, et al.
(author)
-
Computational intelligence framework for context-aware decision making
- 2017
-
In: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348. ; 8:Supp. 4, s. 2146-2157
-
Journal article (peer-reviewed)abstract
- Learning of context-aware systems is necessary in building up knowledge on the characteristics of the environment to provide efficient decision making within multi-objective requirements. As the industrial systems becomes complex day-by-day, intelligent machine learning techniques need to be implemented at respective context-aware situations to facilitate recommendations using soft computing methods based on dynamic user specifications. In this paper, a framework is designed for a meta-database that is generated by contextual information of several peers with what-if conditions and rule-based approaches and thus by provide decision making utilizing several existing soft computing algorithms.
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| 17. |
- Thaduri, Adithya, et al.
(author)
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Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle
- 2016
-
In: Current Trends in Reliability, Availability, Maintainability and Safety. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319235967 - 9783319235974 ; , s. 67-81
-
Conference paper (peer-reviewed)abstract
- Maintenance of moving vehicles is quite challenging because they may disrupt the normal flow of transportation due to unexpected breakdowns, slowdowns and stoppages. In order to avoid stoppages and to minimize the downtime, maintenance and condition monitoring systems must be optimized. On one hand the condition monitoring on board should provide automatic failure detection, identification and localization together with a prognostic of the future failures. On the other hand maintenance logistics and product supportability must be also optimized since the onboard system should provide a suggestion of a repair shop that depends on location, cost and availability of spare parts, technicians’ skills and queuing time for repairs. However the vehicles are independent assets interacting among them within the traffic system and also interacting with the infrastructure (roads, rails etc.) seriously affected by weather, maintenance of infra, regulations etc. Therefore the proposed solution is to equip the vehicles with a context-aware system that monitors the condition and maintenance schedules of parts and alarm the driver of the parts that are in near to repair cycle. This system will perform risk analysis and will communicate with the cloud propose a decision of selection of repair shop on the location and path of vehicle depending on weather, road and traffic, cost and availability of spare parts at respective repair shops based on risk assessment and prediction. The information contained in the cloud will also communicate the workshop that will book time slot and block the necessary spare parts for the coming vehicle minimizing waiting time. This mechanism will help in reducing unexpected stoppages, vehicle degradation and efficient spare parts management combining in a successful way the workload of the workshops from both natural sources, the time based inspections and repairs together with the reactive maintenance coming from unexpected breakdown
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| 18. |
- Thaduri, Adithya, et al.
(author)
-
Process Mining for Maintenance Decision Support
- 2019
-
In: System Performance and Management Analytics. - Singapore : Springer. - 9789811073229 - 9789811073236 ; , s. 279-293
-
Book chapter (peer-reviewed)abstract
- In carrying out maintenance actions, there are several processes running simultaneously among different assets, stakeholders, and resources. Due to the complexity of maintenance process in general, there will be several bottlenecks for carrying out actions that lead to reduction in maintenance efficiency, increase in unnecessary costs and a hindrance to operations. One of the tools that is emerging to solve the above issues is the use Process Mining tools and models. Process mining is attaining significance for solving specific problems related to process such as classification, clustering, discovery of process, prediction of bottlenecks, developing of process workflow, etc. The main objective of this paper is to utilize the concept of process mining to map and comprehend a set of maintenance reports mainly repair or replacement from some lines on the Swedish railway network. To attain the above objective, the reports were processed to extract out time related maintenance parameters such as administrative, logistic and repair times. Bottlenecks are identified in the maintenance process and this information will be useful for maintenance service providers, infrastructure managers, asset owners and other stakeholders for improvement and maintenance effectiveness.
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| 19. |
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| 20. |
- Al-Douri, Yamur K.
(author)
-
Two-Level Multi-Objective Genetic Algorithm for Risk-Based Life Cycle Cost Analysis
- 2019
-
Doctoral thesis (other academic/artistic)abstract
- Artificial intelligence (AI) is one of the fields in science and engineering and encompasses a wide variety of subfields, ranging from general areas (learning and perception) to specific topics, such as mathematical theorems. AI and, specifically, multi-objective genetic algorithms (MOGAs) for risk-based life cycle cost (LCC) analysis should be performed to estimate the optimal replacement time of tunnel fan systems, with a view towards reducing the ownership cost and the risk cost and increasing company profitability from an economic point of view. MOGA can create systems that are capable of solving problems that AI and LCC analyses cannot accomplish alone.The purpose of this thesis is to develop a two-level MOGA method for optimizing the replacement time of reparable system. MOGA should be useful for machinery in general and specifically for reparable system. This objective will be achieved by developing a system that includes a smart combination of techniques by integrating MOGA to yield the optimized replacement time. Another measure to achieve this purpose is implementing MOGA in clustering and imputing missing data to obtain cost data, which could help to provide proper data to forecast cost data for optimization and to identify the optimal replacement time.In the first stage, a two-level MOGA is proposed to optimize clustering to reduce and impute missing cost data. Level one uses a MOGA based on fuzzy c-means to cluster cost data objects based on three main indices. The first is cluster centre outliers; the second is the compactness and separation ( ) of the data points and cluster centres; the third is the intensity of data points belonging to the derived clusters. Level two uses MOGA to impute the missing cost data by using a valid data period from that are reduced data in size. In the second stage, a two-level MOGA is proposed to optimize time series forecasting. Level one implements MOGA based on either an autoregressive integrated moving average (ARIMA) model or a dynamic regression (DR) model. Level two utilizes a MOGA based on different forecasting error rates to identify proper forecasting. These models are applied to simulated data for evaluation since there is no control of the influenced parameters in all of the real cost data. In the final stage, a two-level MOGA is employed to optimize risk-based LCC analysis to find the optimal replacement time for reparable system. Level one uses a MOGA based on a risk model to provide a variation of risk percentages, while level two uses a MOGA based on an LCC model to estimate the optimal reparable system replacement time.The results of the first stage show the best cluster centre optimization for data clustering with low and high intensity. Three cluster centres were selected because these centres have a geometry that is suitable for the highest data reduction of 27%. The best optimized interval is used for imputing missing data. The results of the second stage show the drawbacks of time series forecasting using a MOGA based on the DR model. The MOGA based on the ARIMA model yields better forecasting results. The results of the final stage show the drawbacks of the MOGA based on a risk-based LCC model regarding its estimation. However, the risk-based LCC model offers the possibility of optimizing the replacement schedule.However, MOGA is highly promising for allowing optimization compared with other methods that were investigated in the present thesis.
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| 21. |
- Alsyouf, Imad, et al.
(author)
-
Improving baggage flow in the baggage handling system at a UAE-based airline using lean Six Sigma tools
- 2019
-
In: Quality Engineering. - : Taylor & Francis. - 0898-2112 .- 1532-4222. ; 30:3, s. 432-452
-
Journal article (peer-reviewed)abstract
- This paper presents a real successful implementation of lean six sigma methodology to continuously improve the baggage flow in a baggage handling system (BHS), by identifying the causes of mishandled baggage, and deriving solutions to enhance BHS performance. The results show that the main critical problems were low system reliability and the high number of bags passing through manual-encoding-stations. This research illustrates how to avoid baggage congestion and provides applicable and cost-effective solutions. The success of this project made the organisation aware of the opportunities that the application of lean Six Sigma methodology created in the aviation and airport sector.
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| 22. |
-
Analytics for Maintenance of Transportation in Smart Cities
- 2015
-
Editorial proceedings (peer-reviewed)abstract
- Cities typically face a wide range of management and maintenance problems. They are complex environments in which digital technologies are more and more pervasive; this digitization of the urban space has led to a rich ecosystem of data producers and data consumers. The connections and exchange of data increase, and the need for data acquisition, processing and management become an extremely important added value to the community. The inclusion of digitization and incorporation of predictive analytics provides a base for a sustainable smart city. This work considers an overview of different challenges that utilizes different technologies for within a smart city maintenance with respect to the transportation. A conceptual framework is proposed to handle the generated data for decision for control, monitoring, fault diagnosis and maintenance of more and more complex systems.
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| 23. |
- Arasteh khouy, Iman, et al.
(author)
-
Cost-effective track geometry maintenance limits
- 2016
-
In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 230:2, s. 611-622
-
Journal article (peer-reviewed)abstract
- In the past, railway maintenance actions were usually planned based on the knowledge and experience of the infrastructure owner. The main goal was to provide a high level of safety, and there was little concern about economic and operational optimisation issues. Today, however, a deregulated competitive environment and budget limitations are forcing railway infrastructures to move from safety limits to cost-effective maintenance limits to optimise operation and maintenance procedures. By so doing, one widens the discussion to include both operational safety and cost-effectiveness for the whole railway transport system. In this study, a cost model is proposed to specify the cost-effective maintenance limits for track geometry maintenance. The proposed model considers the degradation rates of different track sections and takes into account the costs associated with inspection, tamping, delay time penalties, and risk of accidents due to poor track quality. It draws on track geometry data from the Iron Ore Line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to estimate the geometrical degradation rate of each section. The methodology is based on reliability and cost analysis and facilitates the maintenance decision-making process to identify cost-effective maintenance thresholds.
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| 24. |
- Asim, Muhammad, et al.
(author)
-
Experimental analysis of solar thermal integrated MD system for cogeneration of drinking water and hot water for single family villa in Dubai using flat plate and evacuated tube solar collectors
- 2017
-
In: Desalination and Water Treatment. - : DESALINATION PUBL. - 1944-3994 .- 1944-3986. ; 92, s. 46-59
-
Journal article (peer-reviewed)abstract
- This paper presents the experimental analysis performed on solar thermal integrated membrane distillation (MD) system using flat plate and evacuated tube collectors. The system will be utilized for cogeneration of drinking water and domestic hot water for single family in Dubai comprising of four to five members. Experiments have been performed in Ras Al Khaimah Research and Innovation Centre (RAKRIC) facility. The experimental setup has been installed to achieve the required production of 15-25 L/d of drinking water and 250 L/d of hot water for domestic purposes. Experiments have been performed on MD setup at optimized flow rates of 6 L/min on hot side and 3 L/min on cold side for producing the desired distillate. The hot side and cold side MD temperature has been maintained between 60 degrees C and 70 degrees C, and 20 degrees C and 30 degrees C. The total annual energy demand comes out to be 8,223 kWh (6,000 kWh is for pure water and 2,223 kWh for hot water). The optimum aperture areas for flat plate and evacuated tube collector field have been identified as 8.5 and 7.5 m(2), respectively. Annual energy consumption per liter for pure water production is 1, 0.85 and 0.7 kWh/L for different MD hot and cold inlet temperatures.
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| 25. |
- Asim, Muhammad, et al.
(author)
-
Feasibility analysis of solar combi-system for simultaneous production of pure drinking water via membrane distillation and domestic hot water for single-family villa : pilot plant setup in Dubai
- 2016
-
In: Desalination and Water Treatment. - : Taylor & Francis. - 1944-3994 .- 1944-3986. ; 57:46, s. 21674-21684
-
Journal article (peer-reviewed)abstract
- This paper presents the feasibility study of installation of a solar-driven integrated MD desalination system for simultaneous production of pure drinking water and solar domestic hot water in United Arab Emirates (UAE) for a single-family villa comprising of 4-5 persons. In order to satisfy the current and future demand of water for domestic purposes, the desalination of seawater is considered to be one of the most effective and strategic technique in UAE. The stress on the underground water aquifers, rapid industrial growth, and increase in urban population in UAE results in the tremendous increase in fresh water demand during the past few decades. Since the local municipalities also provide the desalinated fresh water to the people but they mostly rely on bottled water for drinking purpose. In this paper, the pilot setup plant is designed, commissioned, and installed on site in UAE using air gap membrane distillation desalination process to fulfill the demand of 15-25 L/d of pure drinking water and 250 L/d of domestic hot water for a single-family villa. Experimental analyses have been performed on this setup during summer on flat plate solar collectors having different aperture areas (Experiments have been performed for aperture area of 11.9 m(2) in this research study for feasibility purpose). The average hot-side temperature ranges from 50 to 70 degrees C and average cold-side temperature of 35 degrees C.
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| 26. |
- Asplund, Matthias
(author)
-
Wayside Condition Monitoring System for Railway Wheel Profiles : Applications and Performance Assessment
- 2016
-
Doctoral thesis (other academic/artistic)abstract
- The railway is an important mode of transport, due to its environmental friendliness, high safety level, and low energy consumption combined with a high transport capacity, among other factors. The Swedish railway network is old, there has been almost no expansion of the network during the past few decades, and more traffic is expected. Therefore, there is currently a demand for more track capacity and, in the short term, the existing network is expected to deliver the increased capacity. The railway operators in the network have a large impact on train delays, and wheel failures are one large contributor of delays. Delays destroy capacity and, therefore, capacityconsuming failures, such as abnormal wheels, need to be minimised. This can be achieved by using appropriate condition monitoring for the wheels on the track to find potential capacity consumers before failures happen. Therefore, the condition of the wheel-rail interface is important, since the state of the wheel influences that of the rail and vice versa. The monitoring of rail profiles is already being performed, but the monitoring of wheel profiles is still in the development phase. This thesis treats the applications and performance assessment of a wheel profile measurement system (WPMS), and presents case studies focusing on its system and measurement performance. The proposed applications concern how the information from the WPMS can be integrated with information from other data sources and with physical models to obtain a true current picture of the wheel behaviour. The thesis investigates the measurement performance of the WPMS by using a paired T-test and a number of quality measures, e.g. the reproducibility and repeatability, the precision-to-tolerance ratio and the signal-to-noise ratio. In conclusion, this thesis shows that the WPMS works well with an expected level of reliability in a harsh climate with respect to its measurement and system performance. By combining other data with the data from the WPMS, potentially abnormal wheels can be found in an early stage if the proposed new maintenance limit for the wheel parameter of the flange height is implemented. Furthermore, through adding a physical model to the process, the real contact condition of the actual wheel-rail interface can be evaluated and measurement deviations can be found. However, the wheel parameters, as well as the entire profile, need a high measurement quality with little variation, which seems to be an issue with respect to the measurement performance when advanced calculations are to be done. Therefore, a new approach for evaluating measurement performance has been developed using established statistical tools and quality measures with predefined acceptance limits; with the help of this approach, one can differentiate between the variation in the measurements originating in the different measurement units and the variation originating in the wheels. This new approach can be applied to judge the measurement performance of wheel profile condition-monitoring systems, and can also be implemented for other condition-monitoring systems to evaluate their measurement performance. Finally, this approach promotes the development of a condition-based maintenance policy by providing more reliable information for maintenance decision makers.
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| 27. |
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| 28. |
- Block, Jan, et al.
(author)
-
Spares Provisioning Strategy for Periodically Replaced Units within the Fleet Retirement Period
- 2019
-
In: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348. ; 10:3, s. 299-315
-
Journal article (peer-reviewed)abstract
- Within aviation enterprises, the process of dismantling an aircraft at the end of its life is referred to as parting-out. Obviously, the asset value of the units and materials parted out from the retired airframes can be considerable. The benchmarked best practice within the aviation industry is to dismantle the retired aircraft and use the parted-out spares to support the remaining fleet or to offer them on the surplus market. Part-out-based spares provisioning (PBSP) has been a major focus of attention for aviation companies. The PBSP approach is a complex task that requires a multidisciplinary and integrated decision-making process. In order to control the stock level and fulfil the decision criteria within PBSP, it is necessary to make decisions on the termination, at specific times, of both the parting-out process and the maintenance and repair actions performed on the units.This paper considers repairable units and introduces a computational model to identify the applicable alternatives for repair termination times that will minimize the number of remaining spares at the end of the retirement period, while fulfilling the availability requirement for spares during the PBSP period, at the lowest possible cost. The feasible alternatives are compared with regard to their respective costs, and the most cost-effective solution is selected. The cost model uses estimates of future maintenance requirements, the turn-around times, the cost of the various maintenance tasks, the future spares consumption, and the estimated salvage of spares from retired aircraft. The output of the model is a set of applicable alternatives which satisfy the availability requirements for spares for the active fleet. The method is illustrated using a case study performed on the Saab-105 training aircraft. The results show that the proposed PBSP approach and computational model provide added value from a sustainability point of view, since the use of existing resources is maximized during the retirement process, through the process of reclaiming units and the applicable maintenance termination alternatives. The implementation of the proposed computational model in a PBSP programme provides a detailed and situation-based overview of the stock level dynamics, and contributes to the spares provisioning process by providing solutions to issues such as obsolescence, last-time buys and cannibalization.
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| 29. |
- Famurewa, Stephen Mayowa, et al.
(author)
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Application of Maintenance Performance Measurement for Continuous Improvement in Railway Infrastructure Management
- 2015
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In: International Journal of COMADEM. - 1363-7681. ; 18:1, s. 49-58
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Journal article (peer-reviewed)abstract
- Railway transport infrastructure is a linearly distributed asset that requires an effective performance management system to meet sectional and overall business objectives. In particular, an effective performance measurement system with relevant analysis technique in an ongoing manner is necessary to facilitate continuous improvement. Maintenance performance measurement (MPM) is essential to quantify the impact of past maintenance decisions and actions and also to support new decisions. This article presents the challenges of implementing and using MPM systems for maintenance decisions in the railway industry. Thereafter, a risk matrix with maintenance performance indicators is introduced as a complementary analysis tool to identify weak links on a railway line. A case study of a section on the heavy haul line of the Swedish Transport Administration railway network is presented to demonstrate the application of the risk matrix tool for continuous improvement. The results identified the bottlenecks on the line section, which are improvement opportunities for maintenance performance in terms of service quality and capacity target of the infrastructure manager
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| 30. |
- Famurewa, Stephen Mayowa, et al.
(author)
-
Augmented utilisation of possession time : Analysis for track geometry maintenance
- 2016
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In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 230:4, s. 1118-1130
-
Journal article (peer-reviewed)abstract
- The demand for increased capacity on existing railway networks is a challenge for many Europe-based infrastructure managers; addressing this challenge requires augmented utilisation of track possession time. It is considered that large-scale maintenance tasks such as geometry maintenance can be improved; thus, reducing the on-track maintenance time and allowing more traffic. In this study, an analysis of track geometry maintenance was performed with the objective of reducing the required possession time. The procedure and models for planning and optimizing track geometry maintenance are presented. A statistical model that uses a simulation approach was used to determine the condition of the track geometry, and a schedule optimization problem was formulated to support intervention decisions and optimize the track possession time. The results of the case study show that optimizing the maintenance shift length and cycle length are opportunities to reduce the extent of track possession required for the maintenance of the track geometry. In addition, continuous improvement of the tamping process through lean analysis promises about a 45% reduction in the required possession time for a tamping cycle.
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| 31. |
- Famurewa, Stephen Mayowa, et al.
(author)
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Evaluation of rail wear characteristics on heavy haul track section using measurement data
- 2015
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Conference paper (peer-reviewed)abstract
- The rail is a structural component of track that serves as the running surface, guiding element, load carrier and distributor. The wear of rail is of great interest since it is known to be an important degradation mode that can limit the performance of rail, reduce its life span and significantly increase the life cycle cost of track if not well managed. It is therefore pertinent to study the wear behaviour of rail under increased loading condition and adopted grinding strategy. In this paper, the analysis of rail profile measurement data collected between 2008 and 2013 has been carried out. This is used to evaluate the wear characteristics of curves with different radii on the Swedish iron ore line to provide engineering insight for improving maintenance for better rail performance. The result shows that the average natural wear rate on sharp curves is about 2 times the wear rate on the mild curves and 5 times the wear rate on the tangent tracks. In addition, the typical total wear on sharp curves after 6 years is over 250 mm2 which is about 1½ and 2½ times the wear on mild curves and tangent tracks respectively
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| 32. |
- Famurewa, Stephen Mayowa, et al.
(author)
-
Maintenance analysis for continuous improvement of railway infrastructure performance
- 2015
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In: Structure and Infrastructure Engineering. - : Informa UK Limited. - 1573-2479 .- 1744-8980. ; 11:7, s. 957-969
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Journal article (peer-reviewed)abstract
- Railway transport system is massive and complex, and as such it requires effective maintenance to achieve the business goal of safe, economic and sustainable transportation of passengers and goods. The growing demand for improved service quality and capacity target by railway infrastructure managers requires appropriate maintenance analysis to facilitate continuous improvement of infrastructure performance. This paper presents the application of risk matrix as a maintenance analysis method for the identification of track zones that are bottlenecks that limit operational capacity and quality. Furthermore, an adapted analysis method is proposed to create a hierarchical improvement list for addressing the problem of train mission interruption and reduced operational capacity. A case study of a line section of the Swedish network is presented. The result classifies the zones on the line section into different risk categories based on their contribution to loss of capacity and punctuality. In addition, an improvement list for the lower-level system is presented to facilitate maintenance decisions and continuous improvement at both operational and strategic levels.
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| 33. |
- Famurewa, Stephen Mayowa, et al.
(author)
-
Optimisation of maintenance track possession time : A tamping case study
- 2015
-
In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 229:1, s. 42726-
-
Journal article (peer-reviewed)abstract
- Optimum allocation and efficient utilisation of track possession time are becoming important topics in railway infrastructure management due to increasing capacity demands. This development and other requirements of modern infrastructure management necessitate the improvement of planning and scheduling of large-scale maintenance activities such as tamping. It is therefore necessary to develop short-, medium- and long-term plans for performing tamping on a network or track section within a definite time horizon. To this end, two key aspects of infrastructure maintenance planning are considered in this paper, deterioration modelling and scheduling optimisation. An exponential deterioration function is applied to model the geometry quality of a series of 200 m segments of a 130 km line section, and an empirical model for recovery after tamping intervention is developed. These two models are subsequently used to generate a methodology to optimise a schedule for tamping intervention by minimising the total cost of intervention including the cost of track possession while geometry quality is ascertained to be within a desirable limit. The modelling considers two types of tamping interventions, preventive and corrective, with different intervention limits and tamping machines. The result of this paper suggests a tamping plan which will lead to optimum allocation of track possession time while maintaining the track geometry quality within specified limits.
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| 34. |
- Famurewa, Stephen Mayowa, et al.
(author)
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Scheduling of Railway Infrastructure Maintenance Tasks Using Train Free Windows
- 2016
-
In: Current Trends in Reliability, Availability, Maintainability and Safety. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319235967 - 9783319235974 ; , s. 425-436
-
Conference paper (peer-reviewed)abstract
- Condition based maintenance scheduling is a promising approach towards effective track possession management in railway transport. If the maintenance tasks arising from condition monitoring and inspection of railways are efficiently scheduled, high service quality and capacity would be assured. In this paper, the authors presents a short-term maintenance scheduling problem to efficiently use available train-free periods for restoration of potential failures such that availability and capacity are maximised. The formulated problem focuses on reducing the possession cost and penalty cost. It is modelled as a quadratically constrained mixed integer programming problem and solved using a branch and cut algorithm. A case study on the Swedish iron ore line is used to demonstrate the use of the scheduling approach for effective track possession management.
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| 35. |
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| 36. |
- Galar, Diego, et al.
(author)
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SMART maintenance and prescriptive asset management for mining
- 2016
-
Conference paper (peer-reviewed)abstract
- Operation and maintenance (O&M) activities are commonly organized into scheduled and unscheduled actions. Scheduled maintenance is undertaken during pre-programmed inspections. Such maintenance operations try to minimize the risk of deterioration based on a priori knowledge of failure mechanisms and their timing. However, in complex systems it is not always possible to schedule maintenance actions to mitigate all undesired effects, and SMART systems, which monitor selected parameters, propose actions to correct any deviation in normal behaviour. Indeed, SMARTness is one step beyond the prediction of failure time but also a proposition of operation and maintenance profiles in order to fulfill the company goals. Therefore prognosis and RUL estimation become a part of the process in order to achieve prescriptive actions and control the degradation and operational aspects of the asset as per expected demand and customer request. These O&M decisions must be made on the basis of accepted risk. Performed or unperformed scheduled tasks as well as deferred corrective actions can have positive or negative consequences for the company, technicians, and machines. These three risks should be properly assessed and prioritized as a function of the goals to be achieved. This paper focuses on the SMARTness of assets in order to go one step forwards and propose prescriptive O&M decisions based on a self-risk assessment as a trade-off for asset integrity and company goals.
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| 37. |
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| 38. |
- Garmabaki, Amir, et al.
(author)
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A Reliability Decision Framework for Multiple Repairable Units
- 2016
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In: Reliability Engineering & System Safety. - : Elsevier BV. - 0951-8320 .- 1879-0836. ; 150, s. 78-88
-
Journal article (peer-reviewed)abstract
- In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplines. This paper presents a decision framework to identify an appropriate reliability model for massive multiple repairable units. It splits non-homogeneous failure data into homogeneous groups and classifies them based on their failure trends using statistical tests. The framework discusses different scenarios for analysing multiple repairable units, according to trend, intensity, and dependency of the units’ failure data. The proposed framework has been verified in a fleet of aircraft and in two simulated data sets. The results show a reliability model of multiple repairable units may contain a mixture of different stochastic models. Considering single reliability models for such populations may cause erroneous calculation of the time to failure of a particular unit, which can, in turn, lead to faulty conclusions and decisions. When dealing with massive and non-homogeneous multiple repairable units, the application of the proposed framework can facilitate the selection of an appropriate reliability model.
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| 39. |
- Garmabaki, Amir, et al.
(author)
-
Data driven RUL estimation of rolling stock using intelligent functional test
- 2017
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In: Risk, Reliability and Safety. - London : CRC Press. - 9781138029972 - 9781315374987 ; , s. 1994-1999
-
Conference paper (peer-reviewed)abstract
- The rolling stock health condition is important for both passenger and freight trains in terms of safety, availability, punctuality and efficiency. Various inspection and maintenance methodologies are per-formed on rolling stock equipment to fulfill the above performance measures. This paper suggests a new approach, namely, intelligent functional test (IFTest) to estimate the remaining useful life (RUL) of the equipment, sub-systems and systems of rolling stock dynamically by data driven methods. IFTest generates a baseline of the current operational abilities in contrast to the required abilities. The test integrates the historical and new set of data to track the trend of degradation of equipment. With this approach, the operation and maintenance personnel have ample time to make decisions for the maintenance and failure consequences. In addition, it is supposed that by using such data we are achieving a more accurate result for the estimation of reliability and RUL of critical rolling stock equipment.
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| 40. |
- Garmabaki, Amir H. Soleimani, et al.
(author)
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A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections
- 2019
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In: Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019). - Singapore : Research Publishing Services. ; , s. 1094-1101
-
Conference paper (peer-reviewed)abstract
- Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures are critical for society and industry resulting in direct and indirect costs for all the related stakeholders. Pipeline failures are complex processes, which are affected by many factors, both static (e.g., pipe material, size, age, and soil type) and dynamic (e.g., traffic load, pressure zone changes, and environmental impacts). These failures have serious impacts on public due to safety, disruption of traffic, inconvenience to society, environmental impacts and shortage of resources. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within transportation infrastructure. The aim of this study is to identify failure modes and consequences related to the crossing of pipelines in railway corridors. Expert opinion have been collected through two set of questionnaires which have been distributed to the 291 municipalities in the whole Sweden. The failure analysis revealed that pipe deformation has higher impact followed by pipe rupture at cross-section with railway infrastructure. For underground pipeline under railway infrastructure, aging and external load gets higher ranks among different potential failure causes to the pipeline.
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| 41. |
- Garmabaki, Amir H. S., et al.
(author)
-
Opportunistic inspection planning for Railway eMaintenance
- 2016
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In: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 49:28, s. 197-202
-
Journal article (peer-reviewed)abstract
- Railway infrastructure is a complex system that comprises of several subsystems which interacts in hierarchical, multi-distributive and multi-user environment. It is a difficult task to perform inspections for all the assets at an instant because the train management system decides when to conduct different types of inspection techniques on several assets in a particular track section. There are two main wastes of resources for inspection planning occurred in maintenance; under usage due to inaccurate prediction of failure and over usage because the necessary information already has been acquired from other sources. These irregularities lead to wastage of resources, for instance, human, machine and time that has tremendous implications on cost, availability and manpower. This paper proposes a methodology by using intelligent functional test outcome to assess the performability of an asset and integrating the data to the eMaintenance cloud platform of Swedish railway infrastructure. By implementing this methodology, we can achieve better planning of resources for optimal performance of assets. A case study is performed on Switches and Crossings of Swedish railway infrastructure for the applicability of the proposed methodology.
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| 42. |
- Gerdes, Mike, 1970-
(author)
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Health Monitoring for Aircraft Systems using Decision Trees and Genetic Evolution
- 2019
-
Doctoral thesis (other academic/artistic)abstract
- Reducing unscheduled maintenance is important for aircraft operators. There are significant costs if flights must be delayed or cancelled, for example, if spares are not available and have to be shipped across the world. This thesis describes three methods of aircraft health condition monitoring and prediction; one for system monitoring, one for forecasting and one combining the two other methods for a complete monitoring and prediction process. Together, the three methods allow organizations to forecast possible failures. The first two use decision trees for decision-making and genetic optimization to improve the performance of the decision trees and to reduce the need for human interaction. Decision trees have several advantages: the generated code is quickly and easily processed, it can be altered by human experts without much work, it is readable by humans, and it requires few resources for learning and evaluation. The readability and the ability to modify the results are especially important; special knowledge can be gained and errors produced by the automated code generation can be removed.A large number of data sets is needed for meaningful predictions. This thesis uses two data sources: first, data from existing aircraft sensors, and second, sound and vibration data from additionally installed sensors. It draws on methods from the field of big data and machine learning to analyse and prepare the data sets for the prediction process.
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| 43. |
- Ghodrati, Behzad, et al.
(author)
-
Context-driven mean residual life estimation of mining machinery
- 2018
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In: International Journal of Mining, Reclamation and Environment. - : Taylor & Francis. - 1748-0930 .- 1748-0949. ; , s. 486-494
-
Journal article (peer-reviewed)abstract
- Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.
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| 44. |
- Ghodrati, Behzad, et al.
(author)
-
Lean mining
- 2016
-
In: The Routledge companion to lean management. - New York : Routledge. - 9781317416517 - 9781138920590 ; , s. 302-310
-
Book chapter (peer-reviewed)
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| 45. |
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| 46. |
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| 47. |
- Gustafson, Anna, et al.
(author)
-
Reliability analysis and comparison between automatic and manual load haul dump machines
- 2015
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In: Quality and Reliability Engineering International. - : Wiley. - 0748-8017 .- 1099-1638. ; 31:3, s. 523-531
-
Journal article (peer-reviewed)abstract
- Today's trend of replacing manually operated vehicles with automated ones will have an impact not only on machine design, working environment and procedures but also on machine breakdown and maintenance procedures. In the harsh environment of underground mines, the transition from manual to automatic operation is believed to fundamentally change the basis for break downs, maintenance and machine design. In this paper, differences and similarities between manual and automatic underground loading equipment is analysed from a reliability point of view. The analysis is based on a case study performed at a Swedish underground mine. In the contrary of common thoughts, this paper proves that there is a difference between the manual and semi-automatic machines and in particular for the transmission, in favour of the manual one. This paper also shows a path for detailed reliability analysis, and the results may be used for improving maintenance programmes for other types of mobile equipment
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| 48. |
- Hoseinie, Hadi, et al.
(author)
-
Maintenance planning for drum shearer machine based on its reliability characteristics and economical sensitivity analysis
- 2015
-
In: Safety and Reliability. - London : CRC Press. - 9781138026810 ; , s. 1257-1262
-
Conference paper (peer-reviewed)abstract
- Cutting arms are the main productive units of coal shearer machine that contact directly with coal seam. More importantly, the cutting arms operate under a high stress environment. In this paper, in order to suggest an optimum maintenance plan for the subsystem of shearer machine, firstly, we conducted a failure and reliability analysis using the data acquired from the Parvadeh coal mine Iran over the last two years. In doing so, we applied estimated distribution functions and calculated cost parameters to identify the cost-based optimum preventive maintenance interval. The analysis shows that the Power Law Process model provides a good fit to the failure data. Accordingly, the preventive maintenance operation can improve the reliability of the system by 53.5%. Furthermore, we conducted a sensitivity analysis of the studied machine and identified that if we consider the variation of the world price of the raw coal then the maintenance plan is sensitive to the price, however the effects of this change on reliability improvement is almost zero
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| 49. |
- Hoseinie, Seyed Hadi, et al.
(author)
-
Reliability Centered Maintenance (RCM) for Automated Mining Machinery
- 2016
-
Reports (other academic/artistic)abstract
- Reliability centered maintenance (RCM) was initiated on 1960s in Boeing company to optimize the maintenance process of aircrafts. Since that date, this method has been applied in wide range of industries and has provided a completely positive results and recommendations for implementation in other industries. RCM is a systematic approach to quantitatively assess and optimize the performance of preventive maintenance tasks and to eliminate non-value adding maintenance actions. It provides considerable cost savings due to optimum maintenance effort, increased safety and productivity. This research considers the feasibility of applying the RCM methodology to fully-automated underground mining machineries as one of the vital requirement of early future modern mining. For this purpose, a literature review has been done to clarify the advantages, requirements, issues and challenges of RCM in other industries such as aviation, marine, nuclear, oil and gas, and process industries. It has been tried to analyze the RCM procedure in detailed and to have a look on the adoption issues and requirement for RCM implementation in fully-automated mining. Mainly, in this research, following RCM documents and standards were used for feasibility study: • Classic RCM in Aviation industry (SAE-JA1011, SAE-JA1012)• NASA RCM guidelines • USA’s military standards MIL-STD-2173• International Atomic Energy Agency (IAEA) RCM documentUsing the above mentioned documents, an implementation issues and challenges in developing a RCM program for fully-automated underground mining machineries has been presented. The result of this study shows that RCM is applicable in maintenance planning for fully-automated underground mining machinery. Because, serious safety restrictions are associated with this kind of mining operation and RCM can properly help the engineers to analyze the safety consequences of any failure and make the best decision for maintenance tasks. However, practical application of RCM has some differences in mining context which in this project are discussed in detail. The investigations show the risk priority number is the suitable measure to select the RCM target component/system. Since, there is no operation in site, detective the some evident failures are become impossible in automated mining. Therefore, we have to consider the smartness level and capabilities of agent-based supervisors to get the real feeling of machinery health and operation condition. Internet of Thing platforms are also required in fully automated mine to develop the machine-to-machine communication and to reduce the risk of failures and failure propagation in fleet level. RCM could apply the outcomes of these advanced technologies to optimize the maintenance actions in automated mines.
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| 50. |
- Illankoon, Prasanna, 1977-, et al.
(author)
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A prospective study of maintenance deviations using HFACS-ME
- 2019
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In: International Journal of Industrial Ergonomics. - : Elsevier. - 0169-8141 .- 1872-8219. ; 74
-
Journal article (peer-reviewed)abstract
- The factors initiating aviation accidents are usually hidden behind various steps, systems, and tasks, and systematic root-cause analysis is required to uncover the initial factor(s). To reduce the risk of unfavourable events, it is more appropriate to study their causal factors. We argue that an in-depth study on maintenance process deviations could assist in uncovering hidden causal factors. We therefore analyse reported maintenance deviations from an aviation organisation using the Human Factor Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy to aggregate and map hidden causal factors. We find attention and memory errors and inadequacy of processes and documentation are major causal factors. We argue a well-run organisation can capture hidden causal factors and reduce the risk of incidents and accidents. More specifically, we show how situation awareness (SA) interventions can assist in the mitigation of maintenance deviations and capture hidden causal factors.
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