| 1. |
- Ahmadi, Mahdieh, et al.
(författare)
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An approach to Symbolic Modelling : a Railway Case study for Maintenance Recovery Level Identification
- 2017
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Ingår i: Proceedings of MPMM 2016. - Luleå : Luleå tekniska universitet. - 9789175838410 ; , s. 187-
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Konferensbidrag (refereegranskat)abstract
- Increasing demand for quality and reliability of the asset is progressively seen as a motivation for improved maintenance procedure and management. Always the role of qualitative maintenance data is neglected in the maintenance recovery level identification. Human factor parameter in the maintenance and qualitative technical data, for instance, maintenance experience, maintenance knowledge, training, quality before maintenance, number of previous maintenance, maintenance documentation and environmental condition can be collected and evaluated to increase the accuracy of maintenance recovery estimation. This information always expressed linguistically and considering their effect in the recovery model is challenging. The aim of this study is to propose a symbolic model to capture the effect of above qualitative factor on maintenance recovery level. Fuzzy inference systems are applied to qualitative expert knowledge to extract the percentage effect which can be incorporated in the recovery level model. The tamping railway case study is considered to validate the model. The results show that the maintenance experience and environmental condition are playing main role in maintenance quality. The application of above method can be extended to asset condition assessment in combination with data driven and physical model
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| 2. |
- Galar, Diego, et al.
(författare)
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Big Data in Railway O&M: A Dependability Approach
- 2022
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Ingår i: Research Anthology on Big Data Analytics, Architectures, and Applications. - : IGI Global. ; , s. 391-416
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Railway systems are complex with respect to technology and operations with the involvement of a wide range of human actors, organizations and technical solutions. For the operations and control of such complexity, a viable solution is to apply intelligent computerized systems, for instance, computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by only applying operation and maintenance activities. Indeed, safety is a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them and trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Big data analytics are expected to improve the overall performance of the railways supported by smart systems and Internetbased solutions. Operation and Maintenance will be application areas, where benefits will be visible as a consequence of big data policies due to diagnosis and prognosis capabilities provided to the whole network of processes. This chapter shows the possibilities of applying the big data concept in the railway transportation industry and the positive effects on technology and operations from a systems perspective. © 2022 by IGI Global. All rights reserved.
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| 3. |
- Galvez, Antonio, et al.
(författare)
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A Hybrid Model-Based Approach on Prognostics for Railway HVAC
- 2022
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 108117-108127
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Tidskriftsartikel (refereegranskat)abstract
- Prognostics and health management (PHM) of systems usually depends on appropriate prior knowledge and sufficient condition monitoring (CM) data on critical components’ degradation process to appropriately estimate the remaining useful life (RUL). A failure of complex or critical systems such as heating, ventilation, and air conditioning (HVAC) systems installed in a passenger train carriage may adversely affect people or the environment. Critical systems must meet restrictive regulations and standards, and this usually results in an early replacement of components. Therefore, the CM datasets lack data on advanced stages of degradation, and this has a significant impact on developing robust diagnostics and prognostics processes; therefore, it is difficult to find PHM implemented in HVAC systems. This paper proposes a methodology for implementing a hybrid model-based approach (HyMA) to overcome the limited representativeness of the training dataset for developing a prognostic model. The proposed methodology is evaluated building an HyMA which fuses information from a physics-based model with a deep learning algorithm to implement a prognostics process for a complex and critical system. The physics-based model of the HVAC system is used to generate run-to-failure data. This model is built and validated using information and data on the real asset; the failures are modelled according to expert knowledge and an experimental test to evaluate the behaviour of the HVAC system while working, with the air filter at different levels of degradation. In addition to using the sensors located in the real system, we model virtual sensors to observe parameters related to system components’ health. The run-to-failure datasets generated are normalized and directly used as inputs to a deep convolutional neural network (CNN) for RUL estimation. The effectiveness of the proposed methodology and approach is evaluated on datasets containing the air filter’s run-to-failure data. The experimental results show remarkable accuracy in the RUL estimation, thereby suggesting the proposed HyMA and methodology offer a promising approach for PHM.
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| 4. |
- Galvez, Antonio, et al.
(författare)
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Development and synchronisation of a physics-based model for heating, ventilation and air conditioning system integrated into a hybrid model
- 2021
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Ingår i: International Journal of Hydromechatronics. - : InderScience Publishers. - 2515-0464 .- 2515-0472. ; 4:3
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a physics-based model which is part of a hybrid model (HyM). The physics-based model is developed for a heating, ventilation, and air conditioning (HVAC) system installed in a passenger train carriage. This model will be used to generate data for building a data-driven mode. Thus, the combination of these two models provides the hybrid model-based approach (HyMAs). The physics-based model of the HVAC system is divided into four principal parts: cooling subsystems, heating subsystems, ventilation subsystems, and vehicle thermal networking. First, the subsystems are modelled, considering the sensors embedded in the real system. Next, the model is synchronised with the real system to give better simulation results and validate the model. The cooling subsystem, heating subsystem and ventilation subsystem are validated with the acceptable sum square error (SSE) results. Second, the new virtual sensors are defined in the model, and their value to future research is suggested
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| 5. |
- Galvez, Antonio, et al.
(författare)
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Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach
- 2021
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 13:12
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Tidskriftsartikel (refereegranskat)abstract
- Heating, ventilation, and air conditioning (HVAC) systems installed in a passenger train carriage are critical systems, whose failures can affect people or the environment. This, together with restrictive regulations, results in the replacement of critical components in initial stages of degradation, as well as a lack of data on advanced stages of degradation. This paper proposes a hybrid model-based approach (HyMA) to overcome the lack of failure data on a HVAC system installed in a passenger train carriage. The proposed HyMA combines physics-based models with data-driven models to deploy diagnostic and prognostic processes for a complex and critical system. The physics-based model generates data on healthy and faulty working conditions; the faults are generated in different levels of degradation and can appear individually or together. A fusion of synthetic data and measured data is used to train, validate, and test the proposed hybrid model (HyM) for fault detection and diagnostics (FDD) of the HVAC system. The model obtains an accuracy of 92.60%. In addition, the physics-based model generates run-to-failure data for the HVAC air filter to develop a remaining useful life (RUL) prediction model, the RUL estimations performed obtained an accuracy in the range of 95.21–97.80% Both models obtain a remarkable accuracy. The development presented will result in a tool which provides relevant information on the health state of the HVAC system, extends its useful life, reduces its life cycle cost, and improves its reliability and availability; thus enhancing the sustainability of the system.
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| 6. |
- Gálvez, Antonio, et al.
(författare)
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Feature Assessment for a Hybrid Model
- 2023
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Ingår i: Proceedings of the 5th International Conference on Maintenance, Condition Monitoring and Diagnostics 2021. - : Springer Nature. ; , s. 43-58
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Konferensbidrag (refereegranskat)abstract
- This paper proposes an assessment of features orientated to improve the accuracy of a hybrid model (HyM) used for detecting faults in a heating, ventilation, and air conditioning (HVAC) system. The HyM combines data collected by sensors embedded in the system with data generated by a physics-based model of the HVAC. The physics-based model includes sensors embedded in the real system and virtual sensors to represent the behaviour of the system when a failure mode (FM) is simulated. This fusion leads to improved maintenance actions to reduce the number of failures and predict the behaviour of the system. HyM can lead to improved fault detection and diagnostics (FDD) processes of critical systems, but multiple fault detection models are sometimes inaccurate. The paper assesses features extracted from synthetic signals. The results of the assessment are used to improve the accuracy of a multiple fault detection model developed in previous research. The assessment of features comprises the following: (1) generation of run-to-failure data using the physics-based model of the HVAC system; the FMs simulated in this paper are dust in the air filter, degradation of the CO2 sensor, degradation of the evaporator fan, and variations in the compression rate of the cooling system; (2) identification of the individual features that strongly distinguish the FM; (3) analysis of how the features selected vary when components degrade.
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| 7. |
- Galvez, Antonio
(författare)
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Hybrid digital twins: A co-creation of data science and physics
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Safety is more important than reliability or efficiency in railway, aerospace, oil & gas, and chemical industries. Regulations are very restrictive in sectors where safety is paramount. This makes maintainers replace critical components in initial stages of degradation, which implies a loss of useful life and a lack of information about advanced stages of degradation for those components. Nevertheless, this lack of data can be overcome using hybrid digital twins, also known as hybrid-model based approaches (HyMAs), which combine data-driven models with physics-based models. This fusion minimizes the occurrence of undesirable failures that may interrupt the functionality of critical systems in a safe or cost-efficient manner.HyMAs have been studied at Luleå University of Technology by other Ph.D. students who found promising direction for future research in prognostics and health management (PHM) applications. Thus, this research work continues the direction defined in previous research with the proposal of HyMAs for a heating, ventilation, and air conditioning (HVAC) system installed in a passenger train carriage orientated to diagnostics and prognostics processes. The proposed hybrid modelling consists of the fusion of data obtained from two sources: data obtained from the real system and synthetic data generated by a developed physics-based model of the HVAC.The HVAC system is considered a system of systems (SoS). Therefore, the physics-based model of the HVAC system is divided into four main systems: heating subsystem, cooling subsystem, ventilation subsystem, and cabin thermal networking subsystem. These subsystems are modelled considering the sensors installed in the real system and soft sensors, also known as virtual sensors, which provide crucial information for fault detection, diagnostics, and prognostics. These sensors defined in the physics-based model generate synthetic data which reproduce the behaviour of the system while a failure mode (FM) is simulated. Verification and validation are key processes to synchronise the response of the physics-based model with the signals obtained from the real system. Hence, the physics-based model is synchronised, verified, and validated using data collected by sensors located in the real system. These steps are conducted following guidelines suggested in the literature.Different datasets containing real data and synthetic data while the HVAC system works in faulty and healthy states are used to train data-driven models for fault detection and diagnostics and to train data-driven models for prognostics.Statistical features, such as shape factor, kurtosis, skewness, and sum square error, among others, are calculated from the selected signals. These features are labelled according to the related FMs and are merged with the features calculated from the data obtained from the real system. The data fusion is classified according to the condition indicators of the system in terms of FMs and level of degradation. The merged features are used to train data-driven models for fault detection and diagnostics. In addition, the real data can be loaded to the physics-based model to predict the degradation of the air filter.Then, the prediction data are loaded to an exponential model that provides an estimation of the remaining useful life (RUL) of the air filter. To improve the prognostics model, the physics-based model is used to generate run-to-failure data which are used to train and test a deep convolutional neural network (CNN) which accurately estimates the RUL of the air filter.
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| 8. |
- Gálvez, Antonio, et al.
(författare)
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Hybrid Model Development for HVAC System in Transportation
- 2021
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Ingår i: Technologies. - : MDPI. - 2227-7080. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Hybrid models combine physics-based models and data-driven models. This combination is a useful technique to detect fault and predict the current degradation of equipment. This paper proposes a physics-based model, which will be part of a hybrid model, for a heating, ventilation, and air conditioning system installed in the passenger vehicle of a train. The physics-based model is divided into four main parts: heating subsystems, cooling subsystems, ventilation subsystems, and cabin thermal networking subsystems. These subsystems are developed when considering the sensors that are located in the real system, so the model can be linked via the acquired sensor data and virtual sensor data to improve the detectability of failure modes. Thus, the physics-based model can be synchronized with the real system to provide better simulation results. The paper also considers diagnostics and prognostics performance. First, it looks at the current situation of the maintenance strategy for the heating, ventilation, air conditioning system, and the number of failure modes that the maintenance team can detect. Second, it determines the expected improvement using hybrid modelling to maintain the system. This improvement is based on the capabilities of detecting new failure modes. The paper concludes by suggesting the future capabilities of hybrid models.
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| 9. |
- Gálvez, Antonio, et al.
(författare)
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Hybrid Models and Digital Twins for Condition Monitoring: HVAC System for Railway
- 2021
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Ingår i: Simulation Notes Europe. - : ARGESIM Publisher. - 2306-0271 .- 2305-9974. ; 31:3, s. 121-126
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Tidskriftsartikel (refereegranskat)abstract
- Safety passenger transportation is more important than efficiency or reliability. Therefore, it is vital to maintain the proper condition of the equipment related to the passengers’ comfort and safety. This manuscript presents the methodology of complete development and implementation of both hybrid model and digital twin 3.0 for an HVAC in railways. The objective of this is to monitor the condition of the HVAC where it matters to the comfort and safety of the passengers in the trains. The level 3.0 of digital twin will be developed for the diagnosis and prognosis of HVAC by using hybrid modeling. The description illustrated in this paper is focused on the methodology used to implement a hybrid model-based approach, and both the need and advantages of using hybrid model approaches instead of data-based approaches. The development considers the importance of safety and environmental risks, which are included in the risk quantification of failure modes. Railway’s maintainers replace critical components in early stages of degradation; thus, the use of a data-driven model loses essential information related to advanced stages of degradation which might decrease the accuracy of the maintenance instructions provided. Physics-based model can be used to generate synthetic data to overcome the lack of data in advanced stages of degradation, and then, the synthetic data can be combined with the real data, which is collected by sensor located in the real system, to build the data-driven model. The combination leads to form hybrid-model based approach with a large number of failure modes that were unpredictable. Finally, the outcome is beneficial for the proper functioning of systems; hence, safety of the passengers.
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| 10. |
- Gálvez, Antonio, et al.
(författare)
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Synthetic Data Generation in Hybrid Modelling of Railway HVAC System
- 2020
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Ingår i: 17th IMEKO TC 10 and EUROLAB Virtual Conference. - : International Measurement Confederation (IMEKO). ; , s. 79-84
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a hybrid model (HyM)for a heating, ventilation and air conditioning (HVAC) system installed in a passenger train. This HyM fuses data from two sources: data taken from the real system and synthetic data generated using a physics-based model of the HVAC.The physical model of the HVAC was developed to include the sensors located in the real system and new virtual sensors reproducing the behaviour of the system while a failure mode (FM) is simulated.Statistical features are calculated from the selected signals. These features are labelled according to the related FMs and are merged with the features calculated from the data from the real system. This data fusion allows us to classify the condition indicators of the system according to the FMs. The merged features are used to train a neural network (NN), which achieves a remarkable accuracy.Accuracy is a key concern of future research on the detection and diagnosis of a multiple faults and the estimation of the remaining useful life (RUL) through prognosis. The outcome is beneficial for the proper functioning of the system and the safety of the passengers.
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| 11. |
- Garmabaki, Amir, et al.
(författare)
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Data driven RUL estimation of rolling stock using intelligent functional test
- 2017
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Ingår i: Risk, Reliability and Safety. - London : CRC Press. - 9781138029972 - 9781315374987 ; , s. 1994-1999
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Konferensbidrag (refereegranskat)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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| 12. |
- Garmabaki, Amir H. S., et al.
(författare)
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Opportunistic inspection planning for Railway eMaintenance
- 2016
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Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 49:28, s. 197-202
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Tidskriftsartikel (refereegranskat)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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| 13. |
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| 14. |
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MPMM 2016, Maintenance, Performance, Measurement & Management : conference proceedings
- 2017
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Proceedings (redaktörskap) (refereegranskat)abstract
- The maintenance function is inherent to production but its activities are not always understood or quantified. A characteristic of maintenance is that its activity involves more than a group of people or a workshop and goes beyond the limits of a traditional department.The scope of maintenance in a manufacturing environment is illustrated by its various definitions. British Standards Institute defines maintenance as a combination of all technical and associated administrative activities required to keep equipment, installations and other physical assets in the desired operating condition or restore them to this condition, some authors indicate that maintenance is about achieving the required asset capabilities within an economic or business context, or consists of the engineering decisions and associated actions necessary and sufficient for the optimization of specified equipment ‘capability’ where capability is the ability to perform a specified function within a range of performance levels that may relate to capacity, rate, quality, safety and responsiveness. However, they all agree that the objective of maintenance is to achieve the agreed-upon output level and operating pattern at minimum resource cost within the constraints of system condition and safety.We can summarize the maintenance objectives under the following categories: ensuring asset functions (availability, reliability, product quality etc.); ensuring design life; ensuring asset and environmental safety; ensuring cost effectiveness in maintenance; ensuring efficient use of resources (energy and raw materials). For production equipment, ensuring the system functions as it should is the prime maintenance objective. Maintenance must provide the required reliability, availability, efficiency and capability of production systems. Ensuring system life refers to keeping the equipment in good condition to achieve or prolong its designed life. In this case, cost has to be optimized to achieve the desired plant condition. Asset safety is very important, as failures can have catastrophic consequences. The cost of maintenance has to be minimized while keeping the risks within strict limits and meeting the statutory requirements.For a long time, maintenance was carried out by the workers themselves, in a more loosely organized style of maintenance with no haste for the machinery or tools to be operational again. However, things have changed.• First, there is a need for higher asset availability. With scale economies dominating the global map, the demand for products is increasing. However, companies suffer financially from the costs of expansion, purchase of industrial buildings, production equipment, acquisitions of companies in the same sector, and so on. Productive capacities must be kept at a maximum, and organizations are beginning to worry about keeping track of the parameters that may affect the availability of their plants and machinery.• The second concern follows from the first. When organizations begin to optimize their production costs and create cost models attributable to the finished product, they start to question maintenance cost. This function has grown to include assets, personnel etc., consuming a significant percentage of the overall organization budget. Therefore, when companies are establishing policies to streamline costs, the question of the maintenance budget arises, followed by questions about the success of this budget. They start to consider availability and quality parameters.A question that has haunted maintenance throughout history now appears: how do we maximize availability at the lowest cost? To answer this question, various methodologies, technologies and batteries of indicators are being developed to observe the impacts of improvements.
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| 15. |
- Seneviratne, Dammika, et al.
(författare)
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Autonomous inspection and maintenance of linear assets
- 2017
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Ingår i: 15th IMEKO TC10 Workshop on Technical Diagnostics 2017. - 9781510844919 ; , s. 194-199
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Konferensbidrag (refereegranskat)abstract
- Linear assets have linear properties, for instance, similar underlying geometry and characteristics over a distance. They show specific patterns of continuous inherent deteriorations and failures. Therefore, remedial inspection and maintenance actions will be similar along the length of a linear asset, but because it is distributed over a large area, the execution costs are greater. Autonomous robots can be programmed for repetitive and specific tasks. Unmanned aerial vehicles and remotely operated vehicles are currently used in different industrial settings in ad-hoc manner for inspection and maintenance purposes. This manuscript provides a conceptual framework for the use of autonomous inspection and maintenance practices for linear assets to reduce maintenance costs, human involvement, etc., whilst improving the availability of linear assets by effective utilization of autonomous robots and data from different sources
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| 16. |
- Teymourian, Kiumars, et al.
(författare)
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Ergonomics contribution in maintainability
- 2017
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Ingår i: Management Systems in Production Engineering. - Luleå : Walter de Gruyter. - 2299-0461 .- 2450-5781. ; 25:3, s. 217-223, s. 180-186
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this paper is to describe an ergonomics contribution in maintainability. The economical designs, inputs and training helps to increase the maintainability indicators for industrial devices. This analysis can be helpful, among other cases, to compare systems, to achieve a better design regarding maintainability requirements, to improve this maintainability under specific industrial environment and to foresee maintainability problems due to eventual changes in a device operation conditions. With this purpose, this work first introduces the notion of ergonomics and human factors, maintainability and the implementation of assessment of human postures, including some important postures to perform maintenance activities. A simulation approach is used to identify the critical posture of the maintenance personnel and implements the defined postures with minimal loads on the personnel who use the equipment in a practical scenario. The simulation inputs are given to the designers to improve the workplace/equipment in order to high level of maintainability. Finally, the work concludes summarizing the more significant aspects and suggesting future research.
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| 17. |
- Teymourian, Kiumars, et al.
(författare)
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Ergonomics Evaluation in Designed Maintainability:Case Study Using 3 DSSPP
- 2021
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Ingår i: Management Systems in Production Engineering. - : Sciendo. - 2299-0461 .- 2450-5781. ; 29:4, s. 309-319
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Tidskriftsartikel (refereegranskat)abstract
- Maintainability is one of the design parameters (reliability, availability, maintainability, and safety (RAMS)) and maintenance is needed to keep the respective design in sustainable use. At the same time, the human is involved in the form of interface and interaction in an engineered product/system designed. Ergonomics is a multi-disciplinary science that considers human capabilities and limitations in a broader sense. The objective of this paper is to integrate ergonomics into the maintainability design process in order to facilitate maintenance operation in lesser; time, cost, easier operation as well as the well-being of human who is involved. In other words, good ergonomics lead to good economics and in a broader sense, sustainability. This investigation shows that designing comfortable workplaces and lesser workload for maintenance operators will be beneficial for the maintainability design process and also improve the meantime to repair MTTR. In order to evaluate the effect of designed work-place and workload on maintainers 3 D Static Strength Prediction Program (3D SSPP) that is commonly used as an ergonomics evaluation tool in scientific studies was applied.
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| 18. |
- Teymourian, Kiumars, et al.
(författare)
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Ergonomics in Maintainability : System and Product Design Process
- 2018
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Ingår i: Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2018. - : FCTUC-DEM. ; , s. 18-23
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Konferensbidrag (refereegranskat)abstract
- Maintainability is key part of RAMS estimation and prediction in complex assets. Indeed, availability calculation comprises accurate estimation of maintainability and many times, it is just a time stamp for MTTR estimations. However, maintainability is a human related figure where the skill, capabilities, tools and the design of the asset play key role in its performance. The aim of this article is to describe the effects of ergonomist contribution during maintainability process for system/products design. System designer thinking in system and its subsystem in a way of technical functionality. On the other hand, ergonomist are expertise in human capability and limitation. If human, become a part of system than their interface and interaction become crucial factors in a success of system performance and its sustainability. In this paper, it has discussed four main issues that help the process of maintainability design. These issues are safety (Safety I and Safety II), task analysis (Hierarchical Task Analysis (HTA) as tool) and risk analysis (using William Fine method). It has also touched reliability engineer’s task in order to increase Overall Equipment Effectiveness (OEE).
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| 19. |
- Teymourian, Kiumars, et al.
(författare)
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Integrating Ergonomics in Maintanability : A Case Study from Manufacturing Industry
- 2019
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Ingår i: Journal of Industrial Engineering and Management Science. - : River Publishers. - 2446-1822. ; 2018:1, s. 131-150
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Tidskriftsartikel (refereegranskat)abstract
- Maintainability is key part of Reliability, Availability, Maintainability and Safety (RAMS) estimation and prediction in complex assets. Indeed, availability calculation comprises accurate estimation of maintainability and frequently, it is just a time stamp for mean time to repair (MTTR) estimations. However, maintainability is a human related figure where the skill, capabilities, tools and the design of the asset play key role in its performance. The aim of this article is to describe the effects of ergonomists’ contribution during maintainability process for system/products design. System designer thinking in system and its subsystem in a way of technical functionality. On the other hand, ergonomists are expertise in human capability and limitation. If human become a part of system than their interface and interaction become crucial factors in a success of system performance and its sustainability. In this paper, it has discussed three main issues that help the process of maintainability design. These issues are safety, task analysis and risk analysis. It has also touched reliability engineer’s task to increase Overall Equipment Effectiveness (OEE). These issues are explained via a case study from a manufacturing industry.
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| 20. |
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| 21. |
- Villarejo, Roberto, et al.
(författare)
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Bottom to Top Approach for Railway KPI Generation
- 2017
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Ingår i: Management Systems in Production Engineering. - : Walter de Gruyter. - 2299-0461 .- 2450-5781. ; 25:3, s. 191-198
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Tidskriftsartikel (refereegranskat)abstract
- Railway maintenance especially on infrastructure produces a vast amount of data. However, having data is not synonymous with having information; rather, data must be processed to extract information. In railway maintenance, the development of key performance indicators (KPIs) linked to punctuality or capacity can help planned and scheduled maintenance, thus aligning the maintenance department with corporate objectives. There is a need for an improved method to analyse railway data to find the relevant KPIs. The system should support maintainers, answering such questions as what maintenance should be done, where and when. The system should equip the user with the knowledge of the infrastructure's condition and configuration, and the traffic situation so maintenance resources can be targeted to only those areas needing work. The amount of information is vast, so it must be hierarchized and aggregated; users must filter out the useless indicators. Data are fused by compiling several individual indicators into a single index; the resulting composite indicators measure multidimensional concepts which cannot be captured by a single index. The paper describes a method of monitoring a complex entity. In this scenario, a plurality of use indices and weighting values are used to create a composite and aggregated use index from a combination of lower level use indices and weighting values. The resulting composite and aggregated indicators can be a decision-making tool for asset managers at different hierarchical levels.
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