Over years, the International Journal of Performability Engineering (IJPE) has been providing a highly professional and authoritative source of information in the field of performability, which in effect, is not only achieving high level of dependability characterised by optimizing the attributes like quality, reliability, maintainability, safety etc., but also maximizing sustainability by minimizing the material and energy requirements as well as creating minimum waste and environment pollution over the entire life time of systems, products or services.
Prognostics Health Management can in fact be viewed as an essential and important activity of overall performability improvement strategy. The present Special Issue aims to provide an overview of the latest developments in the area of Prognostics and Health Management (PHM) methods and their applications in different technologies. PHM takes past, present and (predicted) future information on the conditions of an equipment and use it to detect degradation, diagnose faults, and predict failures. PHM results are, then, used to guide condition-based and predictive maintenance strategies, with significant improvement of equipment availability and results in substantial savings. This is the reason why considerable attention is being given to the development of improved techniques for health monitoring, fault detection, diagnosis and prognosis.
The six papers collected in this special issue are extended and revised versions of selected works presented at the international Prognostics and System Health Management Conference, PHM 2013, that took place at Politecnico di Milano, Milan (Italy) on September 8-11, 2013. The conference was the 4th edition of the Prognostics and System Health Management Conference series. Close to 250 attendees from universities, research laboratories, industries and consultancy firms shared four days of intense technical and social activities, creating a stimulating and pleasant atmosphere of technical exchange.
The unifying motivation behind the selection of the works is that of reporting on the international advancements in model-based and data-driven PHM techniques, highlighting their capabilities, reliability and cost-effectiveness in diverse practical applications, such as energy production, train and railway, oil and gas, maritime and manufacturing industries.
The first paper by Takahito Kobayashi, Yasukuni Naganuma and Hitoshi Tsunashima shows the effectiveness of condition-monitoring techniques in limiting the drawbacks of components degradation in safety-relevant systems, such as train transportation systems. The authors propose an improvement of an existing condition-monitoring system installed on the Tokaido Shinkansen train line for track irregularity estimation by Inverse Analysis. The novelty is in the capability of track irregularity estimation by using a Kalman filter approach fed with measures taken from accelerometers placed on the car-body above the rear bogie. Thus, the effect of the bending mode of the car-body can be reduced and the condition-monitoring can be based only on the car-body motion. The second paper by Chengpeng Wan, Xinping Yan, Di Zhang, Jing Shi and Shanshan Fu concerns the problem of identifying the hazards of a newly designed system and providing information for its operation and health management. The authors propose a comprehensive framework based on the Analytical Hierarchy Process (AHP) for the identification and ranking of the safety critical factors. Then, measures for optimal health management are identified using a TOPSIS method to tackle the multi-objective and multi-criteria optimization problem that arises. The proposed framework is applied with success to a marine Liquefied Natural Gas (LNG)-diesel engine that is at its early stage of development in the Chinese shipping industry.
The third paper by Marc Hilbert, Christiane Küch and Karl Nienhaus addresses the problem of model-based fault detection in complex industrial systems. The novelty of the proposed approach is that it does not require a model of the entire industrial system. This allows to obtain a remarkable reduction of the computational time for early fault detection. Furthermore, the approach is shown to be able to isolate the cause of the fault and to perform well also when applied to the detection of faults during operational transients. The demonstration of the method is obtained by its successful application to a problem of fault detection in wind turbines.
The fourth paper by Victor Krymsky proposes a Control Theory (CT) model for in-depth understanding of system behaviour, The state-space evolution during the system life-cycle can be used for system reliability quantification and failure time prognosis. In particular, the proposed CT model is shown to be effective for systems with a significant lack of initial reliability information, e.g. the distributions of the components Time To Failure (TTF) variables. In fact, the CT model is shown to easily combine with Imprecise Prevision Theory (IPT) to introduce 'interval-valued probabilities' in the CT model and, thus, quantify the uncertainty of the reliability estimates even if the distributions of the TTFs are unknown or imperfectly known.
The fifth paper by Micaela Demichela, Roberta Pirani and Maria Chiara Leva focuses on hazards and Safety Integrity Levels (SILs) of complex systems. A method is proposed to account qualitatively and quantitatively for the human factors in the logical models of Quantitative Risk Analysis (QRA) techniques. The paper proposes the use of the Integrated Dynamic Decision Analysis (IDDA) framework in association with Task Analysis for identifying all the possible alternative states into which the system could evolve as a logical and temporal sequence of events (including explicitly human interactions). The application of the framework to an unforeseen accidental sequence of events for an hydraulic press shows that the performance of a safety instrumented system in the operational phase is influenced by many factors: in particular, not only the system design and the related testing and maintenance strategies should be taken into account, but also Human and Organizational Factors (HOFs) play a major role.
The sixth paper by Piero Baraldi, Francesca Mangili, Giulio Gola, Bent H. Nystad and Enrico Zio deals with the problem of assessing the health status of critical components in the process industry. Specifically, the authors propose a method for estimating process parameters which are, then, used for assessing the component degradation level. The method is based on a hybrid ensemble of data-driven and physics-based models. A local procedure is adopted to aggregate the different model outcomes, weighed by the models performances on similar training data. A successful application is chosen, with regards to real measurements taken on offshore choke valves located topside at different wells and undergoing degradation due to erosion.
As a final remark, we would like to thank the authors for their outstanding contributions and the reviewers for their hard, timely and professional work; we also wish to acknowledge that this special issue would have not been possible without the kind and sharp support of Prof. Krishna. B. Misra, Editor-in-Chief of the journal, who has given us the opportunity and the assistance necessary to put together such a collection of interesting works. To all of these people goes our sincere professional appreciation and personal gratitude.
Piero Baraldi (B.S. in nuclear engng., Politecnico di Milano, 2002; Ph.D. in nuclear engng., Politecnico di Milano, 2006) is Assistant Professor of Nuclear Engineering at the Department of Energy at the Politecnico di Milano (Italy). He is the current Chairman of the European Safety and Reliability Association, ESRA, Technical Committee on Fault Diagnosis. He is functioning as Technical Committee Co-chair of the European Safety and Reliability Conference, ESREL 2014, and he has been the Technical Programme Chair of the 2013 Prognostics and System Health Management Conference (PHM-2013). He is serving as editorial board member of the international scientific journals such as : Journal of Risk and Reliability and International Journal on Performability Engineering. He is co-author of 56 papers in international journals, 55 in proceedings of international conferences and 2 books. He serves as referee of 4 international journals. (Email: email@example.com)
Francesco Di Maio (B.Sc. in Energetic Engineering, 2004; M.Sc. in Nuclear Engineering, 2006; Double EU-China PhD in Nuclear Engineering, 2010) is Assistant Professor in Nuclear Power Plants at Politecnico di Milano (Milano, Italy). His research aims at developing efficient computational methods for improving a number of open issues relevant for dynamic reliability analysis, system monitoring, fault diagnosis and prognosis, and safety and risk analysis of nuclear power plants. In 2009-2010 he has been Research Fellow of the Science and Technology Programme (STFP) in China, financed by the European Commission, and spent 24 months of practical research at Tsinghua University (Beijing, China). In 2010, he has been appointed as Senior Researcher in City University of Hong Kong. He has published more than 50 articles in peer-reviewed international journals and international conferences proceedings. He is serving as Associate Editor of the International Journal of Performability Engineering. He is Chair of the Italian IEEE Reliability Chapter. (Email: firstname.lastname@example.org )
Enrico Zio (Enrico Zio (B.Sc. in nuclear engng., Politecnico di Milano, 1991; M.Sc. in mechanical engng., UCLA, 1995; PhD, in nuclear engng., Politecnico di Milano, 1995; PhD, in nuclear engng., MIT, 1998) is Director of the Chair in Complex Systems and the Energetic Challenge of the European Foundation for New Energy of Electricite' de France (EDF) at Ecole Centrale Paris and Supelec, full professor, President and Rector's delegate of the Alumni Association and past-Director of the Graduate School at Politecnico di Milano, adjunct professor at University of Stavanger. He is the Chairman of the European Safety and Reliability Association ESRA, member of the scientific committee of the Accidental Risks Department of the French National Institute for Industrial Environment and Risks, member of the Korean Nuclear society and China Prognostics and Health Management society, and past-Chairman of the Italian Chapter of the IEEE Reliability Society. He is serving as Associate Editor of IEEE Transactions on Reliability and as editorial board member in various international scientific journals, among which Reliability Engineering and System Safety, Journal of Risk and Reliability, International Journal of Performability Engineering, Environment, Systems and Engineering, International Journal of Computational Intelligence Systems. His research focuses on the characterization and modeling of the failure/repair/maintenance behavior of components, complex systems and critical infrastructures for the study of their reliability, availability, maintainability, prognostics, safety, vulnerability and security, mostly using a computational approach based on advanced Monte Carlo simulation methods, soft computing techniques and optimization heuristics. He is author or co-author of five international books and more than 170 papers in international journals. (Email: email@example.com)