Article
Business
Alberto F. De Toni, Elena Pessot
Summary: Understanding and properly facing the increasing complexity of projects is crucial for success in project-based organisations. This paper provides insights into the interplay between project complexity and organisational learning, highlighting the need for different organisational learning processes based on the dimensions of complexity identified in literature. The study conducted in a leading shipbuilding company reveals the importance of specific behaviors and approaches for organizational learning in addressing complexity issues within projects.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Gozde Bilgin, Irem Dikmen, M. Talat Birgonul, Beliz Ozorhon
Summary: Project portfolio management is a systematic process that involves assessing portfolio risk and profitability, as well as the alignment of projects with company objectives. This study developed a tool called COPPMAN to support decision-making in construction companies, which was found to be effective in practice. The research design and findings can be applied to the development of similar tools in other project-based industries.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Management
Behrang Manouchehrabadi, Paolo Letizia, George Hendrikse
Summary: The article examines how committee members interact and make project selection decisions under democratic and elite governance structures. It is found that the efficient committee governance structure can be determined by focusing on specific communication between elite and common committee members.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Forestry
David E. Calkin, Christopher D. O'Connor, Matthew P. Thompson, Richard Stratton
Summary: The USDA Forest Service initiated the Risk Management Assistance (RMA) program in 2016 to improve strategic decision-making on large and complex wildfire events. RMA involves personnel from various disciplines to produce actionable science, aligning with best practices in risk assessment and decision-making. Over the years, RMA has evolved in content, structure, and application domain, expanding from large incident support to pre-event assessment and organizational change.
Article
Computer Science, Artificial Intelligence
Ru Wang, Anand Balu Nellippallil, Guoxin Wang, Yan Yan, Janet K. Allen, Farrokh Mistree
Summary: Process knowledge is crucial for the digitalization and intelligentization of the manufacturing industry. The management of complexity and uncertainty in model-based engineered systems is critical to achieving rational, comprehensive, and robust decisions. The proposed decision-centric design process representation scheme aims to support the management of complexity and uncertainty in decision-making processes.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Irem Dikmen, Guzide Atasoy, Huseyin Erol, Hazal Deniz Kaya, M. Talat Birgonul
Summary: This research aims to develop a decision-support tool that can estimate the level of risk and required contingency in a project by assessing complexity factors and contextual information. The tool has demonstrated promising results in terms of usability and prediction through testing on 11 mega construction projects.
COMPUTERS IN INDUSTRY
(2022)
Article
Computer Science, Cybernetics
Yao Zhang, Xin Guan
Summary: This paper proposes a method to allocate response budget from preventive and protective perspectives using fault tree analysis and optimization model. The study finds that response budget should be allocated based on events with the greatest expected loss and risk causes with highest occurrence probability.
Article
Computer Science, Artificial Intelligence
Sena Aydogan, Gul E. Okudan Kremer, Diyar Akay
Summary: The study introduces a linguistic summarization approach based on fuzzy sets for describing a realistic complex network of a bike supply chain, calculating the truth degree of generated summaries using fuzzy cardinality-based methods to overcome inherent disadvantages.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Engineering, Industrial
Libiao Bai, Huijing Shi, Shuyun Kang, Bingbing Zhang
Summary: The authors of this study have developed a quantitative evaluation model based on a fuzzy Bayesian network to analyze project portfolio risk considering the interdependency effect. The findings indicate that the interdependency effect can lead to high-stake risks such as weak financial liquidity, a lack of cross-project members, and project priority imbalance. The model can help systematically assess and manage the complicated and interdependent risks associated with project portfolios.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Hadi Jaber, Franck Marie, Ludovic-Alexandre Vidal, Ilkan Sarigol, Lionel Didiez
Summary: This research aims to assist managers in anticipating, detecting, and managing complex situations to avoid negative consequences. It introduces a framework with 90 factors to measure project complexity and utilizes fuzzy techniques to provide early warning signs.
Article
Computer Science, Information Systems
Dan Wang, Qian Jia, Ruixue Zhang
Summary: This study introduced prospect theory and constructed a risk management behavior game model to analyze the behavior evolution between owners and contractors in the construction stages of engineering projects. The results revealed that positive risk management is a stable evolutionary strategy for both parties, but differences in risk perceptions and the effect of prospect theory hindered them from evolving towards the optimal strategy.
Article
Engineering, Civil
Didrik Meijer, Hans Korving, Francois Clemens-Meyer
Summary: This paper introduces the application of hydrodynamic models and the analysis of urban drainage networks using graph-based topological features. A new parameterization method for topological features of looped drainage networks is proposed based on linearized hydraulics and bottleneck identification.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2022)
Article
Forestry
Crystal S. Stonesifer, David E. Calkin, Matthew P. Thompson, Erin J. Belval
Summary: Aircraft play a key role in wildfire suppression globally, but their use also comes with certain risks that require strategic risk management. To address this issue, a framework for risk-informed strategic aviation decision support system has been proposed, utilizing aircraft event tracking data and geospatial datasets to guide decision makers in strategic risk management.
Review
Environmental Sciences
Francesca Perosa, Laura Felicia Seitz, Aude Zingraff-Hamed, Markus Disse
Summary: This article explores the state of multi-criteria analysis (MCA) and decision-support systems (DSS) in flood risk management in Germany. The study finds that MCA and DSS have played a significant role in decision-making, but there are challenges in their applicability, as well as issues related to transparency and participation. Addressing these issues would lead to more holistic, and climate-resilient decisions.
ENVIRONMENTAL SCIENCE & POLICY
(2022)
Article
Engineering, Industrial
Yuning Wang, Xiaohua Jin
Summary: This study has established a comprehensive evaluation system of the structural risk of diversified financing. Based on the validated systematic evaluation, comparison and ranking of the structural risk of diversified financing of CICs by using the BWM, the ranking results can help investors to select the CICs with small structural risk of diversified financing to invest.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2021)
Article
Automation & Control Systems
Yue Xu, Dechang Pi, Shengxiang Yang, Yang Chen, Shuo Qin, Enrico Zio
Summary: This study proposes a novel angle-based bi-objective redundancy allocation algorithm to address the uncertainty issue in multi-objective optimization. The algorithm achieves better performance, reduced computational time, and improved result distribution.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Piero Baraldi, Michele Compare, Enrico Zio, Francesco Cannarile, Zhe Yang
Summary: A recurrent difficulty in applying PHM methods is the evolving environments in which industrial components operate. This is even more complicated for multi-component systems where one component's degradation can affect others, changing their lifetime distributions and signal statistics. The Aramis challenge aims to address this issue by proposing solutions for assessing degradation state in evolving environments and introducing an original metric for evaluating fault detection methods.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Engineering, Multidisciplinary
Seyed Mojtaba Hoseyni, Francesco Di Maio, Enrico Zio
Summary: This study proposes an optimization method to solve the sensor positioning problem in equipment health monitoring. The Subset Simulation (SS) method is used to find the optimal set of sensor positions in a short computational time.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Chemistry, Analytical
Yuhua Yin, Zhiliang Liu, Junhao Zhang, Enrico Zio, Mingjian Zuo
Summary: In this paper, an adaptive sampling framework of segment intervals is proposed to monitor mechanical degradation. The results of the experiments show that the proposed method has better sampling effects compared to existing methods, and the results are closely related to data status and degradation indicators.
Editorial Material
Energy & Fuels
Piero Baraldi, Roozbeh Razavi-Far, Enrico Zio
Article
Computer Science, Artificial Intelligence
Zhe Chen, Xiao-Jun Wu, Josef Kittler
Summary: This paper proposes a Fisher regularized e-dragging framework for image classification, which improves the intraclass compactness and interclass separability of relaxed labels. The Fisher criterion and e-dragging technique are integrated into a unified model, achieving superior performance compared to other classification methods.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Review
Energy & Fuels
Zhaoming Yang, Qi Xiang, Yuxuan He, Shiliang Peng, Michael Havbro Faber, Enrico Zio, Lili Zuo, Huai Su, Jinjun Zhang
Summary: A natural gas pipeline system (NGPS) is a crucial energy transportation network that exhibits complex systemic characteristics. The investigation into NGPS resilience focuses on the constraints of pipeline integrity and reliability, including vulnerability, robustness, and recovery. Based on a literature review and practical engineering insights, the generalized concept of NGPS resilience is elucidated. The research methodologies of NGPS resilience are classified into three types: indicator construction method, process analysis method, and complex networks method. The practical applications of NGPS resilience research are analyzed, which are based on NGPS operation safety, information safety, and market safety. The ongoing applications and detailed measures are also concluded, which can guide the researchers and engineers in NGPS resilience.
Article
Automation & Control Systems
Bingsen Wang, Piero Baraldi, Enrico Zio
Summary: This article introduces a deep multiadversarial conditional domain adaptation network to address the lack of labeled data and inconsistent data distribution in fault diagnostics. The network aligns weighted marginal data distributions class by class using multiple domain discriminators, overcoming the issue of negative transfer caused by limited training data. Two cross-domain fault diagnostic case studies verify the superiority of the proposed method through Friedman and Holm post-hoc tests.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Hardware & Architecture
Zhen Chen, Di Zhou, Enrico Zio, Tangbin Xia, Ershun Pan
Summary: Degradation modeling and prognostics are important for system health management. This study proposes a novel feature fusion-based HI construction method with deep learning and multiobjective optimization. Multiple degradation features are fused by a deep neural network (DNN) and several desired properties for prognostics are used to formulate the objective functions of DNN training. A multiobjective optimization model is generated to balance the complexity and performance of the fusion model. The proposed method is illustrated with two cases to demonstrate its effectiveness and robustness.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Industrial
Haoxuan Zhou, Bingsen Wang, Enrico Zio, Guangrui Wen, Zimin Liu, Yu Su, Xuefeng Chen
Summary: This paper proposes a novel method for dealing with time-varying operating conditions (TVOCs) in condition monitoring (CM). The method is based on a neural network and a state-space model (SSM) to build a hybrid system response model for describing the operating process of equipment under TVOCs. Experiments on accelerated fatigue degradation of bearings validate the effectiveness and superiority of the proposed method, as it eliminates the interference of TVOCs and constructs an effective health indicator (HI).
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Daogui Tang, Yi-Ping Fang, Enrico Zio
Summary: This paper studies cyber attacks on customers' demand-response programs in smart grids by injecting false consumption and generation information. An online detector based on convolutional neural networks is designed to detect the attacks and mitigate impacts. The vulnerability of power distribution systems with and without the detector is analyzed in a case study. The results show that the power distribution systems are vulnerable to the studied cyber attack and the proposed detector can achieve high accuracy and mitigate the impact of fixed change rate attacks, but it is challenging to detect attacks with variable change rates.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Multidisciplinary
Enrico Zio
Summary: This research is positioned in the emerging field of quantum probability theory and its application to reliability analysis in wireless telecommunication networks. The study specifically focuses on the development of a Quantum Bayesian Network (QBN) to calculate the reliability of a 5G wireless telecommunication network. The qualitative comparison with a classical Bayesian Network model showcases the significance of interferences in the calculation of reliability in complex systems such as wireless telecommunication networks.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Mathematics
Enrico Zio, Hadi Gholinezhad
Summary: In this paper, the well-known Redundancy Allocation Problem (RAP) in the field of reliability optimization is investigated. The distribution of the failure time of components is assumed to follow an Erlang distribution with a time-dependent rate parameter, and the choice of redundancy for each subsystem can be none, active, standby, or mixed. A genetic algorithm is used to solve the problem of optimal allocation. Numerical examples and a case study show that the time dependence of failure time distribution parameters can significantly affect the optimal redundancy allocation.
Article
Engineering, Industrial
Lida Naseh Moghanlou, Francesco Di Maio, Enrico Zio
Summary: This paper proposes a probabilistic scenario analysis framework to quantify service losses and assess the economic losses and transport reliability of road-power infrastructure under different car accident scenarios. The framework allows comparing alternative designs and evaluating their performance using graphical representations.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Dario Valcamonico, Piero Baraldi, Enrico Zio, Luca Decarli, Anna Crivellari, Laura La Rosa
Summary: This study investigates the possibility of using information from reports on process safety events (PSEs) in hydrocarbon production assets to support quantitative risk assessment (QRA). A novel methodology combining natural language processing (NLP) and Bayesian networks (BNs) is proposed to estimate the probability of different severity levels of PSEs and identify the factors that have the most influence on their occurrence. The results show that the proposed methodology can identify critical factors for the severity of PSE consequences and inform decisions on system safety improvements.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
