The fourth industrial era, known as ‘Industry 4.0’ (I4.0), aided and abetted by the digital revolution, has attracted increasing attention among scholars and practitioners in the last decade. The adoption of I4.0 principles in Disaster Risk Management (DRM) research and associated industry practices is particularly notable, although its origins, impacts and potential are not well understood. In response to this knowledge gap, this paper conducts a systematic literature review and bibliometric analysis of the application and contribution of I4.0 in DRM. The systematic literature review identified 144 relevant articles and then employed descriptive and content analysis of a focused set of 70 articles published between 2011 and 2021. The results of this review trace the growing trend for adoption of I4.0 tools and techniques in disaster management, and in parallel their influence in resilient infrastructure and digital construction fields. The results are used to identify six dominant clusters of research activity: big data analytics, Internet of Things, prefabrication and modularization, robotics and cyber-physical systems. The research in each cluster is then mapped to the priorities of the Sendai framework for DRR, highlighting the ways it can support this international agenda. Finally, this paper identifies gaps within the literature and discusses possible future research directions for the combination of I4.0 and DRM.

Industry 4.0, Disaster Risk Management and Infrastructure Resilience: A Systematic Review and Bibliometric Analysis

Successful implementation of construction projects worldwide calls for a set of effective risk management plans in which uncertainties associated with risks and effective response strategies are addressed meticulously. Thus, this study aims to provide an optimization approach with which risk response strategies that maximize the utility function are selected. This selection is by opting for the most appropriate strategies with the highest impact on the project regarding the weight of each risk and budget constraints. Moreover, the risk assessment and response strategy of a construction project in Iran as a case study, based on the global standard of the project management body of knowledge (PMBOK) and related literature, is evaluated. To handle the complexity of the proposed model, different state of the art metaheuristic algorithms including the ant lion optimizer (ALO), dragonfly algorithm (DA), grasshopper optimization algorithm (GOA), Harris hawks optimization (HHO), moth-flame optimization algorithm (MFO), multi-verse optimizer (MVO), sine cosine algorithm (SCA), salp swarm algorithm (SSA), whale optimization algorithm (WOA), and grey wolf optimizer (GWO). These algorithms are validated by the exact solver from CPLEX software and compare with each other. One finding from this comparison is the high performance of MFO and HHO algorithms. Based on some sensitivity analyses, an extensive discussion is provided to suggest managerial insights for real-world construction projects.

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Selecting Appropriate Risk Response Strategies Considering Utility Function and Budget Constraints: A Case Study of a Construction Company in Iran

This paper develops an integrated model for the distribution of post-disaster temporary shelters after a large-scale disaster. The proposed model clusters impacted areas using an Adaptive Neuro-Fuzzy Inference System (ANFIS) method and then prioritizes the points of clusters by affecting factors on the route reliability using a permanent matrix. The model’s objectives are to minimize the maximum service time, maximize the route reliability and minimize the unmet demand. In the case of ground relief, the possibility of a breakdown in the vehicle is considered. Due to the disaster’s uncertain nature, the demands of impacted areas are considered in the form of fuzzy numbers, and then the equivalent crisp counterpart of the non-deterministic is made by Jimenez’s method. Since the developed model is multi-objective, the Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Firefly Algorithm (MOFA) are applied to find efficient solutions. The results confirm higher accuracy and lower computational time of the proposed MOFA. The findings of this study can contribute to the growing body of knowledge about disaster management strategies and have implications for critical decision-makers involved in post-disaster response projects. Furthermore, this study provides valuable information for national decision-makers in countries with limited experience with disasters and where the destructive consequences of disasters on the built environment are increasing.

https://www.mdpi.com/2075-5309/12/4/414/pdf?version=1649333251

Post-Disaster Temporary Shelters Distribution after a Large-Scale Disaster: An Integrated Model

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Developing an integrated model for planning the delivery of construction materials to post-disaster reconstruction projects

Health systems are recognised as playing a potentially important role in many risk management strategies; however, there is strong evidence that health systems themselves have been the victims of unanticipated risks and have lost their functionality in providing reliable services. Existing risk identification and assessment tools in the health sector, particularly in the blood supply chain, address and evaluate risks without taking into account their interdependence and a holistic perspective. As a result, the aim of this paper is to develop a new systemic framework based on a semi-quantitative risk assessment approach to measure supply chain risks, which will be implemented through a case study on the Iranian BSC. This paper identifies and assesses supply chain risks (SCRs) by employing a novel systemic process known as SSM-SNA-ISM (SSI). First, the supply chain and its risks are identified using Soft Systems Methodology (SSM). Then, given the large number of risks, the second stage uses Social Network Analysis (SNA) to identify the relationships between the risks and select the most important ones. In the third stage, risk levelling is performed with a more in-depth analysis of the selected risks and the application of Interpretive Structural Modelling (ISM), and further analysis is performed using the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). The study found that by using the new proposed approach, taking into account risk relationships, and taking a holistic view, various supply chain risks could be assessed more effectively, especially when the number of risks is large. The findings also revealed that resolving the root risks of the blood supply chain frequently necessitates management skills. This paper contributes to the literature on supply chain risk management in two ways: First, a novel systemic approach to identifying and evaluating risks is proposed. This process offers a fresh perspective on supply chain risk modelling by utilising systems thinking tools. Second, by identifying Iranian BSC risks and identifying special risks.

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Developing a Risk Reduction Support System for Health System in Iran: A Case Study in Blood Supply Chain Management

Integration of the lean and resilience paradigms has attracted increasing attention among scientists and practitioners. In an interconnected world, the need to be resilient involves increased readiness to deal with risks from both outside and inside an enterprise, and to be lean involves maximizing value while minimizing waste. The combination of these requirements has been the catalyst for a move towards lean–resilience operations. To better understand this trend, which seeks to help firms retain a competitive position and survive disruptions, this paper provides a systematic literature review of 53 articles identified through the C-I-M-O (context-intervention-mechanism-outcome) framework and examines them using descriptive and content analysis. The results trace the growth of lean–resilience research from its infancy to its current advanced state. This paper also identifies for the first time the lack of structured research on the number and categories of implemented practices and their associated benefits. To address this deficiency, a concept map is developed to provide guidance on the topic, identify gaps and inconsistencies in the literature, understand the state of development and suggest future research directions. The results are used to identify four dominant streams: application, compatibility, integration, and impact assessment in the context of the supply chain, conceptual development and operational research of various organizational and industry sectors. Further topics for investigation are recommended in the form of research questions. The proposed concept map is intended to assist researchers and practitioners to develop knowledge about the integration of lean and resilience paradigms in new contexts and formulate more effective deployment strategies.

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The Integration of Lean and Resilience Paradigms: A Systematic Review Identifying Current and Future Research Directions

Natural hazards can have substantial destructive impacts on the built environment. Providing effective services in disaster areas is heavily reliant on maintaining or replacing infrastructure; thus, post-disaster reconstruction of infrastructure has attracted growing attention. Due to the complex and dynamic nature of infrastructure recovery projects, contractor companies engaged in this work have typically experienced poor performance. Furthermore, from a commercial perspective, the post-disaster reconstruction environment is characterized by fierce competition and market uncertainty, challenging the organizational resilience of companies undertaking this work. One approach for improving contractor performance is the implementation of lean construction, but the literature lacks consensus on its capability to affect organizational resilience. To respond to this problem, a conceptual framework applicable for lean implementation in infrastructure, which explicitly addresses organizational resilience, is required for recovery projects. In parallel, contributing components to effective implementation of lean-recovery and supportive theories for justifying the conceptual framework must be identified. Consequently, this paper proposes a conceptual framework to implement lean practices for the enhancement of organizational resilience. The framework is developed using a systematic research method, wherein 110 research documents were discovered initially, and following processing, 18 relevant documents were identified and analyzed. Through this process, contingency and Transformation-Flow-Value (TFV) theories were identified as an appropriate foundation for a framework to implement lean construction in infrastructure recovery projects.

https://www.mdpi.com/2075-5309/12/3/272/pdf?version=1647938973

Mahyar Habibi Rad

Papers

Industry 4.0, Disaster Risk Management and Infrastructure Resilience: A Systematic Review and Bibliometric Analysis

The Integration of Lean and Resilience Paradigms: A Systematic Review Identifying Current and Future Research Directions

A Conceptual Framework for Implementing Lean Construction in Infrastructure Recovery Projects