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This paper aims to present a new robustness-based design strategy for thin-walled composite structures under compressive loading, which combines strength requirements in terms of the limit and ultimate load with robustness requirements evaluated from the structural energy until collapse.

In order to assess the structural energy, the area under the load-shortening curve between several characteristic points such as local buckling, global buckling, onset of degradation and collapse load is calculated. In this context, a geometrically nonlinear finite element analysis is carried out, in which the ply properties are selectively degraded by progressive failure.

The advantage of the proposed methodology is observed by analyzing unstiffened composite plates under compressive loading, wherein the lightest plate that satisfies both strength and robustness requirements can be attained.

As a practical implication, this methodology gives a new argument to accept the collapse load close to the ultimate load once robustness is ensured.

The structural energy is employed to investigate the robustness of thin-walled composite structures in postbuckling, and new energy-based robustness measures are proposed. In the design of composite structures, this innovative strategy might lead to a more robust design when compared to an approach that only accounts for the ultimate load.

The purpose of this paper is to attempt to realize the optimization of cascading failure process of urban transit network based on Load‐Capacity model, for better evaluating and improving the operation of transit network.

Robustness is an essential index of stability performance for urban transit systems. In this paper, firstly, the static robustness of transit networks is analyzed based on the complex networks theory. Aiming at random and intentional attack, a concrete algorithm process is proposed on the basis of Dijstra algorithm. Then, the dynamic robustness of the networks, namely cascading failure, is analyzed, and the algorithm process is presented based on the Load‐Capacity model. Finally, the space‐of‐stations is adopted to build the network topology of Foshan transit network, and then the simulation analyses of static and dynamic robustness are realized.

Results show that transit network is robust to random attack when considering static robustness, but somewhat vulnerable to intentional attack. For dynamic robustness analysis, a large‐scale cascade of transit network may be triggered when the tolerance parameter α is less than a value, so that the robustness of transit network can be improved through some reasonable measures.

The results of this study provide useful information for urban transit network robustness optimization.

An effective method for analyzing the static and dynamic robustness of transit network is provided in this paper.

The effects of supply chain risk management (SCRM) on the performance of a supply chain remain unexplored. It is assumed that SCRM helps supply chains to cope with vulnerabilities both proactively by supporting robustness and reactively by supporting agility. Both dimensions are assumed to have an influence on the supply chain's customer value and on business performance. The aim of this research is to provide clarity by empirically testing these hypotheses and scrutinizing the findings by the means of case studies.

The research is empirical. Survey data were collected from 270 manufacturing companies for hypotheses testing via structural equation modeling. Additionally, qualitative data were collected to explore the nature of non‐hypothesized findings.

It is found that SCRM is important for agility and robustness of a company. Both agility and robustness show to be important in improving performance. While agility has a strong positive effect only on the supply chain's customer value, but not directly on business performance, robustness has a strong positive effect on both performance dimensions. This important finding directs the strategic attention from agility‐centered supply chains to ones that are both robust and agile. The case studies provide insights to the fact that robustness can be considered a basic prerequisite to deal with supplier‐side risks, while agility is necessary to deal with customer‐side risks. The amount of agility and robustness needs to fit to the competitive strategy.

Since volatility has increasingly become a prevalent state of supply chains, companies need to consider robustness to be of primary importance to withstand everyday risks and exceptions.

This is the first study to view the relationship between SCRM, agility/robustness, and performance.

The purpose of this paper is to obtain a better understanding on robust performance of a hardening and tempering process producing component worm shaft used in the steam power plant. This research is capable to explaining the variation of process capability in terms of robustness.

This paper proposed a methodology (a combination of simulation, regression modelling and robust design technique) to study robustness of a hardening and tempering process producing component worm shaft used in the steam power plant and process capability acts as a surrogate measure of robustness. In each experimental run, the values of responses and the corresponding multivariate process capability indices across the outer array are determined. The variation of process performance (process capability values) due to random noise variation is studied using a general purpose process control chart (R-chart).

The results provide useful information in term of insensitiveness of the process against the noise (raw material and process noise) variation where the process capability acts as a surrogate measure of process robustness and explains the variation of process capability in term of robustness.

This paper adds to the body of knowledge on robustness of a manufacturing process. This paper may be of particular interest to practicing engineers as it suggests what factors should be more emphasis to achieve robust (consistent) performance from the process.

The originality of this paper lies within the context in which this study is to address key relationships between process robustness and process capability in a manufacturing industry.

This paper aims to propose a logistical network design framework with robustness and complexity considerations.

The paper defines robustness, complexity, and normalised efficiency of a logistical network. A mathematical model is then constructed based on the conceptual framework and applied to a hypothetical case study with varying robustness requirements. The mathematical model is formulated as an Mixed‐Integer Linear Programming problem. Furthermore, the paper introduces a graph‐theoretic view of the logistical network and presents its topological properties such as average path length, clustering coefficient, and degree distribution.

The results show that logistical network configurations can be obtained with desirable robustness levels whilst minimising cost. The relationships of robustness versus normalised efficiency and complexity are also presented. The results show that relationships between logistical network topological properties and robustness exist, as in other real world natural and man‐made complex networks.

Logistical network design is one of the earliest strategic decisions in supply chain management that supply chain managers have to make. Practitioners and researchers typically focus on optimising efficiency and/or responsiveness of logistical networks. It is argued that logistical network designers should also consider robustness and complexity as they are important characteristics of logistical network functionality. The logistical network design frame work successfully incorporates robustness and complexity into design considerations.

This paper newly introduces other important performance measures, robustness and complexity, into the logistical network design objective. The design framework is highly relevant and adds value to logistical network designers and managers.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

The purpose of this paper is to provide groundwork for an emerging theory of supply chain robustness – which has been conceptualized as a dimension of supply chain resilience – through reviewing and synthesizing related yet disconnected studies. The paper develops a formal definition of supply chain robustness to build a framework that captures the dimensions, antecedents and moderators of the construct as discussed in the literature.

The authors apply a systematic literature review approach. In order to reduce researcher bias, they involve a team of academics, librarians and managers.

The paper first, provides a formal definition of supply chain robustness; second, builds a theoretical framework of supply chain robustness that augments both causal and descriptive knowledge; third,shows how findings in this review support practice; and fourth,reveals methodological insights on the use of journal rankings in reviews.

At this stage, managers may benefit from seeing these relationships as clues derived from the literature. The paper is fundamentally a call for researchers to conduct quantitative testing of such relationships to derive more reliable understanding and practical applications.

Rather than presenting empirical findings, this paper reveals to managers that visibility, risk management orientation and reduced network complexity have been the main predictive antecedents of supply chain robustness (as discussed in the academic literature). This provides a potentially important signal as to where to invest resources.

The study is the first to develop a formal definition of supply chain robustness and to establish a comprehensive theoretical framework for understanding the construct.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

Interrupting work continuity provides a way to improve some project performance, but unexpected and harmful interruptions may impede the implementation. This paper aims to mitigate the negative impact caused by work continuity uncertainty based on the notion of robustness.

This paper develops a float-based robustness measurement method for the work continuity uncertainty in repetitive projects. A multi-objective optimization model is formulated to generate a schedule that achieves a balance between crew numbers and robustness. This model is solved using two modules: optimization module and decision-making module. The Monte Carlo simulation is designed to validate the effectiveness of the generated schedule.

The results confirmed that it is necessary to consider the robustness as an essential factor when scheduling a repetitive project with uncertainty. Project managers may develop a schedule that is subject to delays if they only make decisions according to the results of the deadline satisfaction problem. The Monte Carlo simulation validated that an appropriate way to measure robustness is conducive to generating a schedule that can avoid unnecessary delay, compared to the schedule generated by the traditional model.

Available studies assume that the work continuity is constant, but it cannot always be maintained when affected by uncertainty. This paper regards the work continuity as a new type of uncertainty factor and investigates how to mitigate its negative effects. The proposed float-based robustness measurement can measure the ability of a schedule to absorb unpredictable and harmful interruptions, and the proposed multi-objective scheduling model provides a way to incorporate the uncertainty into a schedule.

Modern supply chains have become increasingly vulnerable to disruptions, as evidenced by the recent COVID-19 crisis, the Suez Canal blockage and the war in Ukraine. The purpose of the study was to examine the impact of disruptions on organizations and their supply chains, and to examine which resilience principles and corresponding strategies were effective at maintaining and/or creating competitive advantage.

Anchored in contingent resource-based view theory and organizational information processing theory, the study uses an explanatory mixed-methods explanatory research design consisting of two surveys followed by semi-structured interviews to elaborate on the quantitative results.

The quantitative findings showed that data analytic capability combined with a data driven culture had a positive impact on competitive advantage through improved supply chain robustness. No similar effect for supply chain resilience on competitive advantage was found. This was explained by the qualitative findings which showed that insights enabled data analytic capability led to increased supply chain robustness by encouraging proactive measures such as safety stock and redundancies in the supply chain. However, supply chain resilience required these measures to be in place. Without them, supply chain managers were unable to act upon the insights enabled by visibility.

The empirical findings show that data analytic capability impacts supply chain robustness and resilience in different ways, especially in the context of unprecedented disruptions.