Min Li, Hangxuan Liu, Xingquan Zhang, Hengji Yang, Lisheng Zuo, Ziyu Wang, Shiwei Duan and Song Shu
The purpose of this paper is to investigate the effect of laser peening (LP) on mechanical and wear properties of 304 stainless steel sheet.
Abstract
Purpose
The purpose of this paper is to investigate the effect of laser peening (LP) on mechanical and wear properties of 304 stainless steel sheet.
Design/methodology/approach
Three-dimensional morphology, micro-hardness and micro-structure of shocked samples were tested. The wear amount, wear track morphology and wear mechanism were also characterized under dry sliding wear using Al2O3 ceramics ball.
Findings
The LP treatment generates deformation twins that contribute to the grain refinement and hardness increase. The wear test displays that the wear mechanism of samples is mainly abrasive wear and oxidation wear at 10 N load. While at 30 N, the delamination and adhesion areas of treated sample are reduced visibly compared to untreated ones.
Originality/value
This study specifically investigates the mechanical and wear properties of 304 stainless steel after the direct action of LP on its surface, which shows an effective improvement on the wear resistance. For example, the wear loss of processed sample is reduced by 19% at 30 N, the friction coefficient decreases from 0.4714 to 0.4308 and the groove depth is reduced from 78.1 to 74.4 µm under same condition.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0007/
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Purpose: To investigate the key technologies facilitating the transition towards Industry 5.0 and analysing the contributions of Nvidia, a prominent leader in this field, to these…
Abstract
Purpose: To investigate the key technologies facilitating the transition towards Industry 5.0 and analysing the contributions of Nvidia, a prominent leader in this field, to these technological advancements.
Significance of the study: Technology companies such as Nvidia play a critical role in this transformation through their innovative solutions. This study addresses the need to understand this evolving landscape and the significant impact of the Nvidia.
Methodology: This study is a qualitative approach that examines the existing literature and secondary case studies pertaining to Industry 5.0, and Nvidia. This study examines Nvidia’s high-performance graphics processing units (GPUs), the digital twin platform Omniverse, and the humanoid robot technology development platform, Isaac.
Findings: The next generation of GPUs with the Blackwell architecture is expected to further advance the development of large language models. The Nvidia Omniverse platform contributes significantly to the development of digital twins, a crucial technology for Industry 5.0. The Nvidia Isaac platform focuses on the development of humanoid robot technology, which is a key component of Industry 5.0. Utilizing realistic simulations with Isaac Sim, imitating human behavior with GR00T, and leveraging the high-performance processing power of Jetson Thor, the platform facilitates the creation of robots capable of safe and effective human–robot collaboration. Nvidia has emerged as a leader in the artificial intelligence (AI), robotics, and gaming sectors because of its innovative and agile company culture.
Practical implications: Companies can leverage Nvidia’s technological solutions to optimize production processes and enhance both efficiency and sustainability. The human–machine collaboration emphasized by Industry 5.0 will necessitate the reshaping of workforce skillsets and operational approaches.
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Qian Yang, Xukang Shen, Yanhui Song and Shiji Chen
This paper aims to explore the citation aging pattern of Library and Information Science (LIS) and further investigate the impact of interdisciplinary citation on the aging of…
Abstract
Purpose
This paper aims to explore the citation aging pattern of Library and Information Science (LIS) and further investigate the impact of interdisciplinary citation on the aging of scientific literature.
Design/methodology/approach
The study examines LIS journal articles published between 2016 and 2020. Articles were retrieved from the Web of Science (WoS) and were organized using Scopus's discipline classification system. Citation aging patterns within LIS are described using literature aging indicators. The study examines the effect of interdisciplinary citations on the literature aging pattern by comparing the half-life of LIS literature and the median age of interdisciplinary citations.
Findings
The study results show that the citation aging rate of LIS in the last five years has been slow, and the rate of slowing down is decreasing. Interdisciplinary citations are sourced from various disciplines, focusing on computer science, social sciences and business. The proportion of self-citations is declining. The Reference Diversity Index (RDI) increases from 0.690 to 0.724 between 2016 and 2020. Currently, the median age of interdisciplinary citations is higher than the LIS's half-life. It has a diminishing effect on the citation aging rate. But the median age of interdisciplinary citations is decreasing. The interdisciplinary citation may contribute to the literature aging rate in the future. The effect of interdisciplinary citation on literature aging needs to be judged dialectically.
Research limitations/implications
This study still has some limitations. Due to the wide variety of citation journals in LIS, there is no database to cover all journals, so it is impossible to match all citation journals with disciplines. Therefore, it is still feasible to analyze interdisciplinary citations based on the two-eight principle for large-scale data. This approach necessarily sacrifices some of the precision of the study. However, the results of this paper can still be helpful for the development of the discipline. In addition, LIS is a discipline with solid cross-cutting properties, and this paper concludes only with this interdisciplinary discipline in mind. It is necessary to test the applicability of the findings to other disciplines.
Originality/value
The study explores the impact of interdisciplinary citation on literature aging from a professional communication perspective. The results reveal underlying reasons for the aging of scientific literature. These findings further enrich the study of the effect of interdisciplinary communication.
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Jing Wang, Ting-Ting Dong and Ding-Hong Peng
Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial…
Abstract
Purpose
Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.
Design/methodology/approach
Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.
Findings
The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.
Originality/value
This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.
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Sirine Ben Yaala and Jamel Eddine Henchiri
This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events…
Abstract
Purpose
This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.
Design/methodology/approach
Over the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.
Findings
By minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.
Practical implications
The adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.
Originality/value
This study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.
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Sanaz Khalaj Rahimi and Donya Rahmani
The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on…
Abstract
Purpose
The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.
Design/methodology/approach
Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.
Findings
Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.
Originality/value
Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.
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Yan Zhou and Chuanxu Wang
Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to…
Abstract
Purpose
Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.
Design/methodology/approach
This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.
Findings
The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.
Originality/value
Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.
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Amir Shariati, Cécile L’Hermitte and Nadia Millis Trent
This study aims to review the prepositioning of relief items literature through a decision-making lens to explore the decisions involved, the factors guiding them and the…
Abstract
Purpose
This study aims to review the prepositioning of relief items literature through a decision-making lens to explore the decisions involved, the factors guiding them and the influence of model design on these decisions. Despite their potential to inform decision-making, quantitative prepositioning models remain underutilised in practice. Understanding the foundational principles that shape model design and their connections to decision-making is crucial for effectively developing and implementing more practical models.
Design/methodology/approach
A systematic literature review was conducted, and 97 relevant papers were analysed bibliographically and thematically. The thematic analysis is guided by the value-focused thinking approach, which provides a structured understanding of the decision-making process by focusing on the decision makers’ values.
Findings
This study identifies key prepositioning decisions related to facilities, inventory and distribution. It highlights efficiency, effectiveness and equity as the main values guiding prepositioning decisions and examines the mutual influence of model design and decisions. Moreover, a decision-making framework for prepositioning problems has been developed, outlining key steps and relevant decisions.
Originality/value
This research provides novel insights into how the decision-making process regarding prepositioning is reflected in quantitative models. It helps researchers choose model designs that better align with decision makers’ priorities and requirements, increasing the models’ practicality. Additionally, it helps decision makers comprehend quantitative models and the reasons behind their mathematical complexities, ultimately improving the effectiveness of decision-making for prepositioning.
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Ji Huang, Monica Jurin, On Kit Tam, Hassan F. Gholipour and Chao Ren
This study evaluates the evolution from traditional to nontraditional financial intermediation (NTFI) in Chinese commercial banks from 2006 to 2021, analysing its impact on bank…
Abstract
Purpose
This study evaluates the evolution from traditional to nontraditional financial intermediation (NTFI) in Chinese commercial banks from 2006 to 2021, analysing its impact on bank performance and risk.
Design/methodology/approach
Accounting measures are used to construct granular activity data, and factor analysis is employed to develop a financial intermediation evolution (FIE) index. The fully modified OLS (FMOLs) estimator is used for nonstationary data analysis, and difference-in-differences (DID) analysis is used for robustness check.
Findings
Chinese banks exhibit unique evolution in financial intermediation compared to developed economies, with greater inter-bank variations over time than intra-bank differences. From 2006 to 2017, three paths were identified: Investment, Fee and Repo models, with a fourth path (the Investment2 model) emerging post-2017. Only the Repo model enhances bank returns (ROA & ROE), while shifts towards NTFI increase liquidity and leverage risks across all models. The evolution of bank business models and their consequent implications on performance and risks are influenced by regulatory objectives and banks’ endeavours in regulatory arbitrage.
Practical implications
Major stakeholders in the banking sector can gain a better understanding of financial intermediation and associated market behaviour, performance and risks, with significant implications for banking regulations and crisis management.
Originality/value
This study provides the first comprehensive overview of the evolution of Chinese commercial banks’ financial intermediation activities over an extended period, uncovering the unique characteristics distinct from the developed economies.
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Bilal Mukhtar, Muhammad Kashif Shad and Fong Woon Lai
The purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the…
Abstract
Purpose
The purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies.
Design/methodology/approach
This was a quantitative study and carried out by applying a research survey. The questionnaire was used to collect the data from 204 Malaysian manufacturing companies of the “consumer products and services” sector listed at Bursa Malaysia, incorporating a five-point Likert scale. All the hypothesized relationships were tested by using the partial least square structural equation modeling (PLS-SEM).
Findings
The empirical results showed that the comprehensive adoption of green technology innovation significantly promotes sustainability performance including economic, environmental and social performance. In addition, innovation capabilities significantly and positively moderate the relationship between green technology innovation and sustainability performance.
Research limitations/implications
The scope of this study is specifically confined to the Malaysian manufacturing listed companies, operating within the consumer products and services sector listed at Bursa Malaysia. Consequently, the findings of this study may not be generalized to manufacturing companies of the different geographical contexts.
Practical implications
The findings of this study may help the top management and policymakers of the Malaysian manufacturing listed companies to scrutinize green technology innovation and innovation capabilities to achieve higher sustainability performance.
Originality/value
This study magnifies and provides new insights into the extant literature by developing a comprehensive research model that concurrently tests the direct and moderation effects between green technology innovation, innovation capabilities and sustainability performance. Additionally, this is the first study to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies. This distinct approach significantly bolsters the originality of this study.