Search results

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This study aims to examine the obstacles and approaches to achieving sustainable development in India’s cement solid and hollow brick production business, with a specific emphasis on incorporating the triple bottom line (TBL) concept into strategies for small and medium-sized enterprises (SMEs).

Using the step-wise weight assessment ratio analysis (SWARA)–weighted aggregated sum product assessment (WASPAS) approach, the study prioritized 11 economic, 9 environmental and 14 social sustainability indicators based on information collected from literature and expert opinions.

The study provides valuable insights into the difficulties encountered by SMEs while implementing strategies that focus on the TBL. By putting emphasis on the sustainability criteria, the key areas that require attention to promote sustainability get identified and addressed.

The study’s focus on SMEs in this industry limits its generalizability. To have a more complete picture, future studies may include many areas.

The identified and prioritised sustainability characteristics help small and medium-sized firms (SMEs) design strategies to address sustainable development concerns. The research findings could also inform policymakers and regulatory bodies about the challenges faced by SMEs in the cement and brick production sector regarding sustainability. It could highlight the need for supportive policies and regulations to promote sustainable practices and incentivize SMEs to adopt the TBL approach. The paper can offer practical insights for SME owners and managers on integrating sustainability principles into their business strategies. Actionable recommendations and best practices for enhancing environmental performance, social impact and economic viability within the context of cement and brick production are outlined.

TBL policies improve the sustainability and profitability of small and medium-sized firms (SMEs) and promote environmentally and socially responsible practices that benefit the industry and society. The research paper may facilitate greater engagement and collaboration among various stakeholders involved in the cement and brick production industry, including SMEs, larger corporations, government agencies, non-governmental organizations (NGOs) and local communities. This cooperative approach can encourage open communication, the establishment of trust and coordinated actions to tackle sustainability challenges, ultimately improving social cohesion and collaboration.

This study provides new and valuable insights by investigating the development of TBL strategies in SMEs in the cement solid and hollow brick manufacturing sector in India. The utilization of the SWARA–WASPAS technique brings novelty to research on sustainable development in this field.

The purpose of this paper is to develop a comprehensive understanding of the public safety risks of international construction projects (ICPs) from the perspective of threat and vulnerability. A novel and comprehensive risk assessment approach is developed from a systemic perspective and applied to the Belt and Road Initiative (BRI) to improve the public safety risk management strategy for ICPs in BRI.

First, a public safety risk indicator system was constructed from the two dimensions, namely threat and vulnerability. Next, an integrated measurement model was constructed by combining the Genetic Algorithm-Backpropagation (GA-BP) neural network, fuzzy comprehensive evaluation method and matter-element extension (MME) method. Data from 49 countries involved in the BRI, as well as five typical projects, were used to validate the model. Finally, targeted risk prevention measures were identified for use at the national, enterprise and project levels.

The findings indicate that while the vulnerability risks of typical projects in each region of the BRI were generally low, threat risks were high in West Asia and North Africa, Commonwealth of Independent States (CIS) countries and South Asia.

First, the structure of the public safety risk system of ICPs was analyzed using vulnerability and system theories. The connotation of public safety risk was defined based on two dimensions, namely threat and vulnerability. The idea of measuring threat risk with public data and measuring vulnerability risk with project data was clarified, and the risk measurement was integrated into the measurement results to help researchers and managers understand and systematically consider the public safety risks of ICPs. Second, a public safety risk indicator system was constructed, including 18 threat risk indicators and 14 vulnerability risk indicators to address the gaps in the existing research. The MEE model was employed to overcome the problem of incompatible indicator systems and provide stable and credible integrated measurement results. Finally, the whole-process public safety risk management scheme designed in this study can help to both provide a reference point for the Chinese enterprises and oversea contractors in market selection as well as improve ICP public safety risk management.

Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.

PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.

The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.

In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

A kind of micro-nano hydrophobic ternary microparticles was fabricated from SiO₂/halloysite nanotubes (HNTs) and recycled concrete powders (RCPs), which was then mixed with sodium silicate and silane to form an inorganic slurry. The slurry was further sprayed on the concrete surface to construct a superhydrophobic coating (SHC). Transmission electron microscopy and energy-dispersive X-ray spectroscopy mappings demonstrate that the nano-sized SiO₂ has been grafted on the sub-micron HNTs and then further adhered to the surface of micro-sized RCP, forming a kind of superhydrophobic particles (SiO₂/HNTs@RCP) featured of abundant micro-nano hierarchical structures.

The SHC surface presents excellent superhydrophobicity with the water contact angle >156°. Electrochemical tests indicate that the corrosion rate of mild steel rebar in coated concrete reduces three-order magnitudes relative to the uncoated one in 3.5% NaCl solution. Water uptake and chloride ion (Cl^-) diffusion tests show that the SHC exhibits high H₂O and Cl^- ions barrier properties thanks to the pore-sealing and water-repellence properties of SiO₂/HNTs@RCP particles. Furthermore, the SHC possesses considerable mechanical durability and outstanding self-cleaning ability.

SHC inhibits water uptake, Cl^- diffusion and rebar corrosion of concrete, which will promote the sustainable application of concrete waste in anti-corrosive concrete projects.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise in demand for products from the gourmet industry, little is known regarding the factors that inspire customers to order from online FDAs, subsequently influencing customers’ satisfaction. Considering the knowledge gap, this study utilizes the stimulus-organism-response (S-O-R) model to conceptualize the factors: stimuli (eWOM, online reviews and online deals as external stimuli, and late-night craving and convenience as internal stimuli) that determine the organism level (i.e. customers’ inspiration) to subsequently generate the response (i.e. customers’ satisfaction).

We collected the data from 388 users and analyzed it via partial least squares – structural equation modeling (PLS-SEM).

The results reveal that online reviews, deals, late-night food cravings and convenience positively determine customers’ inspiration and satisfaction. In contrast, eWOM fails to impact customers’ inspiration directly and indirectly, affecting customers’ satisfaction through inspiration. Besides, customers’ inspiration positively mediates the relationship between stimuli (e.g. online reviews, online deals, late-night cravings and convenience) and customers’ satisfaction.

This study is novel in that it explores the impact of internal (late-night craving and convenience) and external (eWOM, online reviews and online deals) stimuli on customer inspiration and subsequently predicts customer satisfaction. We also expand prior studies on food delivery apps by studying customer inspiration as a mediating mechanism between internal and external stimuli and customer satisfaction.

This study aims to analyze the effect of interrupted rolling on microstructures and mechanical properties of Mg–8Li–xGr composite is investigated.

Graphene reinforced composite was developed by using stir casting route and rolled with different reduction in thickness such as 50, 75 and 90%. Microstructure, hardness and tensile characteristics of the rolled samples were evaluated.

Investigation on microstructures of rolled composite depicts that increase in rolling reduction % resulted in fine elongated grains and decreased aspect ratio. Further, it was also observed that increasing percentage of rolling reduction promotes the dissolution of ß Li phase and as a result the ductility of composite decreases. Interrupted rolled samples showcase higher hardness when compared with as-cast composite. Composite rolled with 90% reduction displays higher yield strength of 219 MPa. Hardening capacity of composites decreases with increase in reduction percentage due to the effective reduction in grain size.

Investigation on the influence of interrupted rolling on microstructures and mechanical properties of Mg graphene composite. The in-depth understanding of this will help to improve its wide spread application.

This study analyzes how possessing female chief financial officers (CFOs) on boards in emerging economies impacts on firm investment efficiency and addresses overinvestment and underinvestment tendencies of firms based on this aspect. The study draws from resource-based and stakeholder theories. Additionally, it explores how institutional gender parity influences this relationship.

The study uses a two-step system generalized method of moment (GMM) estimation technique to test its hypotheses. Data span from 2010 to 2021 and cover firms in emerging economies. The approach addresses endogeneity and accounts for unobserved heterogeneity in the data.

The study’s results support the hypothesis that firms with female CFO decrease overinvestment and underinvestment tendencies, indicating improved investment efficiency. This effect is more pronounced in emerging economies with higher gender parity and support for female leadership.

The study’s findings suggest fostering gender parity and female leadership in emerging economies to maximize the benefits of female CFO board membership. Policymakers should advocate for corporate governance practices and gender parity through supportive policies to advance economic outcomes and competitiveness.

This study advances existing literature by highlighting the positive outcomes of having female CFOs on boards in emerging economies. It emphasizes gender diversity’s importance in leadership and advocates for inclusive institutional frameworks.