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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.

Environmental disasters are preventable, but this remains a complicated and elusive prospect. This article discusses factors that combine to limit and undermine environmental disaster prevention efforts and explores directions for improved theory and practice.

The challenge of integrating root cause analysis of environmental disasters with interventions and preventive measures at later stages of disaster incubation is outlined. The prospect of learning and transferring lessons from past environmental disasters is discussed. Eighteen environmental disaster cases are summarized and analyzed.

A range of factors, including complexity, lack of lesson transfer, perceived lack of incentives and inaction, limits advances in environmental disaster prevention. Theoretical challenges involve better bridging of root cause and incubation analyses, enhanced understanding of the nature and discipline of foresight and greater documentation of alternative approaches to prevention, including post–normal techniques. Although a transformative breakthrough in environmental disaster prevention is unlikely, substantial progress could be made through better lesson transfer and application of alternative approaches.

This article draws attention to problems and opportunities surrounding the challenge of environmental disaster prevention and proposes directions for improved theory and practice.

This paper aims to propose a novel model that addresses the limitations of current practices, through considering quantitative and qualitative criteria in the decision-making process for equipment replacement.

Literature review and consultation with professionals in the heavy construction industry was conducted to identify the criteria influencing the replacement of construction machines. A questionnaire survey using analytic hierarchy process and multi-attribute utility theory was used to rank these criteria and establish their utility scores. Sensitivity analysis was performed to assess how adjustments in the weights of main criteria would impact equipment replacement decisions.

The identified criteria were classified into three categories: economic, technical and socioenvironmental, encompassing a total of 15 criteria. The findings indicated that salvage value/meeting payback period/maximizing profitability held the highest importance in the replacement process, followed by considerations like high repair and maintenance cost; working condition and economic conditions. Safety and social benefits scored the least among all criteria and categories.

This study focuses on earth-moving equipment and involves experts from the Eastern Province of Saudi Arabia. The model introduces a novel methodology to aid decision-makers, particularly contractors and project managers, in determining when to replace heavy construction equipment, which results in resource efficiency and time saving.

The model integrates expertise and knowledge from experts to establish criteria for replacing construction equipment. This research aims to improve the functionality of the decision-making process regarding the acquisition or replacement of equipment throughout its lifespan.

The study aimed to address how recruits perceive their roles and develop professional identities during in-classroom and in-field training.

This study explored the professional identity formation process by analysing asynchronous surveys with recruits from 13 municipal police departments in British Columbia, Canada. The participants were surveyed twice: after classroom-based training following Block I at the British Columbia Police Academy (BCPA) and after their departmental field training following Block II.

The analysis revealed that police recruits lacking public safety experience transformed their occupation and lifestyle. The training at the police academy helped develop recruits' muscle memory as they applied their knowledge to the situation through hands-on practice. Moreover, teamwork at the police academy and during field training allowed recruits to form their police identity. The study was conducted between 2020 and 2021 during the COVID-19 pandemic, thus revealing how the recruits learnt effectively whilst facing continuous challenges and adjusting.

This study relied solely on the respondents' language in text-based answers; therefore, it was not possible to ask follow-up questions or seek clarification. Consequently, several inputs were excluded from the analysis. This would not have been the case if a quantitative method, where answers can be selected accurately, had been used.

This study demonstrates that police recruits acquire diverse competencies and skill sets through rigorous formal requirements, nuanced informal aspects and comprehensive training at the BCPA and during field training, all of which pivotal in shaping their professional identities.

Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.

A total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.

The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.

This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

The relationship between medicine and video games is growing tremendously. In the field of medicine, realistic simulation and games have risen in popularity, and in turn, gamification has transformed the game elements into a non-gaming world for human engagement like motivation and performance. It is not surprising that game-based learning has branched out in the realm of the medical world. The person’s psychological state determines the effectiveness of education during training. This study aims to examine how the usage of immersive technology impacts users’ tendency to access immersive resources for learning during an emergency like the COVID-19 pandemic. Augmented reality (AR) apps have grown to be a popular tool in education nowadays. The purpose of using AR applications is to impart knowledge during the COVID-19 pandemic. An investigation was conducted to test the effectiveness of immersive technology in learning by developing a game-based experimental model and testing it on 100 non-randomly selected users of various ages. This study shows that users are open to new teaching approaches, including AR applications, in response to the challenges presented by the pandemic. AR applications provide a potential solution to the difficulties associated with education by providing an immersive and interesting experience that enhances learning-based results. This demonstrates that while using AR apps, an individual’s viewpoints and sense of control over their learning are more essential in influencing their conduct. By integrating AR apps into learning systems, immersive education may enhance users’ engagement, motivation and overall learning experiences.

Convenience sampling was chosen as the method for data analysis. One hundred users from a leading private university in the northwest part of India participated in this study. This gave a minimum sample size of 79 participants. To analyse the user experience (UX), a UX questionnaire was adopted. In this research paper, the researcher explores the importance of immersive games that emphasise awareness and experience through a series of questionnaires to assess the effective awareness of COVID through immersive technology, because the immersive element plays a major role in the quality and success of awareness through COVID-19 fighter video games as an interactive learning platform.

Results showed that most people do not know how to deal with an infected person in a critical situation; either they feel scared or deal without taking precautions. COVID-19 fighters are empowered with a virtual patient, which players can interact with. Once the user finishes the FPS game, he must find out the source of viruses that will be an AR-based virtual patient. The first step of the instruction will ask the user to give the mask to the infected person; in the second step, it will ask the user to sanitise his body. In the third step, it will ask to hospitalise.

The research offers empirical evidence on the effectiveness of augmented reality-based game approaches to increase reality in basic education to boost the awareness of individuals. The report also gives an example of good cross-cutting education materials that provide the player with a very valuable tool for understanding knowledge of covid awareness by playing the COVID-19 fighter game.

Energy consumption has increased significantly since the 1970s, which has increased demand for sufficient infrastructure in the oil and gas industry. Many top-notch oil and gas companies invested in and equipped their facilities with high-capacity electrical equipment to meet high demand and benefit from high revenues. This is becoming a challenge nowadays for old facilities in the oil and gas industry, as most of the electrical equipment installed has reached or even exceeded its lifetime. Moreover, many of the original equipment manufacturers (OEMs) for electrical equipment from the 1980s are no longer in market today. Therefore, the aim of this study is to develop a proactive, cost-effective obsolescence management framework for electrical equipment in the oil and gas industry, considering the aging factor of the equipment.

Firstly, the study begins with gathering available information and identifying criteria. Secondly, the data collection is evaluated by subject-matter-experts (SMEs) in asset management field to ensure compliance with updated international standards and relevant regulatory requirements. Thirdly, a multi-criteria decision-making process is used to rank criteria. Finally, a scoring system is developed to measure the electrical equipment obsoleteness.

The developed framework will assist decision-makers in making informed decisions about maintenance, replacement or upgrades, using knowledge from previous studies and experts’ input. The result finding indicates that considering aging correction factors when measuring equipment obsoleteness leads to accurately and correctly predicting the electrical equipment obsoleteness score.

Previous studies have addressed obsolescence management without taking equipment age into account, regardless of how the equipment is performing. Thus, the lack of a comprehensive obsolescence management framework that accounts for both cost-effectiveness and the aging factor in the oil and gas industry poses a critical challenge.

The domains of Industry 4.0 and Smart Farming encompass the application of digitization, automation, and data-driven decision-making principles to revolutionize conventional sectors. The intersection of these two fields has numerous opportunities for industry, society, science, technology and research. Relatively, this intersection is new, and still, many grey areas need to be identified. This research is a step toward identifying research areas and current trends.

The present study examines prevailing research patterns and prospective research prospects within Industry 4.0 and Smart Farming. This is accomplished by utilizing the Latent Dirichlet Allocation (LDA) methodology applied to the data procured from the Scopus database.

By examining the available literature extensively, the researchers have successfully discovered and developed three separate research questions. The questions mentioned above were afterward examined with great attention to detail after using LDA on the dataset. The paper highlights a notable finding on the lack of existing scholarly research in the examined combined field. The existing database consists of a restricted collection of 51 scholarly papers. Nevertheless, the forthcoming terrain harbors immense possibilities for exploration and offers a plethora of prospects for additional investigation and cerebral evaluation.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

The paper proposes that the incorporation of Industry 4.0 technology into agricultural operations can enhance efficiency, production and sustainability. Furthermore, it highlights the significance of creating user-friendly solutions specifically tailored for farmers and companies. The study indicates that the implementation of supportive legislative frameworks, incentive programmes and resource conservation methods might encourage the adoption of smart agricultural technologies, resulting in the adoption of more sustainable practices.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

Based on a thorough examination of existing literature, it has been established that there is a lack of research specifically focusing on the convergence of Industry 4.0 and Smart Farming. However, notable progress has been achieved in the field of seclusion. To date, the provided dataset has not been subjected to analysis using the LDA technique by any researcher.

With the increasing agility of IT enterprises, it is crucial to identify suitable managerial strategies for controlling information system development (ISD) projects in the new agile working environments. These environments are characterized by the collaborative nature of work and the recurring nature of communication. This study aims to explore how perceived transparency in ISD processes, controlled by transparency strategies, impacts project quality.

In collaboration with a firm that implemented a customized Scaled Agile Framework, questionnaires were distributed to employees involved in ISD projects. The goal was to understand the influence of perceived transparency in ISD processes on project quality.

Our research demonstrates that perceived transparency in ISD processes enhances project quality through knowledge exchange by strengthening goodwill trust among team members. Additionally, transparency improves project quality through client feedback by strengthening competence trust of clients toward the team. Goodwill trust of clients toward the team and competence trust among team members have less impact on project quality enhancement.

This study reveals the nomological network among the perceived transparency, different types of trust among stakeholders, social interactions among stakeholders, and project outcomes in agile ISD environments. This nomological network has been overlooked by previous studies that biased toward top-down, interorganizational communication. It highlights that not all types of trust among stakeholders are involved in the processes through which perceived transparency influences ISD project quality in agile working environments. Additionally, it exposes the limitations of transparency strategies for controlling projects in agile IT enterprises.

A major obstacle regarding the measurement of an organization's sustainability and accountability in the space economy is defining the context and boundaries of commercial activity in outer space. Here, we introduce an ecosystem framework to address this obstacle. We utilize this framework to analyze the space mining sector. Our ecosystem framework sets the space mining sector's boundaries and helps a firm identify key stakeholders, activities, policies, norms and common pool resources in that sector and the interactions between them; a significant step in structuring how to measure space sustainability and accountability.

Borrowing theories and perspectives from a wide range of academic fields, this paper conducts a comprehensive context analysis of the space mining ecosystem.

Using our ecosystem framework to define the context and set boundaries for the space mining sector allowed us to identify sustainability-related issues in the sector and offer roadmaps to develop sustainability measures and standards.

To the best of the authors’ knowledge, this is one of the first papers to introduce a framework to define boundaries in the global space economy and provides a tool to understand, measure and evaluate the space mining sector's environmental, social and economic issues.