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This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements.

A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company.

Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively.

Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions.

This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

This article empirically tests the impact of risk appetite of the executive team on the re-innovation strategy after technological innovation failure using a panel regression model from the perspective of regional financial development level of enterprises.

By means of time series global principal component analysis and panel regression model method, the study validated and analyzed the impact of risk appetite of the executive team on the re-innovation strategy after enterprise technological innovation failure.

The research found that the higher the risk appetite of executive team, the more inclined the enterprise is to choose the “focusing on quantity, ignoring quality” re-innovation strategy after technological innovation failure. The better the financial development level of the region where the enterprise is located, the better it can effectively reduce the re-innovation strategy of “focusing on quantity, ignoring quality” of the enterprise due to the high risk appetite of the executive team.

The findings of this study are helpful in improving the financial development level of the region where the enterprise is located. It can help the executive team of the enterprise to more objectively choose the innovation strategy after technological innovation failure, and reduce the phenomenon that the executive team of the enterprise only pays attention to the quantity of re-innovation and underestimates the quality of re-innovation after technological innovation failure due to its high risk appetite.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.

This paper aims to analyze what Samarco and Brazilian magazines speak and say about Mariana’s environmental crime. Discover their doxa in this subject. Interpret the speakings, sayings and doxas through the theories of the treadmills of production, crime and law.

It is a qualitative and documental research and a narrative analysis. Regarding the documents: 45 were from public authorities, 14 from Samarco Mineração S.A. and 73 from Brazilian magazines. Theoretically, the authors resorted to Bourdieusian sociology (speaking, saying and doxa) and the treadmills of production, crime and law theories.

Samarco: speaking – mission statements; saying – detailed information and economic and financial concerns; doxa – assistance discourse. Brazilian magazines: speaking – external agents; saying – agreements; doxa – attribution, aggravations, historical facts, impacts and protests.

The absence of discussions that addressed this fatality, with its respective consequences, from an agenda that exposed and denounced how it exacerbated race, class and gender inequalities.

Regarding Mariana’s environmental crime: Samarco Mineração S.A. speaks and says through the treadmill of production theory and supports its doxa through the treadmill of crime theory, and Brazilian magazines speak and say through the treadmill of law theory and support their doxa through the treadmill of crime theory.

To provoke reflections on the relationship between the mining companies and the communities where they settle to develop their productive activities.

Concerning environmental crime in perspective, submit it to a theoretical interpretation based on sociological references, approach it in a debate linked to environmental criminology, and describe it through narratives exposed by the guilty company and by Brazilian magazines with high circulation.

The construction sector is recognized for subjecting its workers to various psychological pressures and mental stressors. As a result, it is crucial to explore and discover effective strategies to support these workers in managing and enduring these demanding circumstances. Mental toughness is a concept that has been advocated to aid individuals in coping and adapting to pressures and challenges. Therefore, it is imperative to explore strategies critical to developing mental toughness among construction professionals. Thus, the purpose of this study is to identify critical strategies for the development of mental toughness among construction professionals.

A comprehensive literature review was conducted using Google Scholar, Scopus, ScienceDirect and PubMed databases to identify the strategies for the development of mental toughness. These identified strategies were used to develop a structured closed-ended questionnaire to aid in data collection. Of the 317 questionnaires distributed, 207 were collected and used for data analysis. The data were analysed using mean score ranking and one sample t-test.

The study highlighted 12 critical strategies for the development of mental toughness among construction professionals. These include recognizing and rewarding achievements, taking time for self-care, organizing mental training programs, using positive self-talk, embracing a growth mindset, providing social support/developing a strong support network, creating a challenging training environment, engaging in regular physical exercise, fostering a mastery motivational climate, setting clear but challenging goals, practicing mental imagery and practicing reflection on setbacks and failures. The analysis results indicated that all of the strategies, except one (which involves practicing reflection on setbacks and failures), displayed significance. By incorporating these strategies, construction firms and the industry as a whole can empower their workforce to cope and/or overcome the various demands and stressors that work and life places on them.

The study highlights the significance of recognizing and rewarding achievements, fostering a growth mindset and implementing mental training programs to cultivate mental toughness among construction professionals. Moreover, promoting self-care practices and offering social support are essential strategies for enhancing mental resilience in the construction industry. By adopting these evidence-based approaches, construction organizations can create a mentally tough workforce capable of handling the challenges and demands of the industry effectively.

This study contributes significantly to the general body of knowledge in mental health management among employees in the construction industry. It does set the pace for the development of the general well-being of construction professionals in the achievement of mental toughness goals.

The purpose of this global study is to investigate the critical failure factors (CFFs) in the deployment of operational excellence (OPEX) programs as well as the key performance indicators (KPIs) that can be used to measure OPEX failures. The study also empirically analyzes various OPEX methodologies adopted by various organizations at a global level.

This global study utilized an online survey to collect data. The questionnaire was sent to 800 senior managers, resulting in 249 useful responses.

The study results suggest that Six Sigma is the most widely utilized across the OPEX methodologies, followed by Lean Six Sigma and Lean. Agile manufacturing is the least utilized OPEX methodology. The top four CFFs were poor project selection and prioritization, poor leadership, a lack of proper communication and resistance to change issues.

This study extends the current body of knowledge on OPEX by first delineating the CFFs for OPEX and identifying the differing effects of these CFFs across various organizational settings. Senior managers and OPEX professionals can use the findings to take remedial actions and improve the sustainability of OPEX initiatives in their respective organizations.

This study uniquely identifies critical factors leading to OPEX initiative failures, providing practical insights for industry professionals and academia and fostering a deeper understanding of potential pitfalls. The research highlights a distinctive focus on social and environmental performance metrics, urging a paradigm shift for sustained OPEX success and differentiating itself in addressing broader sustainability concerns. By recognizing the interconnectedness of 12 CFFs, the study offers a pioneering foundation for future research and the development of a comprehensive management theory on OPEX failures.