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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.

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.

This study aims to investigate the influence of the interrelationship between the deployment of Industry 4.0 (I4.0) technologies and the application of lean production (LP) practices on the degree of organizational sustainability performance (SP) enhancement of the Bangladeshi ready-made garment (RMG) sector.

Previously, researchers have applied the resource-based view (RBV) or dynamic capability view (DCV) to describe the interaction of resources and capacities (technologies, management practices, SP) to analyze their effectiveness. However, in light of several contemporary academic discussions, this study contends that these organizational views are inappropriate for explicating SP. Hence, as the foundation of this study’s theoretical framework, the authors used the practice-based view (PBV), which is recommended as a useful window to evaluate the function of practices that are common and simple to emulate in execution. To test the theoretical framework and research hypothesis, this study used partial least square (PLS) analysis. For that, the authors carried out a systematic survey to collect data from 80 Bangladeshi RMG factories.

The results of this research imply that LP is a crucial factor in enhancing organizational SP. Moreover, the results also indicate that the adoption of I4.0 technologies along with LP can assist in delivering the lean objectives more efficiently and, therefore, the combined application of LP practices and I4.0 technologies play a significant role in enhancing organizational SP.

Though the present literature indicates the probable significant association between LP and SP or I4.0 technologies and SP, no study, with the best of the authors’ knowledge, has empirically examined the combined impacts of correlation between LP and I4.0 on SP. This is also a unique study to apply the PBV theory to explain the organizational SP through the combination of common resources and technologies.

The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

This study aims to focus on the preparation and characterization of the silver nanowire (AgNWs), as well as their application as antimicrobial and antivirus activities either with incorporation on the waterborne coating formulation or on their own.

Prepared AgNWs are characterized by different analytical instruments, such as ultraviolet-visible spectroscope, scanning electron microscope and X-ray diffraction spectrometer. All the paint formulation's physical and mechanical qualities were tested using American Society for Testing and Materials, a worldwide standard test procedure. The biological activities of the prepared AgNWs and the waterborne coating based on AgNWs were investigated. And, their effects on pathogenic bacteria, antioxidants, antiviral activity and cytotoxicity were also investigated.

The obtained results of the physical and mechanical characteristics of the paint formulation demonstrated the formulations' greatest performance, as well as giving good scrub resistance and film durability. In the antimicrobial activity, the paint did not have any activity against bacterial pathogen, whereas the AgNWs and AgNWs with paint have similar activity against bacterial pathogen with inhibition zone range from 10 to 14 mm. The development of antioxidant and cytotoxicity activity of the paint incorporated with AgNWs were also observed. The cytopathic effects of herpes simplex virus type 1 (HSV-1) were reduced in all three investigated modes of action when compared to the positive control group (HSV-1-infected cells), suggesting that these compounds have promising antiviral activity against a wide range of viruses, including DNA and RNA viruses.

The new waterborne coating based on nanoparticles has the potential to be promising in the manufacturing and development of paints, allowing them to function to prevent the spread of microbial infection, which is exactly what the world requires at this time.