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Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

The artificial intelligence (AI) based total productive maintenance (TPM) condition based maintenance (CBM) approach through Industry 4.0 transformation can well predict the breakdown in advance to eliminate breakdown.

Meeting the customer requirement as per the delivery schedule with the existing resources are always a big challenge in industries. Any catastrophic breakdown in the equipment leads to increase in production loss, damage to machines, repair cost, time and affects delivery. If these breakdowns are predicted in advance, the breakdown can be addressed before its occurrence and the demand supply chain can be met. TPM is one of the essential operational excellence tool used in industries to utilize the existing resources of a plant in a optimal way. The conventional time based maintenance (TBM) and CBM approach of TPM in Industry 3.0 is time consuming and not accurate enough to achieve zero down time.

The proposed AI and IIoT based TPM is achieved in a digitalized data oriented platform to monitor and control the health status of the machine which may reduce the catastrophic breakdown by 95% and also improves the quality rate and machine performance rate. Based on the identified key signature parameters related to major breakdown are measured using the sensors, digitalised by programmable logic controller (PLC) and monitored by supervisory control and data acquisition (SCADA) and predicted in server or cloud.

Long short term memory based deep learning network was developed as a regression forecasting model to predict the remaining useful life RUL of the part or assembly and based on the predictions, corrective action has been implemented before the occurrence of breakdown. The reliability and consistency of the proposed approach are validated and horizontally deployed in similar machines to achieve zero downtime.

This study aims to demonstrate how governmental authorities can take interorganizational network responses to address unexpected situations developed by the breakdown of critical infrastructure, such as communication failure in a hyperconnected society.

This study uses social network analysis to investigate the performance of interorganizational response networks regarding the 2018 KT network blackout, a failure of telecommunication facility, compared to the planned network.

The national fire agency was the most prominent actor in the actual interorganizational network, while the actor was not significant in the planned network in addressing unexpected needs. Moreover, top government authorities were involved in the actual response network because of the national attention on the breakdown of the infrastructure as a focusing event.

Unexpected conditions in the actual response to a technological disaster, such as a critical infrastructure (CI) breakdown, require the involvement of emerging or non-significant actors in accordance with the findings related to other types of disasters. Particularly, communication failure in a hyperconnected society may involve prominent government authorities in the actual interorganizational response because of the event's broad and severe impact on the functions of society.

The behavior of the entities in a small and medium-sized enterprise (SME) cooperation network is influenced by the core enterprise. Addressing the problem of how the network vulnerability changes when the core enterprise is attacked is a challenging topic. The purpose of this paper is to reveal the failure process of SME cooperation networks caused by the failure of the core SME from the perspective of cascading failure.

According to the Torch High Technology Industry Development Center, Ministry of Science & Technology in China, 296 SMEs in Jiangsu province were used to construct an SME cooperation network of technology-based SMEs and an under-loading cascading failure model. The weight-based attack strategy was selected to mimic a deliberate node attack and was used to analyze the vulnerability of the SME cooperation network.

Some important conclusions are obtained from the simulation analysis: (1) The minimum boundary of node enterprises has a negative relationship with networks' invulnerability, while the breakdown probability has an inverted-U relationship with networks' invulnerability. (2) The combined effect of minimum boundary and breakdown probability indicates that the vulnerability of networks is mainly determined by the breakdown probability; while, minimum boundary helps prevent cascading failure occur. Furthermore, according to the case study, adapting capital needs and resilience in the cooperation network is the core problem in improving the robustness of SME cooperation networks.

This research proposed an under-loading cascading failure model to investigate the under-loading failure process caused by the shortage of resources when the core enterprise fails or withdraws from the SME cooperation network. Two key parameters in the proposed model—minimum capacity and breakdown probability—could serve as a guide for research on the vulnerability of SME cooperation networks. Additionally, practical meanings for each parameter in the proposed model are given, to suggest novel insights regarding network protection to facilitate the robustness and vulnerability in real SME cooperation networks.

In recent years, using aberration-corrected transmission electron microscopy, the authors have achieved precisely detecting the structural evolution of passive film as well as its interface zone at atomic scale. The purpose of this paper aims to make a brief review to show the authors’ new understanding and perspective on the issue of critical factors determining stability of passive film of Fe-Cr alloy.

The introduction of single crystal enabled the authors to obtain a distinct metal/passive film interface and better characterize the structure of the interface region. The authors use aberration-corrected TEM to conduct cross-sectional observation and directly capture the details across the entire film at a high spatial and energy resolution.

Apart from the passive film itself, the interface zone, including metal/film (Me/F) interface and the adjacent metal side, is also the site which is attacked. Accordingly, the nature of the interface zone, such as microstructure, composition and atomic configuration, is one of the critical factors determining the stability of passive film.

Deciphering the critical factors determining the stability of passive film is of great significance and has been a fundamental issue in corrosion science. Great attention has been paid to the nature of the passive film itself. In contrast, the possible role of the interface between the passive film and the metal is rarely taken into account. Based on the advanced analytical tool with high spatial resolution, the authors have specified the significant role of interface structures on the macro-scale stability of passive film.

While the petroleum industry remains to be the main source of energy in the world, it is responsible for a large amount of resource consumption, environmental emission and safety issues. In this industry, most of the refinery equipment are running out of their designed life cycle, leading to many challenges regarding equipment reliability, products quality, organizations’ profitability, human resources safety and job satisfaction, and environmental pollution, which affects not only the human resources of the refinery but also the people who live in the vicinity. This study aims to model and simulate the maintenance system of an oil refinery to reduce the rotating equipment’s downtime while simultaneously considering the three pillars of sustainability.

Considering the complexity of the system and its inherent dynamism, System Dynamics (SD) approach is applied to model and simulate the maintenance system of an oil refinery, aiming at reducing equipment’s downtime considering the three pillars of sustainability simultaneously. As a case study, the maintenance system of rotating equipment in the Abadan oil refinery of Iran is investigated.

Individual policies are investigated and categorized into three main groups: economic, social and environmental. The dynamic nature of the system demonstrates that applying combinations of the policies would be more effective than performing individual ones or even a combination of all policies at the same time. The findings show that to manage the maintenance and reliability issues in complex industries, only operational level maintenance strategies would not be helpful; rather, a holistic strategic solution counting different suppliers or even the government policies supporting the operational level maintenance decisions would be effective.

This study is the first which brings the perspective of sustainable policy-making in the SD modeling of a complex maintenance system like that of the petroleum industry. The developed model considers economic, environmental and social objectives simultaneously. Besides, it reflects the role of different stakeholders in the system. Furthermore, the policy-making attempt is not limited to the operational level corrective and maintenance solutions; instead, a comprehensive, holistic view is applied.

This study aims to examine how teacher candidates (TCs) in Türkiye and the USA navigate their intercultural communication skills in a telecollaboration project.

Forty-eight TCs participated (26 in Türkiye and 22 in the USA) in the study. TCs discussed critical issues in multicultural education on an online learning platform for six weeks. Their discussions were analyzed using content and discourse analysis.

The findings indicated that TCs approached the telecollaborative space as a translingual contact zone and positioned themselves and their interlocutors in the discourse by using the personal pronouns; I, we, you and they. When they positioned themselves using we (people in Türkiye/USA), they spoke on behalf of everyone included in the scope of we. Their interlocutors responded to these positionings either by accepting this positioning and responding with a parallel positioning or by engaging in translingual negotiation strategies to revise the scope of we and sharing some differences/nuances in beliefs and practices in their community.

When TCs talk about their culture and community in a singular manner using we, they frame them as the same across every member in that community. When they ask questions to each other using you, the framing of the questions prime the respondents to sometimes relay their own specific experiences as the norm or consider experiences from different points of view through translingual negotiation strategies. A singular approach to culture(s) may affect the marginalized communities the most because they are lost in this representation, and their experiences and voices are not integrated in the narratives or integrated with stereotypical representation.

Teachers and teacher educators should first pay attention to their language choices, especially use of pronouns, which may communicate inclusion or exclusion in intercultural conversations. Next, they should prepare their students to adopt and practice language choices that communicate respect for cultural diversity and are inclusive of marginalized populations.

Speakers’ pronoun use includes identity construction in discourse by drawing borders around and between communities and cultures with generalization and particularity, and by patrolling those borders to decide who is included and excluded. As a response, interlocutors use pronouns either to acknowledge those borders and respond with corresponding ones from their own context or negotiate alternative representations or further investigate for particularity or complexity. In short, pronouns could lead the direction of intercultural conversations toward criticality and complexity or otherwise, and might be reasons where there are breakdowns in communication or to fix those breakdowns.

This study shows that translingual negotiation strategies have explanatory power to examine how speakers from different language backgrounds negotiate second and third order positionings in the telecollaborative space.

It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.

In this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.

It is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.

The original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.

This research aims to investigate critical success factors, barriers and initiatives of total productive maintenance (TPM) implementation in selected manufacturing industries in Addis Ababa, Ethiopia.

This study built and looked into a conceptual research framework. The potential barriers and success factors to TPM implementation have been highlighted. The primary study techniques used to collect relevant data were a closed-ended questionnaire and semi-structured interview questions. With the use of SPSS version 23 and SmartPLS 3.0 software, the data were examined using descriptive statistics and the inferential Partial Least Square Structural Equation Modeling (PLS-SEM) techniques.

According to the results of descriptive statistics and multivariate analysis using PLS-SEM, the case manufacturing industries' TPM implementation initiative is in its infancy; break down maintenance is the most widely used maintenance policy; top managers are not dedicated to the implementation of TPM; and there are TPM pillars that have been weakly and strongly addressed by the case manufacturing companies.

The small sample size is a limitation to this study. It is therefore challenging to extrapolate the research findings to other industries. The only manufacturing KPI utilized in this study is overall equipment effectiveness (OEE). It is possible to add more parameters to the manufacturing performance measurement KPI. The relationships between TPM and other lean production methods may differ from those observed in this cross-sectional study. Longitudinal experimental studies and in-depth analyses of TPM implementations may shed further light on this.

Defining crucial success factors and barriers to TPM adoption, as well as identifying the weak and strong TPM pillars, will help companies in allocating their scarce resources exclusively to the most important areas. TPM is not a quick solution. It necessitates a change in both the company's and employees' attitude and their values, which takes time to bring about. Hence, it entails a long-term planning. The commitment of top managers is very important in the initiatives of TPM implementation.

This study is unique in that, it uses a new conceptual research model and the PLS-SEM technique to analyze relationships between TPM pillars and OEE in depth.

This paper aims at building a discharge model for the power cable bellows based on plasma energy deposition and analyzing the discharge ablation problem.

Aiming at the multiphysical mechanism of the discharge ablation process, a multiphysical field model based on plasma energy deposition is established to analyze the discharge characteristics of the power cable bellows. The electrostatic field, plasma characteristics, energy deposition and temperature field are analyzed. The discharge experiment is also carried out for result validation.

The physical mechanism of the bellows ablative effect caused by partial discharge is studied. The results show that the electric field intensity between the aluminum sheath and the buffer layer easily exceeds the pressure resistance value of air breakdown. On the plasma surface of the buffer layer, the electron density is about 4 × 1,019/m³, and the average temperature of electrons is about 3.5 eV. The energy deposition analysis using the Monte Carlo method shows that the electron range in the plasma is very short. The release will complete within 10 nm, and it only takes 0.1 s to increase the maximum temperature of the buffer layer to more than 1,000 K, thus causing various thermal effects.

Its physical process involves the distortion of electric field, formation of plasma, energy deposition of electrons, and abrupt change of temperature field.