Virtual manufacturing in Industry 4.0: A review

Data Science and Management, Journal Year: 2023, Volume and Issue: 7(1), P. 47 - 63

Published: Nov. 1, 2023

Virtual manufacturing is one of the key components Industry 4.0, fourth industrial revolution, in improving processes. enables manufacturers to optimize their production processes using real-time data from sensors and other connected devices 4.0. Web-based virtual platforms are a critical component enabling design, test, collaboratively efficiently. In radio frequency identification (RFID) technology used provide visibility control supply chain as well enable automation various Big analytics can be conjunction with valuable insights Artificial intelligence (AI) have potential enhance effectiveness, consistency, adaptability processes, resulting faster cycles, better-quality products, lower prices. Recent developments application systems digital different perspectives, such Internet Things, big analytics, additive manufacturing, autonomous robots, cybersecurity, RFID discussed this study analyze develop part process The limitations advantages 4.0 discussed, future research projects also proposed. Thus, productivity enhanced by reviewing analyzing applications

Language: Английский

---

Artificial neural networks in supply chain management, a review

Journal of Economy and Technology, Journal Year: 2023, Volume and Issue: 1, P. 179 - 196

Published: Nov. 1, 2023

Artificial Neural Networks (ANNs) are a type of machine learning algorithm inspired by the structure and function human brain. In context supply chain management, ANNs can be used for demand forecasting, inventory optimization, logistics planning, anomaly detection. help companies to optimize their levels, production schedules procurement activities in terms productivity enhancement part production. By considering multiple variables constraints, identify most efficient routes, allocate resources effectively, reduce costs. Furthermore, anomalies as well abnormalities data, such unexpected patterns, quality issues disruptions operations order minimize impact on chain. also analyze supplier performance including quality, delivery times pricing assess reliability effectiveness suppliers. This information support decision-making processes evaluation selection processes. Moreover, continuously monitor performance, raising alerts deviations from predefined criteria provide safe secure analyzing various data sources, weather conditions, political instability, mitigate risks safety neural networks management is studied research work enhance performances process manufacturing. New ideas concepts future works presented reviewing recent achievements applications artificial management. Thus, manufacturing enhanced promoting using networks.

Language: Английский

---

How does artificial intelligence promote renewable energy development? The role of climate finance

Energy Economics, Journal Year: 2024, Volume and Issue: 133, P. 107493 - 107493

Published: March 22, 2024

Scholars, stakeholders, and the government have given significant attention to development of renewable energy in recent times. However, previous research has failed acknowledge potential impact artificial intelligence on advancing development. Drawing insights from a global dataset encompassing 63 countries over period 2000–2019, this paper provides observations regarding influence progress energy, by using Instrumental Variable Generalized Method Moments model. We also explore their asymmetric nexus, mediation effect. Moreover, study explores moderating role climate finance highlights following interesting findings. First, contributes significantly enhanced primary finding holds after two robustness tests changing independent dependent variables. Second, an effect development, nexus is closer with lower levels Thid, works through technology innovation Fourth, presents direct benefits development; simultaneously, plays effective relationship between These findings inspire us propose policy implications promote energy.

Language: Английский

---

Artificial intelligence and carbon emissions inequality: Evidence from industrial robot application

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 438, P. 140817 - 140817

Published: Jan. 1, 2024

Language: Английский

---

AI-Based Decision Support Systems in Industry 4.0, A Review

Journal of Economy and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Language: Английский

---

Identifying barriers and drivers for energy efficiency in steel and iron industries of Karachi, Pakistan: Insights from executives and professionals

Energy Nexus, Journal Year: 2024, Volume and Issue: 14, P. 100284 - 100284

Published: March 16, 2024

Pakistan has faced a persistent energy deficit over the past few decades, with energy-intensive industries occupying substantial share of consumption. Despite potential for efficiency improvements within industrial sector, numerous barriers hinder progress. This study identifies and drivers practices specifically steel iron economic hub Pakistan. Through questionnaire-based approach follow-up interviews, responses were gathered from 32 executives professionals representing eight firms. Reliability analysis was conducted to ensure robustness data. The reveals that limited awareness inadequate managerial commitment are significant initiatives. Moreover, ineffective policies lack government implementation plans contribute diminishing demand energy-efficient technologies. However, there is growing interest among respondents in reducing consumption enhance cost-effectiveness. Key such as long-term benefits, improved working conditions, cost savings emerge crucial factors motivating adoption practices. Positively, some companies have already initiated energy-saving measures, including advanced technologies renewable sources. These findings highlight urgent need collaborative efforts overcome promote sustainability sector

Language: Английский

---

Intelligent robotic systems in Industry 4.0: A review

Journal of Advanced Manufacturing Science and Technology, Journal Year: 2024, Volume and Issue: 4(3), P. 2024007 - 2024007

Published: Jan. 1, 2024

As Industry 4.0 continues to transform the landscape of modern manufacturing, integration intelligent robotic systems has emerged as a pivotal factor in enhancing efficiency, flexibility, and overall productivity. The Integration within framework represents transformative shift advanced manufacturing systems. significantly reduced production costs while simultaneously improving product quality. decision-making capabilities have played role minimizing downtime order enhance productivity process part manufacturing. Intelligent not only increased efficiency but also contributed more sustainable eco-friendly environment through optimized resource utilization. This review explores key aspects, benefits, challenges associated with deployment 4.0. analyze cutting-edge advancements artificial intelligence, machine learning, sensor technologies that contribute evolution discussion extends emerging trends including digital twin, blockchain, Internet Things, analytics for real-time decision support Challenges considerations surrounding implementation are thoroughly examined, ranging from technical hurdles ethical societal implications. Finally, concludes forward-looking perspective on future trajectory result, study can provide roadmap researchers industry professionals navigate evolving robotics era

Language: Английский

---

Blockchains for industrial Internet of Things in sustainable supply chain management of industry 4.0, a review

Sustainable Manufacturing and Service Economics, Journal Year: 2024, Volume and Issue: 3, P. 100026 - 100026

Published: Jan. 1, 2024

Language: Английский

---

Modeling challenges for Industry 4.0 implementation in new energy systems towards carbon neutrality: Implications for impact assessment policy and practice in emerging economies

Resources Conservation and Recycling, Journal Year: 2023, Volume and Issue: 199, P. 107246 - 107246

Published: Oct. 13, 2023

Language: Английский

---

Robotical Automation in CNC Machine Tools: A Review

Acta Mechanica et Automatica, Journal Year: 2024, Volume and Issue: 18(3), P. 434 - 450

Published: July 25, 2024

Abstract Robotics and automation have significantly transformed Computer Numerical Control (CNC) machining operations, enhancing productivity, precision, efficiency. Robots are employed to load unload raw materials, workpieces, finished parts onto CNC machines. They can efficiently handle heavy bulky components, reducing the demand of manual labour minimizing risk injuries. also be used in machine tools perform tasks such as automatic tool changing system, part inspection, workpiece positioning. Automation technologies, including in-line inspection systems Non-Destructive Testing (NDT) methods, integrated into cells enhance accuracy reduce scrap rework operations. These collect real-time data on process parameters performance predict maintenance, optimize parameters, improve overall In current study, applications robotics modification reviewed discussed. Different tools, automated material handling, changing, robotic work cells, adaptive machining, tending, quality monitoring analysis, production line integration, Thus, by analysing recent achievements published papers, new ideas concepts future research works suggested. As a result, well productivity enhanced applying

Language: Английский

---