A path to follow to overcome foundational barriers to the adoption of artificial intelligence within the manufacturing industry: a conceptual framework

Enterprise Information Systems, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Language: Английский

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Research on the Path to Improving the Teaching Effectiveness of News Communication in Colleges and Universities under the Background of Artificial Intelligence

Applied Mathematics and Nonlinear Sciences, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 1, 2025

Abstract With the rapid development of artificial intelligence technology, field education, especially journalism communication teaching in colleges and universities, is facing unprecedented opportunities for change. Artificial not only promotes innovation methods, but also provides a new path improving effects. This paper takes major universities as research object, discusses how to effectively improve effect under background intelligence. Through investigation data analysis disciplines 30 across country, introduction technology has shown significant advantages students’ learning efficiency, enhancing curriculum interactivity, teachers’ quality. The intelligence-assisted personalized system can customize course content according progress interests, while evaluation real-time feedback on performance through analysis, helping teachers adjust strategies more accurately. In using average grades have increased by 15%, classroom participation 20%, satisfaction 25%.

Language: Английский

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Analysing Lean 4.0 Adoption Factors Towards Manufacturing Sustainability in SMEs: A Hybrid ANN-Fuzzy ISM Framework

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

Manufacturing industries across the globe are undergoing a digital transformation that demands both efficiency and sustainability. Industry 4.0 (I4.0) Lean (L4.0) methodologies have become focal points in these efforts. Despite widespread recognition of benefits integrating L4.0 I4.0, more studies need to address practical challenges this integration, especially key factors influence its successful implementation. Small medium-sized enterprises (SMEs) emerging economies often face significant practices due resource limitations complex operational challenges. This study bridges critical research gap by proposing an integrated framework combines Artificial Neural Networks (ANN) with fuzzy Interpretive Structural Modeling (FISM) identify prioritise success (CSFs) for adoption. A survey 216 manufacturing SMEs was used validate CSFs through Exploratory Factor Analysis (EFA). The ANN analysis revealed Process Factors highest normalised importance (NI) 100%, followed Organizational (NI = 60.46%), Human 58.93%), Technological 43.21%), External 42.13%), Environmental 39.63%). Complementary FISM Cross-Impact Matrix Multiplication Applied Classification (MICMAC) analyses further structured relationships, underscoring roles Change Management, Culture, Waste Reduction, Regulatory Compliance. These findings offer theoretical advancement understanding CSF interactions guidance striving achieve sustainable practices.

Language: Английский

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Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling

Machines, Journal Year: 2025, Volume and Issue: 13(5), P. 372 - 372

Published: April 29, 2025

This paper introduces an acoustic-based monitoring system for high-speed CNC drilling, aimed at optimizing processes and enabling real-time machine state detection. High-fidelity acoustic sensors capture sound signals during drilling operations, allowing the identification of critical events such as tool engagement, material breakthrough, withdrawal. Advanced signal processing techniques, including spectrogram analysis Fast Fourier Transform, extract dominant frequencies patterns, while learning algorithms like DBSCAN clustering classify operational states cutting, returning. Experimental studies on materials acrylic, PTFE, hardwood reveal distinct profiles influenced by properties conditions. Smoother patterns lower characterize PTFE whereas produces higher rougher due to its density resistance. These findings demonstrate correlation between emissions machining dynamics, non-invasive predictive maintenance. As AI power increases, it is expected in-situ process information achieve resolution, enhancing precision in data interpretation decision-making. A key contribution this project creation open library processes, fostering collaboration innovation intelligent manufacturing. By integrating big concepts algorithms, supports continuous monitoring, anomaly detection, optimization. AI-ready hardware enhances accuracy efficiency improving quality, reducing wear, minimizing downtime. The research establishes a transformative approach advancing manufacturing systems.

Language: Английский

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Structural modification of supply chains in the imperatives of circular economy

Journal of Innovation and Entrepreneurship, Journal Year: 2025, Volume and Issue: 14(1)

Published: May 14, 2025

Language: Английский

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Construction Strategy of Intelligent Accounting Information Systems for Supply Chain Enterprises in the Digital Economy Era

Management Science and Engineering, Journal Year: 2024, Volume and Issue: 14(01), P. 9 - 18

Published: Dec. 31, 2024

Language: Английский

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