Proposal to increase efficiency in the pizza production line in Peruvian MYPE using Lean Manufacturing tools and IoT DOI
Katherine Melissa De la Torre, Cesar Gabriel Vilela, José Antonio Velásquez Costa

et al.

Published: Dec. 20, 2024

Language: Английский

Ergonomics and design for safety: A scoping review and bibliometric analysis in the industrial engineering literature DOI
Lucia Vigoroso, Federica Caffaro, Massimo Tronci

et al.

Safety Science, Journal Year: 2025, Volume and Issue: 185, P. 106799 - 106799

Published: Feb. 3, 2025

Language: Английский

Citations

1

The Impact of Digitalization and Information and Communication Technology on the Nature and Organization of Work and the Emerging Challenges for Occupational Safety and Health DOI Open Access
Izuchukwu Chukwuma Obasi, Chizubem Benson

International Journal of Environmental Research and Public Health, Journal Year: 2025, Volume and Issue: 22(3), P. 362 - 362

Published: Feb. 28, 2025

Digitalization, driven by the widespread adoption of information and communication technology (ICT), reshapes occupational safety (OSH). This study examines emerging OSH risks linked to digitalization, assessing its benefits challenges. Through a comprehensive literature review, key technologies influencing are identified, their effects categorized, mitigation strategies proposed. While ICT enhances workplace through improved monitoring decision-making, it also introduces such as stress overload. The findings emphasize need for further research on long-term impacts effective risk management. paper contributes field highlighting ICT's positive negative implications underscoring importance responsible adoption. insights presented valuable policymakers, researchers, industry practitioners committed fostering safe healthy work environment.

Language: Английский

Citations

0

The Future of Manufacturing and Industry 4.0 DOI Creative Commons
Szilárd Jaskó, Tamás Ruppert

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4655 - 4655

Published: April 23, 2025

Industry and its associated elements are an important part of modern society [...]

Language: Английский

Citations

0

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

Pimolkan Piankitrungreang,

Kantawatchr Chaiprabha,

Worathris Chungsangsatiporn

et al.

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

Citations

0

A Comparative Analysis of Anomaly Detection Methods in IoT Networks: An Experimental Study DOI Creative Commons

Emanuel Krzysztoń,

Izabela Rojek, Dariusz Mikołajewski

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11545 - 11545

Published: Dec. 11, 2024

The growth of the Internet Things (IoT) and its integration with Industry 4.0 5.0 are generating new security challenges. One key elements IoT systems is effective anomaly detection, which identifies abnormal behavior in devices or entire systems. This paper presents a comprehensive overview existing methods for detection networks using machine learning (ML). A detailed analysis various ML algorithms, both supervised (e.g., Random Forest, Gradient Boosting, SVM) unsupervised Isolation Autoencoder), was conducted. results tests conducted on popular datasets (IoT-23 CICIoT-2023) were collected analyzed detail. performance selected algorithms evaluated commonly used metrics (Accuracy, Precision, Recall, F1-score). experimental showed that Forest Autoencoder highly detecting anomalies. article highlights importance appropriate data preprocessing to improve accuracy. Furthermore, limitations centralized approach context distributed discussed. also potential directions future research field IoT.

Language: Английский

Citations

2

Digital technology in occupational health of manufacturing industries: a systematic literature review DOI Creative Commons

Luping Jiang,

Jingdong Zhang, Yiik Diew Wong

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 6(12)

Published: Nov. 22, 2024

In this study, we fill the gap of limited effort on systematic literature review into field digital technology for occupational health manufacturing industries. Upon reviewing 53 publications selected by combined bibliometric and classical methods, present an integrated overview major research areas hot topics critically identify prevalent technologies application modes, enablers barriers to implementation, as well agenda in health. The results show that, with increasing popularity penetration items like wearable devices sensors, human–robot collaboration, deep learning analytics, identified implementation are: intelligent manufacturing, competitive condition, data-driven decision-making tool, considerations welfare health; technological gap, privacy data security, culture acceptance, cost consideration. Additionally, propositions three aspects six perspectives are recommended future field. Overall, study provides insights through analysis synthesis, offers means achieve Sustainable Development Goals (SDGs) exploring efficient protect labor rights improve

Language: Английский

Citations

1

Encouraging Safety 4.0 to enhance industrial culture: An extensive study of its technologies, roles, and challenges DOI Creative Commons

Abid Haleem,

Mohd Javaid, Ravi Pratap Singh

et al.

Green Technologies and Sustainability, Journal Year: 2024, Volume and Issue: unknown, P. 100158 - 100158

Published: Dec. 1, 2024

Language: Английский

Citations

1

Safe-and-Sustainable-by-Design Framework: (Re-)Designing the Advanced Materials Lifecycle DOI Open Access

Adamantia Kostapanou,

Konstantina‐Roxani Chatzipanagiotou, Spyridon Damilos

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10439 - 10439

Published: Nov. 28, 2024

In the last few years, materials research community has shown increased interest in Advanced Materials (AdMas) that are specifically designed to substitute traditionally used materials, not only with a view their sustainability, sourcing criticality, or scarcity, but also maintaining even enhancing functionality and performance. The use of AdMas is particularly researched sectors where environmental impact traditional substantial, terms waste production resource consumption. Due novelty potentially unpredictable impacts, add further value application, there an increasing safety sustainability AdMas. this context, new 5-step Safe-and-Sustainable-by-Design (SSbD) framework was developed by European Union, support (re-)design development novel materials. A guideline presented for enforcing phase paradigms guide stakeholders practically materials’ industry. present manuscript analyzes advances challenges SSbD framework, showcasing its applicability limitations added compared assessment methodologies, provide comprehensive evaluation methodology industry concerning sustainability.

Language: Английский

Citations

0

Proposal to increase efficiency in the pizza production line in Peruvian MYPE using Lean Manufacturing tools and IoT DOI
Katherine Melissa De la Torre, Cesar Gabriel Vilela, José Antonio Velásquez Costa

et al.

Published: Dec. 20, 2024

Language: Английский

Citations

0