Total Productivity Optimization (TPO): A Case Study in Plastic Manufacturing Industry DOI

Joyeshree Biswas,

Suman G. Das

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

Synthesis, characterization, and practical applications of perovskite quantum dots: recent update DOI
Subhash Chandra, Mohammed Ahmed Mustafa,

Kamil Ghadir

et al.

Naunyn-Schmiedeberg s Archives of Pharmacology, Journal Year: 2024, Volume and Issue: 397(12), P. 9633 - 9674

Published: July 29, 2024

Language: Английский

Citations

5
Unveiling spatial insights: navigating the parameters of dynamic Geographic Information Systems (GIS) analysis DOI Creative Commons

Mohammad Aman Ullah Sunny

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 11(2), P. 1976 - 1985

Published: April 30, 2024

In today's rapidly evolving landscape of Geographic Information Systems (GIS), understanding the intricate parameters that govern GIS analysis is paramount. This title encapsulates essence delving into multifaceted dimensions GIS, where a myriad factors converges to shape process and outcomes spatial analysis. From selection input data layers fine-tuning analytical techniques model parameters, every step in governed by set influence accuracy, reliability, relevance results. The beckons researchers, practitioners, enthusiasts alike embark on journey exploration, unraveling complexities its underlying parameters. It speaks dynamic nature interplay data, computational algorithms, user-defined creates rich tapestry insights discoveries. Whether mapping urban growth patterns, assessing natural resource availability, or modeling environmental change, essential for unlocking full potential informing decision-making processes. Moreover, hints at transformative power as tool addressing complex phenomena. By scrutinizing analysis, researchers can gain deeper processes driving patterns trends. They identify optimal parameter settings, refine workflows, enhance accuracy precision models predictions. essence, "Exploring Parameters: Understanding Dynamics Analysis" field, exploration serves gateway harnessing geography address real-world challenges opportunities.

Language: Английский

Citations

4
Deep learning identifies transversely isotropic material properties using kinematics fields DOI
Nikzad Motamedi, Hazem Wannous, Vincent Magnier

et al.

International Journal of Mechanical Sciences, Journal Year: 2024, Volume and Issue: 283, P. 109672 - 109672

Published: Sept. 4, 2024

Language: Английский

Citations

4
Investigating the effectiveness of a mobile wind turbine generating electricity from vehicle air movement DOI Creative Commons

Joyeshree Biswas,

Suman Das

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 22(1), P. 210 - 218

Published: April 9, 2024

This study presents an evaluation of the effectiveness a portable wind generator designed to harness flow generated by moving vehicles for electricity production. With growing emphasis on renewable energy sources and need sustainable power solutions, innovative approaches such as utilizing vehicle-induced currents have gained attention. The under examination is engineered capture airflow from passing convert it into electrical energy. Through combination field experiments theoretical analysis, performance efficiency device were assessed various environmental traffic conditions. Factors speed, direction, vehicle velocity considered in process. results indicate promising potential supplementary source, particularly environments with high vehicular traffic. However, challenges variability patterns optimal positioning remain areas further investigation refinement. Overall, this contributes understanding unconventional resources provides insights practical implementation mobile technology generation.

Language: Английский

Citations

3
Integrating Deep Learning Into Mechanical Engineering: A Systematic Review of Applications and Educational Implications DOI

Geethika S. Kollu,

Javeed Kittur

Computer Applications in Engineering Education, Journal Year: 2025, Volume and Issue: 33(3)

Published: May 1, 2025

ABSTRACT Deep learning (DL) is reshaping mechanical engineering by offering advanced capabilities for solving complex problems, particularly in fault diagnosis, predictive maintenance, and materials science. While conventional machine physics‐based approaches remain prevalent, DL models provide superior performance terms of accuracy, automation, adaptability. This systematic review investigates trends applications within from 2015 to 2024. An initial search using the query “deep AND engineering” across seven major databases—Google Scholar, Web Science, IEEE Xplore, ERIC, Science Direct, Compendex, Wiley Online Library—yielded 149 articles. After applying exclusion criteria (published before 2014, non‐English, short or work‐in‐progress papers, not and/or focus, conceptual papers), 49 studies were selected in‐depth analysis. The results indicate that improve prediction accuracy 10%–35% over traditional techniques various applications, including detection rotating machinery microstructural analysis engineering. Despite notable gains, challenges persist related data availability, computational intensity, model interpretability. highlights importance addressing these limitations recommends future research efforts toward improving generalization, incorporating explainable AI techniques, optimizing deployment under limited‐data scenarios. Furthermore, integration with Industry 4.0 technologies—such as IoT, digital twins, cyber‐physical systems—presents a promising direction real‐time, intelligent decision‐making systems. serves comprehensive resource researchers practitioners seeking apply advance methods contexts.

Language: Английский

Citations

0
Exploring the structural, optical, dielectric and magnetic properties of rare earth samarium doped Ca-Mg based Ca0.5Mg0.5Fe12−xSmxO19 ferrite nanoparticles DOI
Basmah H. Alshammari, Kaseb D. Alanazi, Sana Ullah Asif

et al.

Inorganic Chemistry Communications, Journal Year: 2024, Volume and Issue: unknown, P. 113159 - 113159

Published: Sept. 1, 2024

Language: Английский

Citations

3
Optimizing Decision Accuracy in Supplier Selection: A Mathematical Framework Employing Triangular Fuzzy Logic DOI
Iqtiar Siddique,

Joyeshree Biswas

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

Citations

2
Productivity optimization techniques using industrial engineering tools: A review DOI Creative Commons

Tomal Das

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 12(1), P. 375 - 385

Published: May 12, 2024

This review explores productivity optimization techniques through the lens of industrial engineering tools. Industrial serves as a critical discipline in enhancing efficiency and effectiveness across various industries. The abstract delves into methodologies, such time motion studies, Six Sigma, Lean principles, operations research, which are instrumental streamlining processes improving productivity. These tools aid identifying inefficiencies, eliminating waste, overall performance. Through comprehensive analysis existing literature case this highlights diverse applications benefits optimizing Additionally, it discusses integration advanced technologies, automation, data analytics, artificial intelligence, modern enhancement strategies. concludes with insights future directions potential challenges leveraging for sustained improvements dynamic organizational environments.

Language: Английский

Citations

1
Total Productivity Optimization (TPO): A Case Study in Plastic Manufacturing Industry DOI

Joyeshree Biswas,

Suman G. Das

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

Citations

0