Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Research Progress in Manufacturing, Grinding and Polishing of Chemical Machinery
applsci-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Research Progress in Manufacturing, Grinding and Polishing of Chemical Machinery

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 857

Special Issue Editors

Dr. Pablo Rodriguez

E-Mail Website
Guest Editor
Department of Manufacturing Engineering, University of Leon, 24071 Leon, Spain
Interests: electropolishing; micromilling; electrochemical micromachining
Special Issues, Collections and Topics in MDPI journals
Dr. Pawan Tyagi

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of the District of Columbia, Washington, DC, USA
Interests: magnetic tunnel junction-based molecular spintronic devices (MTJMSD); nanotechnology; nanosensors for biochemical and electromagnetic energy detection

Special Issue Information

Dear Colleagues,

Chemical Industry is a field of technology that undergoes constant expansion, which requires parts with increasingly sophisticated characteristics for its machinery. The manufacturing of these parts must be improved to meet the demanding requirements in terms of dimensional accuracy, mechanical resistance, corrosion resistance and, most of all, surface roughness. An important factor which requires special attention is the sustainability of the products used in the industry, as well as the reduction in waste products generated in these processes. Therefore, manufacturing processes and especially finishing processes play a crucial role in the development and enhancement of the equipment used as chemical machinery. The recent developments in advanced manufacturing processes like ultrasonic machining, electrodischarge machining and electrochemical machining, as well as in finishing process like grinding, chemical polishing and electropolishing, can contribute to this goal. These processes are especially adequate for the post-processing of parts obtained using additive manufacturing, which produces several parts with complex geometries from diverse materials, and they are quite adequate for all types of machinery, including chemical machinery.

This Special Issue gathers some of these advances and presents them as important contributions to the field of manufacturing applied to chemical machinery and available for many other applications.

Dr. Pablo Rodriguez
Dr. Pawan Tyagi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • chemical machinery
  • advanced manufacturing
  • grinding
  • polishing
  • electropolishing

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 2950 KiB  
Article
Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations
by Bogdan Felician Abaza and Vlad Gheorghita
Appl. Sci. 2025, 15(7), 3499; https://doi.org/10.3390/app15073499 - 23 Mar 2025
Viewed by 419
Abstract
In the era of Industry 4.0 and the transition toward Industry 5.0, advanced manufacturing is increasingly driven by data analytics, artificial intelligence, and cyber-physical systems. The integration of intelligent monitoring systems and self-learning algorithms is reshaping machining processes, enabling higher efficiency, precision, and [...] Read more.
In the era of Industry 4.0 and the transition toward Industry 5.0, advanced manufacturing is increasingly driven by data analytics, artificial intelligence, and cyber-physical systems. The integration of intelligent monitoring systems and self-learning algorithms is reshaping machining processes, enabling higher efficiency, precision, and sustainability. Recent advancements in smart factories emphasize the use of AI-powered process control, enabling machines to self-optimize, self-correct, and even self-retrain to maintain optimal performance. This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. By implementing forward and inverse ANN models, the framework enables real-time estimation of cutting forces and energy consumption, facilitating data-driven decision-making in machining processes. Furthermore, an adaptive recalibration mechanism ensures continuous model updates, allowing the system to dynamically adjust based on evolving machining conditions such as tool wear, material properties, and environmental variations. This research contributes to these advancements by proposing an ANN-based hybrid approach, predictive modeling, and adaptive recalibration. The proposed framework ensures continuous monitoring, automated adjustments, and intelligent decision-making, making it a scalable and adaptable solution for modern machining operations. Full article
(This article belongs to the Special Issue Research Progress in Manufacturing, Grinding and Polishing of Chemical Machinery)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop