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Processes
Special Issues
Industrial Process Operation State Sensing and Performance Optimization
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Industrial Process Operation State Sensing and Performance Optimization

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Automation Control Systems".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 1387

Special Issue Editors

Prof. Dr. Sheng Du

E-Mail Website
Guest Editor
School of Automation, China University of Geosciences, Wuhan 430074, China
Interests: process control; intelligent control; intelligent optimization; computational intelligence; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Li Jin

E-Mail Website
Guest Editor
School of Automation, China University of Geosciences, Wuhan 430074, China
Interests: power system stability analysis and control; time-delay system; robust theory and application
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Xiongbo Wan

E-Mail Website
Guest Editor
1. School of Automation, China University of Geosciences, Wuhan 430074, China
2. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China
3. Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China
Interests: artificial intelligence; robust control of time-delay systems
Special Issues, Collections and Topics in MDPI journals
Dr. Zixin Huang

E-Mail Website
Guest Editor Assistant
School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
Interests: underdrive system control; intelligent control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of large-scale industries, the operational safety, energy consumption, and efficient management of industrial processes have received widespread attention. This Special Issue aims to explore industrial process operation state sensing and performance optimization. The integration of advanced technologies, such as machine learning, artificial intelligence, and data analytics, will provide important support for soft sensing, process monitoring, fault diagnosis, energy consumption optimization, and performance improvement.

Scope and Objectives:

The primary objective of this Special Issue is to promote research and advancement in the field of operation state sensing and performance optimization for industrial processes, especially in the fields of steel metallurgy, chemical engineering, geological drilling, marine exploration, textiles, pharmaceuticals, and other large-scale industries.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Soft sensing techniques.
  • Hybrid intelligent modeling techniques.
  • Data-driven modeling techniques.
  • Operation state sensing.
  • Process monitoring.
  • Fault diagnosis.
  • Energy consumption optimization.
  • Performance improvement.
  • Performance assessment.

Prof. Dr. Sheng Du
Prof. Dr. Li Jin
Prof. Dr. Xiongbo Wan
Guest Editors

Dr. Zixin Huang
Guest Editor Assistant

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. Processes is an international peer-reviewed open access monthly 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

  • data-driven modeling
  • industrial processes
  • machine learning
  • operation state sensing
  • performance improvement

Published Papers (2 papers)

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Research

15 pages, 2955 KiB  
Article
Comparison between Conventional Ageing Process in Barrels and a New Rapid Aging Process Based on RSLDE: Analysis of Bioactive Compounds in Spirit Drinks
by Daniele Naviglio, Paolo Trucillo, Angela Perrone, Domenico Montesano and Monica Gallo
Processes 2024, 12(4), 829; https://doi.org/10.3390/pr12040829 - 19 Apr 2024
Viewed by 276
Abstract
“Aging” is a practice that allows alcoholic beverages to mature and gives them particular flavors and colors. In this context, oak or durmast wooden barrels are used in this process, thus providing different types of aging. This conventional process produces a slow enrichment [...] Read more.
“Aging” is a practice that allows alcoholic beverages to mature and gives them particular flavors and colors. In this context, oak or durmast wooden barrels are used in this process, thus providing different types of aging. This conventional process produces a slow enrichment of organic compounds in the spirit inside the barrels. Organic substances present in the internal part of the barrels slowly undergo the phenomenon of extraction by the liquid phase (solid–liquid extraction). In this work, a new procedure based on rapid solid–liquid dynamic extraction (RSLDE) was used to evaluate the potential of obtaining the effects of aging in spirits in shorter times than conventional methods. For this purpose, a comparison between two solid–liquid extraction techniques, RSLDE and conventional maceration, was made. Four water/ethanol 60:40 (v/v) model solutions were prepared and put in contact with medium-toasted chips using the two extraction procedures (conventional and non-conventional) and determining dry residue and total polyphenol content. Reversed phase high-performance liquid chromatography (RP-HPLC) analyses allowed the identification and quantification of furfural, ellagic acid and phenolic aldehydes (vanillin, syringaldehyde, coniferaldehyde and sinapaldehyde). The aging procedure with medium-toasted chips was tested on a young commercial grappa using maceration and RLSDE. Full article
(This article belongs to the Special Issue Industrial Process Operation State Sensing and Performance Optimization)
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19 pages, 5991 KiB  
Article
Optimization of Anti-Skid and Noise Reduction Performance of Cement Concrete Pavement with Different Grooved and Dragged Textures
by Biyu Yang, Songli Yang, Zhoujing Ye, Xiaohua Zhou and Linbing Wang
Processes 2024, 12(4), 800; https://doi.org/10.3390/pr12040800 - 16 Apr 2024
Viewed by 393
Abstract
Cement concrete pavements are crucial to urban infrastructure, significantly influencing road safety and environmental sustainability with their anti-skid and noise reduction properties. However, while texturing techniques like transverse grooving have been widely adopted to enhance skid resistance, they may inadvertently increase road noise. [...] Read more.
Cement concrete pavements are crucial to urban infrastructure, significantly influencing road safety and environmental sustainability with their anti-skid and noise reduction properties. However, while texturing techniques like transverse grooving have been widely adopted to enhance skid resistance, they may inadvertently increase road noise. This study addressed the critical need to optimize pavement textures to balance improved skid resistance with noise reduction. Tests were conducted to assess the influence of surface texture on skid resistance and noise, exploring the relationship between texture attributes and their performance in these areas. The investigation examined the effects of texture representation methods, mean profile depth, and the high-speed sideway force coefficient (SFC) on noise intensity and pavement skid resistance. The findings revealed that transverse grooves significantly improved the SFC, enhancing skid resistance. In contrast, longitudinal burlap drag, through its micro- and macro-texture adjustments, effectively reduced vibration frequencies between the tire and pavement, thus mitigating noise. Utilizing the TOPSIS multi-objective optimization framework, an optimization model for pavement textures was developed to augment skid resistance and noise reduction at varying speeds. The results indicated that at 60 km/h, an optimal balance of groove width, depth, and spacing yielded superior skid resistance with a minimal noise increase. At 80 km/h, increased groove spacing and depth were shown to effectively decrease noise while maintaining efficient water evacuation. The optimal pavement texture design must consider the specific context, including traffic volume, vehicle types, and operating speeds. This study provides essential guidance for optimizing urban cement concrete pavement textures, aiming to diminish traffic noise and bolster road safety. Full article
(This article belongs to the Special Issue Industrial Process Operation State Sensing and Performance Optimization)
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