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Processes
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Advanced Processes Creating New Technologies in Tomorrow’s Industry (II)
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Advanced Processes Creating New Technologies in Tomorrow’s Industry (II)

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 9325

Special Issue Editor

Dr. Florian Ion Tiberiu Petrescu

E-Mail Website
Guest Editor
1. Theory of Mechanisms and Robots Department, Faculty of Industrial Engineering and Robotics, University POLITEHNICA of Bucharest, Splaiul Independentei Street 313, 060042 Bucharest, Romania
2. Nanomaterials Research Group, Department of Natural Sciences and Technology, Division of Natural Sciences, Technology and Environment, Universidad Ana G. Méndez-Gurabo Campus, Gurabo, PR 00778, USA
Interests: machines; bioengineering; nuclear power; materials science; aerospace
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

You are invited to submit papers to our new Special Issue, entitled "Advanced Processes Creating New Technologies in Tomorrow's Industry (II)". After the conclusion of the second part, we intend to publish a book that will link together all articles collected in both parts of this special issue and which will be distributed to specialists across the globe and field. Part I may be found at: (https://www.mdpi.com/journal/processes/special_issues/advanced_processes_technologies).

This Special Issue aims to bring together recent advances in the broad field of advanced processes to create new technologies for tomorrow's industry. Its scope encompasses all research related to fault detection, diagnosis, coatings, printing, deposition, innovative processes, 3D printing, catalysts, new materials, as well as bio- and nanomaterials. Success in advancing this field will rely heavily on cooperation, and we encourage authors to submit papers on topics such as:

  • 3D printing;
  • Innovative processes;
  • Sensors;
  • Coatings;
  • Catalysts;
  • New materials;
  • Nanomaterials;
  • Chemical processes for new technologies in industry;
  • Monitoring 3D objects (e.g., from additive manufacturing);
  • Artificial intelligence for process monitoring;
  • Fault diagnosis and troubleshooting;
  • Integration of statistical process control and engineering process control;
  • Bioinspired processes;
  • Processes creating new technologies;
  • Micro- or nano-machining TiO2 patterns;
  • Photothermal membrane of CuS/polyacrylamide;
  • Fabricating sub-100nm conducting polymer nanowires;
  • Light-trapping SERS substrate with regular;
  • Fabrication of 3D biomimetic composite coating;
  • Drone drocesses;
  • Processes for robotics;
  • Any kind of new technologies;
  • Dynamic processes;
  • Industrial processes;
  • Technical processes.

Success can only come when we are together!

Dr. Florian Ion Tiberiu Petrescu
Guest Editor

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

  • 3D printing
  • innovative processes
  • sensors
  • coatings
  • catalysts
  • new materials
  • nanomaterials
  • chemically processes for new technologies in the industry
  • monitoring 3D objects
  • manufacturing
  • artificial Intelligence for process monitoring
  • fault diagnosis and troubleshooting
  • bioinspired processes
  • processes creating new technologies
  • micro- or nano-machining TiO2 Patterns
  • the photothermal membrane of CuS/polyacrylamide
  • fabricating sub-100nm conducting polymer nanowires
  • light-trapping SERS substrate with regular
  • fabrication of 3D biomimetic composite coating
  • drone processes
  • processes for robotics
  • industrial processes

Published Papers (6 papers)

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Research

13 pages, 1636 KiB  
Article
Low-Pressure Hydrothermal Processing of Disposable Face Masks into Oils
by Cagri Un, Clayton Gentilcore, Kathryn Ault, Hung Gieng, Petr Vozka and Nien-Hwa Linda Wang
Processes 2023, 11(10), 2819; https://doi.org/10.3390/pr11102819 - 23 Sep 2023
Viewed by 1766
Abstract
A total of 5.4 million tons of face masks were generated worldwide annually in 2021. Most of these used masks went to landfills or entered the environment, posing serious risks to wildlife, humans, and ecosystems. In this study, batch low-pressure hydrothermal processing (LP-HTP) [...] Read more.
A total of 5.4 million tons of face masks were generated worldwide annually in 2021. Most of these used masks went to landfills or entered the environment, posing serious risks to wildlife, humans, and ecosystems. In this study, batch low-pressure hydrothermal processing (LP-HTP) methods are developed to convert disposable face masks into oils. Three different materials from face masks were studied to find optimal processing conditions for converting full face masks into oil. The oil and gas yields, as well as oil compositions, depend on the feedstock composition, particle size, and reaction conditions. Yields of 82 wt.% oil, 17 wt.% gas, and minimal char (~1 wt.%) were obtained from full masks. LP-HTP methods for converting face masks have higher oil yields than pyrolysis methods in the literature and have lower operating pressures than supercritical water liquefaction. LP-HTP methods for face masks can increase net energy returns by 3.4 times and reduce GHG emissions by 95% compared to incineration. LP-HTP has the potential to divert 5.4 million tons of waste masks annually from landfills and the environment, producing approximately 4.4 million tons of oil. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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23 pages, 5330 KiB  
Article
A Methodology for Consolidation Effects of Inventory Management with Serially Dependent Random Demand
by Mauricio Huerta, Víctor Leiva, Fernando Rojas, Peter Wanke and Xavier Cabezas
Processes 2023, 11(7), 2008; https://doi.org/10.3390/pr11072008 - 05 Jul 2023
Cited by 2 | Viewed by 1077
Abstract
Most studies of inventory consolidation effects assume time-independent random demand. In this article, we consider time-dependence by incorporating an autoregressive moving average structure to model the demand for products. With this modeling approach, we analyze the effect of consolidation on inventory costs compared [...] Read more.
Most studies of inventory consolidation effects assume time-independent random demand. In this article, we consider time-dependence by incorporating an autoregressive moving average structure to model the demand for products. With this modeling approach, we analyze the effect of consolidation on inventory costs compared to a system without consolidation. We formulate an inventory setting based on continuous-review using allocation rules for regular transshipment and centralization, which establishes temporal structures of demand. Numerical simulations demonstrate that, under time-dependence, the demand conditional variance, based on past data, is less than the marginal variance. This finding favors dedicated locations for inventory replenishment. Additionally, temporal structures reduce the costs of maintaining safety stocks through regular transshipments when such temporal patterns exist. The obtained results are illustrated with an example using real-world data. Our investigation provides information for managing supply chains in the presence of time-patterned demands that can be of interest to decision-makers in the supply chain. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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16 pages, 1921 KiB  
Article
Mach Number Prediction for 0.6 m and 2.4 m Continuous Transonic Wind Tunnels
by Luping Zhao, Wei Jia and Yawen Shao
Processes 2023, 11(6), 1683; https://doi.org/10.3390/pr11061683 - 01 Jun 2023
Viewed by 800
Abstract
With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if [...] Read more.
With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if a new wind tunnel is designed, the experimental data may be insufficient to build a controlling model. This article reports research on the following two models: (1) for a 0.6 m continuous transonic wind tunnel supported by a large amount of historical data, the false nearest neighbor (FNN) algorithm was adopted to calculate the order of the input variables, and the nonlinear auto-regressive model with the exogenous inputs–backpropagation network (NARX-BP) was proposed to build its Mach number prediction model; (2) for a new 2.4 m continuous transonic wind tunnel with only a small amount of experimental data, the method of model migration, the input and output slope/bias correction–particle swarm optimization (IOSBC-PSO) algorithm, was developed to convert the old model of the 0.6 m wind tunnel into the new model of the 2.4 m wind tunnel, so that the new Mach number prediction could be conducted. Through simulation experiments, it was found that by introducing the NARX-BP algorithm to build the Mach number prediction model, the root-mean-square error (RMSE) of the model decreased by 44.93–77.90%, and the maximum deviation (MD) decreased by 64.05–85.32% compared to the BP model. The performance of the IOSBC-PSO migration model was also better than that of the non-migration model, as evidenced by the 82.06% decrease of the RMSE value and the 78.25% decrease of the MD value. The experiments showed the effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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20 pages, 7396 KiB  
Article
Applying a Combination of Cutting-Edge Industry 4.0 Processes towards Fabricating a Customized Component
by Antreas Kantaros, Evangelos Soulis, Theodore Ganetsos and Florian Ion Tiberiu Petrescu
Processes 2023, 11(5), 1385; https://doi.org/10.3390/pr11051385 - 04 May 2023
Cited by 8 | Viewed by 1608
Abstract
3D scanning, 3D printing, and CAD design software are considered important tools in Industry 4.0 product development processes. Each one of them has seen widespread use in a variety of scientific and commercial fields. This work aims to depict the added value of [...] Read more.
3D scanning, 3D printing, and CAD design software are considered important tools in Industry 4.0 product development processes. Each one of them has seen widespread use in a variety of scientific and commercial fields. This work aims to depict the added value of their combined use in a proposed workflow where a customized product needs to be developed. More specifically, the geometry of an existing physical item’s geometry needs to be defined in order to fabricate and seamlessly integrate an additional component. In this instance, a 3D scanning technique was used to digitize an e-bike’s frame geometry. This was essential for creating a peripheral component (in this case, a rear rack) that would be integrated into the frame of the bicycle. In lieu of just developing a tail rack from scratch, a CAD generative design process was chosen in order to produce a design that favored both light weight and optimal mechanical behaviors. FDM 3D printing was utilized to build the final design using ABS-CF10 materials, which, although being a thermoplastic ABS-based material, was introduced as a metal replacement for lighter and more ergonomic component production. Consequently, the component was manufactured in this manner and successfully mounted onto the frame of the e-bike. The proposed process is not limited to the manufacturing of this component, but may be used in the future for the fabrication of additional peripheral components and tooling. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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12 pages, 2861 KiB  
Article
Comparison of Medium-Pressure UV/Peracetic Acid to Remove Three Typical Refractory Contaminants of Textile Wastewater
by Yanping Zhu, Yuxuan Cao, Shihu Shu, Pengjin Zhu, Dongfang Wang, He Xu and Dongqing Cai
Processes 2023, 11(4), 1183; https://doi.org/10.3390/pr11041183 - 12 Apr 2023
Cited by 1 | Viewed by 1182
Abstract
In this work, the performance of medium-pressure UV/peracetic acid (MPUV/PAA/H2O2) was explored on removing reactive black 5 (RB5), aniline (ANL), and polyvinyl alcohol (PVA), three typical refractory contaminants in printing and dyeing wastewater, compared with MPUV/H2O2 [...] Read more.
In this work, the performance of medium-pressure UV/peracetic acid (MPUV/PAA/H2O2) was explored on removing reactive black 5 (RB5), aniline (ANL), and polyvinyl alcohol (PVA), three typical refractory contaminants in printing and dyeing wastewater, compared with MPUV/H2O2. MPUV/PAA/H2O2 showed 75.0, 44.9, and 57.7% removals of RB5, ANL, and PVA, respectively, within 5 min. The removal of RB5 increased from 68.98 to 91.2%, with pH increasing from 6 to 9, while the removals of ANL and PVA were much less pH-dependent. Quenching experiment results indicated that UV photolysis and radical (i.e., •OH and R-C•) oxidation contributed to RB5 removal, while PAA showed high activity in the oxidation of ANL. For PVA, •OH oxidation and UV photolysis were likely the main mechanisms. The coexisting natural organic matter had a negative effect on the degradation of RB5 and PVA. In addition, MPUV/PAA/H2O2 could effectively degrade those pollutants without increasing the toxicity. This work provides a theoretical reference for the utilization of MPUV/PAA/H2O2 in removing structurally diverse refractory contaminants from printing and dyeing wastewater. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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26 pages, 4029 KiB  
Article
Time Series-Based Edge Resource Prediction and Parallel Optimal Task Allocation in Mobile Edge Computing Environment
by Sasmita Rani Behera, Niranjan Panigrahi, Sourav Kumar Bhoi, Kshira Sagar Sahoo, N.Z. Jhanjhi and Rania M. Ghoniem
Processes 2023, 11(4), 1017; https://doi.org/10.3390/pr11041017 - 27 Mar 2023
Cited by 2 | Viewed by 1290
Abstract
The offloading of computationally intensive tasks to edge servers is indispensable in the mobile edge computing (MEC) environment. Once the tasks are offloaded, the subsequent challenges lie in buffering them and assigning them to edge virtual machine (VM) resources to meet the multicriteria [...] Read more.
The offloading of computationally intensive tasks to edge servers is indispensable in the mobile edge computing (MEC) environment. Once the tasks are offloaded, the subsequent challenges lie in buffering them and assigning them to edge virtual machine (VM) resources to meet the multicriteria requirement. Furthermore, the edge resources’ availability is dynamic in nature and needs a joint prediction and optimal allocation for the efficient usage of resources and fulfillment of the tasks’ requirements. To this end, this work has three contributions. First, a delay sensitivity-based priority scheduling (DSPS) policy is presented to schedule the tasks as per their deadline. Secondly, based on exploratory data analysis and inferred seasonal patterns in the usage of edge CPU resources from the GWA-T-12 Bitbrains VM utilization dataset, the availability of VM resources is predicted by using a Holt–Winters-based univariate algorithm (HWVMR) and a vector autoregression-based multivariate algorithm (VARVMR). Finally, for optimal and fast task assignment, a parallel differential evolution-based task allocation (pDETA) strategy is proposed. The proposed algorithms are evaluated extensively with standard performance metrics, and the results show nearly 22%, 35%, and 69% improvements in cost and 41%, 52%, and 78% improvements in energy when compared with MTSS, DE, and min–min strategies, respectively. Full article
(This article belongs to the Special Issue Advanced Processes Creating New Technologies in Tomorrow’s Industry (II))
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