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Processes
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Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling...
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Special Issue "Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling Processes"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 2795

Special Issue Editor

Prof. Dr. Chien-Chih Wang

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City 24301, Taiwan
Interests: machine learning and AI applications; process quality control and engineering optimization; machine vision and inspection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industrial Engineering and Management (also known as Industrial Engineering or IE)  is a highly systematic and widely applicable discipline combining science, engineering, information technology, and management for the study and optimization of organization performance. To develop practical solutions for improving operational efficiency, industrial engineers need to comprehensively and systematically understand, identify, and evaluate the complex interactions between an organization's departments, units, and subsystems. Industrial engineering has been critical for productivity enhancement, total quality management, and mass production since the second industrial revolution. With the arrival and development of the Industry 4.0 era, global manufacturing is undergoing significant changes. Industrial engineering has evolved with emerging concepts and technologies, bringing new opportunities and challenges for the industrial revolution in the Industry 4.0 era.

This Special Issue focuses on using industrial engineering techniques to solve challenges associated with optimizing and controlling enterprise processes using intelligent industrial engineering techniques. Researchers are encouraged to submit manuscripts on the broad, multidisciplinary topic of IE. Areas of interest include, but are not limited to, the following:

  • Predictive maintenance, quality control, lean six sigma, and process optimization;
  • Smart manufacturing process monitoring and control;
  • Intelligent manufacturing diagnostics, prognostics, energy management, and decision support methods;
  • Operations research, scheduling, system simulation, and supply chain management;
  • Robotics and human-machine interaction;
  • Industry 3.5, Industry 4.0, and Industry 5.0.

Prof. Dr. Chien-Chih Wang
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

  • quality control
  • process optimization
  • smart manufacturing process monitoring and control
  • intelligent manufacturing diagnostics
  • energy management
  • decision support methods
  • system simulation
  • supply chain management
  • robotics and human-machine interaction

Published Papers (3 papers)

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Article
An Amended Crow Search Algorithm for Hybrid Active Power Filter Design
by
Shoyab Ali
,
Annapurna Bhargava
,
Akash Saxena
,
Abdulaziz S. Almazyad
,
Karam M. Sallam
and
Ali Wagdy Mohamed
Processes 2023, 11(9), 2550; https://doi.org/10.3390/pr11092550 - 25 Aug 2023
Viewed by 236
Abstract
Hybrid Active Power Filter (HAPF) imbibes the advantages of both passive and active power filters. These filters are considered one of the important technologies for mitigating harmonic pollution in electrical systems. Accurate estimation of filter parameters is a key component to reduce harmonic [...] Read more.
Hybrid Active Power Filter (HAPF) imbibes the advantages of both passive and active power filters. These filters are considered one of the important technologies for mitigating harmonic pollution in electrical systems. Accurate estimation of filter parameters is a key component to reduce harmonic pollution effectively. In recent years, several optimization approaches have been reported to solve this estimation problem; still, this area is worthy of further investigation. This paper is a proposal for an estimator that can estimate the parameter of HAPF configuration accurately. For evolving this estimator, first, an objective function that mathematically embeds filter parameters and harmonic pollution is presented. For handling the optimization process, an Amended Crow Search Algorithm (ACSA) is proposed. ACSA employs a local search algorithm (in the form of a pattern search) for obtaining optimal results. The analysis of the estimation process is carried out on two HAPF configurations. Various analyses that include harmonic pollution statistical analysis along with fitness function value analysis reveal that the proposed algorithm acquires optimal results as compared with other recently published and reported algorithms. Further, the proposed filter configurations are tested with the existing filter. The results prove that the proposed filter shows promising results. Full article
(This article belongs to the Special Issue Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling Processes)
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Article
Vehicle Routing Problem Model with Practicality
by
SeJoon Park
,
Chunghun Ha
and
Hyesung Seok
Processes 2023, 11(3), 654; https://doi.org/10.3390/pr11030654 - 21 Feb 2023
Viewed by 885
Abstract
Truck platooning has recently become an essential issue in automatic driving. Though truck platooning can increase safety and reduce fuel consumption and carbon emissions, the practical vehicle routing problem involved in truck platooning has not been sufficiently addressed. Therefore, we design a mixed-integer [...] Read more.
Truck platooning has recently become an essential issue in automatic driving. Though truck platooning can increase safety and reduce fuel consumption and carbon emissions, the practical vehicle routing problem involved in truck platooning has not been sufficiently addressed. Therefore, we design a mixed-integer linear programming model for the routing problem in truck platooning considering the deadline of vehicles, continuous-time units, different fuel reduction rates, traffic congestion avoidance, and heterogeneous vehicles. In addition, a forward–backward heuristic called the “greedy heuristic” is presented for reasonable computation time. To validate the model’s performance, several parameters, such as the percentage of fuel reduction, percentage of detour vehicles, and percentage of platooned links (road segments), are considered. Additionally, various cases are considered with varying fuel reduction rates, traffic flow rates, and time windows. Full article
(This article belongs to the Special Issue Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling Processes)
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Article
A Novel CSAHP Approach to Assess the Priority of Maintenance Work Outsourced by a Metro Company
by
Sung-Neng Peng
,
Chien-Yi Huang
and
Hwa-Dong Liu
Processes 2023, 11(1), 100; https://doi.org/10.3390/pr11010100 - 29 Dec 2022
Viewed by 898
Abstract
To lower maintenance costs and improve a metro company’s competitiveness, this research came up with an innovative technique using a considering sensitivity and analytic hierarchy process (CSAHP). Along with interviews with managers and workers at the Taipei Rapid Transit Corporation, this study was [...] Read more.
To lower maintenance costs and improve a metro company’s competitiveness, this research came up with an innovative technique using a considering sensitivity and analytic hierarchy process (CSAHP). Along with interviews with managers and workers at the Taipei Rapid Transit Corporation, this study was able to undertake quantitative analysis. To determine which subsystems and metro lines should be prioritized for outsourcing based on the CSAHP framework, we used the criterium decision plus (CDP) program. This research adds to the existing body of knowledge by advancing the existing analytic hierarchy process (AHP) technique and recommending the CSAHP strategy for assessment. According to the findings, the power supply system was the most in need of outsourcing, followed by air conditioning, firefighting, and elevator systems. When considering which of the four metro lines to outsource first, the blue line came out on top, followed by the red, green, and brown lines. By prioritizing the outsourcing of the power supply system as a result of this research, the Taipei Rapid Transit Corporation may cut the system’s maintenance expenditures from USD 1.57 million to USD 1.33 million, saving 15% on maintenance costs. Applying these findings can improve the economic benefits of outsourced maintenance for the Taipei Rapid Transit Corporation. Full article
(This article belongs to the Special Issue Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling Processes)
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