Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.5
2.4
Journals
Mathematics
Special Issues
Fuzzy Applications in Industrial Engineering II
share announcement

Fuzzy Applications in Industrial Engineering II

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 6477

Special Issue Editors

Prof. Dr. Kuen-Suan Chen

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
Interests: statistical process control; fuzzy decision making; quality management; process capability analysis; six sigma; service management
Special Issues, Collections and Topics in MDPI journals
Dr. Chun-Min Yu

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
Interests: statistical fuzzy methodology; statistical process control; process quality analysis; six sigma methodology and applications
Special Issues, Collections and Topics in MDPI journals
Dr. Tsang-Chuan Chang

E-Mail
Guest Editor
College of Intelligence, National Taichung University of Science and Technology, Taichung 40401, Taiwan
Interests: fuzzy statistics; process capability analysis; performance evaluation; quality management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industrial engineering (IE) is concerned with the design, improvement, and installation of integrated systems of people, material, equipment, and energy. Industrial engineers are concerned with reducing production costs, increasing efficiency, and improving the quality of products and services. Fuzzy set approaches are usually most appropriate when human evaluations and the modeling of human knowledge are needed. IE uses a significant number of applications of fuzzy set theory.

The purpose of this Special Issue is to gather a collection of articles reflecting the latest developments in different fields of industrial engineering by applying fuzzy theory for control and reliability, manufacturing systems and technology management, optimization techniques, quality management, process capability analysis, statistical decision making, and others.

Prof. Dr. Kuen-Suan Chen
Dr. Chun-Min Yu
Dr. Tsang-Chuan Chang
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. Mathematics 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 2600 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

  • fuzzy applications
  • fuzzy control and reliability
  • fuzzy manufacturing systems
  • fuzzy optimization techniques
  • fuzzy service performance evaluation
  • fuzzy process capability analysis
  • fuzzy statistical decision-making

Published Papers (5 papers)

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

Research

18 pages, 3878 KiB  
Article
An Evolutionarily Based Type-2 Fuzzy-PID for Multi-Machine Power System Stabilization
by Ye Wang, Zhaiaibai Ma, Mostafa M. Salah and Ahmed Shaker
Mathematics 2023, 11(11), 2500; https://doi.org/10.3390/math11112500 - 29 May 2023
Cited by 1 | Viewed by 947
Abstract
In this paper, the impact of one of the challenges of the power transmission system, namely three-phase short-circuits, on the stability of the system is discussed. This fault causes the speed change of the synchronous generators, and the control system needs to quickly [...] Read more.
In this paper, the impact of one of the challenges of the power transmission system, namely three-phase short-circuits, on the stability of the system is discussed. This fault causes the speed change of the synchronous generators, and the control system needs to quickly zero this speed difference. This paper introduces a completely new and innovative method for power system stabilizer design. In the proposed method, there is a PID controller with a type-2 fuzzy compensator whose optimal parameter values are obtained using an improved virus colony search (VCS) algorithm at any time. In the simulation section, both transient short-circuits (timely operation of breakers and protection relays) and permanent short-circuits (failure of breakers and protection relays) are applied. For transient short-circuits, the three control systems of type-1 fuzzy-PID, type-2 fuzzy-PID, and optimized type-2 fuzzy-PID based on VCS for the nominal load and heavy load modes were compared in the simulations. Apart from the three control systems mentioned earlier, the response of a standalone PID controller was also evaluated in the context of the permanent short-circuit mode. According to the simulation results, the proposed method demonstrates superior performance and high efficiency. In contrast, the standalone PID exhibits divergence. Full article
(This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering II)
►▼ Show Figures

Figure 1

18 pages, 2379 KiB  
Article
Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique
by Xin Xu, Ahmed Shaker and Marwa S. Salem
Mathematics 2022, 10(20), 3773; https://doi.org/10.3390/math10203773 - 13 Oct 2022
Cited by 2 | Viewed by 1486
Abstract
In this paper, an automatic control method based on type-2 fuzzy sliding mode control for a mobile arm robot is presented. These types of robots have very complex dynamics due to the uncertainty of the arm parameters and the mobility of their base, [...] Read more.
In this paper, an automatic control method based on type-2 fuzzy sliding mode control for a mobile arm robot is presented. These types of robots have very complex dynamics due to the uncertainty of the arm parameters and the mobility of their base, so conventional control methods do not provide a suitable solution. The proposed method proves convergence with Lyapunov theory, and its convergence is mathematically guaranteed. A type-2 fuzzy system is responsible for approximating unmodulated dynamics, nonlinear terms, and uncertain parameters. In simulations, the performance of the proposed method with different situations, including uncertainty in arm parameters, uncertainty in mobile robot parameters (arm robot base), uncertainty in load, as well as indeterminacy in modeling have been applied. The comparison with two conventional controllers shows the efficiency and superiority of the proposed method. Full article
(This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering II)
►▼ Show Figures

Figure 1

15 pages, 1994 KiB  
Article
Sustainable Fuzzy Portfolio Selection Concerning Multi-Objective Risk Attitudes in Group Decision
by Yin-Yin Huang, Ruey-Chyn Tsaur and Nei-Chin Huang
Mathematics 2022, 10(18), 3304; https://doi.org/10.3390/math10183304 - 12 Sep 2022
Cited by 2 | Viewed by 1220
Abstract
Fuzzy portfolio selection has resulted in many researchers to focus on this field. Based on the risk attitudes, this study discusses the risk attitudes in a decision group for portfolio selection. Therefore, we adopt the risk attitudes to describe the experts’ risk preferences [...] Read more.
Fuzzy portfolio selection has resulted in many researchers to focus on this field. Based on the risk attitudes, this study discusses the risk attitudes in a decision group for portfolio selection. Therefore, we adopt the risk attitudes to describe the experts’ risk preferences and subjective judgments, and then we suppose that the risk seeker considers a higher return for an excess investment based on the selected guaranteed rate of return; the risk averter considers a shortage in investment for the securities whose return rates are smaller than the selected guaranteed rate of return; and finally, the risk neutral pursues the regular return rate. In order to solve the multi-objective return rate functions under the corresponding investment risks, the SMART-ROC weighting method is used to hybridize the multi-objective programming model to a linear programming model for solving the portfolio selection. Finally, we illustrate a numerical example and two risk scenarios to show the optimal portfolio selection under different investment risks. The results show that the proposed model can obtain a more robust portfolio than the compared models under different risk priorities in a decision group. Full article
(This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering II)
►▼ Show Figures

Figure 1

11 pages, 1262 KiB  
Article
Fuzzy Evaluation of Process Quality with Process Yield Index
by Kuen-Suan Chen, Chin-Chia Liu and Chi-Han Chen
Mathematics 2022, 10(14), 2514; https://doi.org/10.3390/math10142514 - 19 Jul 2022
Cited by 7 | Viewed by 1018
Abstract
With the rapid development and evolution of the Internet-of-Things (IoT) and big-data analysis technologies, faster and more accurate production data analysis and process capability evaluation models will bring industries closer to the goal of smart manufacturing. Small sample sizes are also common, due [...] Read more.
With the rapid development and evolution of the Internet-of-Things (IoT) and big-data analysis technologies, faster and more accurate production data analysis and process capability evaluation models will bring industries closer to the goal of smart manufacturing. Small sample sizes are also common, due to destructive testing, the high costs of detection, and insufficient technological capacity, and these undermine the reliability of the statistical method. Many studies have pointed out that a confidence-interval-based fuzzy decision model can incorporate accumulated data and expert experiences to increase testing accuracy for small samples. Therefore, this study came up with a confidence-interval-based fuzzy decision model based on a process yield index. The index not only reflects process capability but also has a one-to-one mathematical relation with the process yield so that it is convenient to apply in practice. The proposed model not only diminishes the probability of misjudgment resulting from sampling error but also improves the accuracy of testing under the situation of small sample sizes, thereby contributing to the development of smart manufacturing. Full article
(This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering II)
►▼ Show Figures

Figure 1

22 pages, 801 KiB  
Article
Developing an Enterprise Diagnostic Index System Based on Interval-Valued Hesitant Fuzzy Clustering
by Tian Chen, Shiyao Li, Chun-Ming Yang and Wenting Deng
Mathematics 2022, 10(14), 2440; https://doi.org/10.3390/math10142440 - 13 Jul 2022
Cited by 1 | Viewed by 1181
Abstract
Global economic integration drives the development of dynamic competition. In a dynamic competitive environment, the ever-changing customer demands and technology directly affect the leadership of the core competence of enterprises. Therefore, assessing the performance of enterprises in a timely manner is necessary to [...] Read more.
Global economic integration drives the development of dynamic competition. In a dynamic competitive environment, the ever-changing customer demands and technology directly affect the leadership of the core competence of enterprises. Therefore, assessing the performance of enterprises in a timely manner is necessary to adjust business activities and completely adapt to new changes. Enterprise diagnosis is a scientific tool for judging the development status of enterprises, and building a scientific and rational index system is the key to enterprise diagnosis. Considering the large number of enterprise diagnostic indicators and the high similarity among indicators, this study proposes a selection method for enterprise diagnostic indicators based on interval-valued hesitant fuzzy clustering by comparing the existing indicator systems. First, enterprise organizations are considered as the starting point. Through the key analysis of relevant indicators of domestic and foreign enterprise diagnosis, enterprise diagnosis candidate indicators are constructed from three aspects, namely enterprise performance, employee health, and social benefit. In view of the ambiguity and inconsistency of expert judgment, this study proposes an interval-valued hesitant fuzzy set based on the characteristics of hesitant fuzzy sets and interval-valued evaluation. For improving the interval-valued hesitant fuzzy entropy function, an interval-valued hesitant fuzzy similarity measurement formula considering information features is designed to avoid the problem of data length and improve the degree of identification among indicators. Then, the similarity, equivalence, and truncation matrices are constructed, and the interval-valued hesitant fuzzy clustering method is used to eliminate redundant indicators with repeated information. The availability of the proposed method is illustrated via an example, and the key indicators in the enterprise diagnostic index system are found. Finally, the advantages of the proposed method are discussed using comparative analysis with existing methods. A rational and comprehensive enterprise diagnostic index system was constructed. The system can be used as a scientific basis for diagnosing the development of enterprises and providing an objective and effective reference. Full article
(This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering II)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop