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Sustainable Development of Industrial Engineering With the Application of Intelligent Systems

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 32254

Special Issue Editors

Dr. Babek Erdebilli (B.D Rouyendegh)

E-Mail Website
Guest Editor
Department of Industrial Engineering, AYBU University, Ankara, Turkey
Interests: multi-criteria decision making; supply chain management and logistics management; fuzzy sets; machine learning; linear and nonlinear programming; mathematical modeling; data envelopment analysis; operations research and its applications in energy, GSCM, big data, health care, ergonomics, Industry 4.0, and environmental science
Dr. Erfan Babaee Tirkolaee

E-Mail Website
Guest Editor
Department of Industrial Engineering, Istinye University, Istanbul 34396, Turkey
Interests: supply chain management; waste management; sustainable development; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on intelligent systems (ISs) in the context of sustainable development for industrial engineering. ISs are utilized in healthcare, agriculture, transportation, energy, safety, and education. These mobile systems impact our daily lives. Edge computing brings processing and storage closer to the customer, hence reducing reaction times. Such disruptive innovations improve the quality of human life, but they must be sustainable in terms of natural resource usage and should not be detrimental to present or future generations.

Due to their objective-oriented and adaptive qualities, ISs are applicable in virtually every sector. With the exponential increase in population and the continual decrease in resources (such as the land area for agriculture, labour, and water), AI strategies and novel computing can maximize additional resources and can deliver these applications to the fingertips of users.

This Special Issue aims to cover research and innovation in healthcare decision support systems, weather forecasting, waste management, sustainable agriculture, traffic and pollution control applications, and safety and security applications. It will examine research and expertise in intelligent systems, machine and deep learning computing, and sustainable development.

Topics include, but are not limited to the following:

  • Sustainable development of industrial engineering using approximate optimization methods;
  • Sustainable development of industrial engineering using novel meta-heuristic algorithms;
  • Sustainable development of industrial engineering using simulation-based optimization
  • Sustainable development of industrial engineering using machine learning methods;
  • Sustainable development of industrial engineering using MCDM methods;
  • Sustainable development of industrial engineering using fuzzy methods.

Dr. Babek Erdebilli (B.D Rouyendegh)
Dr. Erfan Babaee Tirkolaee
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. Sustainability 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

  • sustainable development
  • optimization methods
  • intelligent systems
  • machine learning

Published Papers (16 papers)

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Editorial

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3 pages, 137 KiB  
Editorial
Sustainable Development of Industrial Engineering with the Application of Intelligent Systems
by Babek Erdebilli and Erfan Babaee Tirkolaee
Sustainability 2024, 16(5), 1928; https://doi.org/10.3390/su16051928 - 27 Feb 2024
Viewed by 623
Abstract
This Special Issue focuses on Intelligent Systems (ISs) in the context of sustainable development for industrial engineering [...] Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)

Research

Jump to: Editorial

24 pages, 620 KiB  
Article
Supplier Selection for a Power Generator Sustainable Supplier Park: Interval-Valued Neutrosophic SWARA and EDAS Application
by Emre Cakmak
Sustainability 2023, 15(18), 13973; https://doi.org/10.3390/su151813973 - 20 Sep 2023
Cited by 2 | Viewed by 1053
Abstract
Power generator manufacturers play a critical role in maintaining electric flow for sustainable product and service production. The aim of this study is to extract the criteria necessary for a generator manufacturer to evaluate and select its suppliers for its sustainable supplier park, [...] Read more.
Power generator manufacturers play a critical role in maintaining electric flow for sustainable product and service production. The aim of this study is to extract the criteria necessary for a generator manufacturer to evaluate and select its suppliers for its sustainable supplier park, and to prioritize them to form the supply network. The methodology of this research covers the phases as (i) extracting the criteria affecting the supplier selection decision process of a power generator company via an in-depth literature and industrial report review, (ii) evaluating these criteria by industry experts, (iii) identifying the weights of each criterion via SWARA (“step-wise weight assessment ratio analysis”), (iv) prioritizing the alternative suppliers fitting to the criteria so that the power generator company can construct its sustainable supplier park via IVN EDAS (“interval valued neutrosophic Evaluation Based on Distance from Average Solution”), (v) conducting a sensitivity analysis to check for the robustness of the results by changing the weights, and (vi) applying a comparative analysis to validate the methodology’s accuracy by comparing the results with IVN TOPSIS and IVN CODAS. Moreover, this paper contributes to the literature by elaborating on the integration details of the IVN SWARA and IVN EDAS as the first research paper of the author’ knowledge. A practitioner can understand which factors to consider prominently in forming a sustainable supplier park, or in deciding on which suppliers to select to plan the strategic operations of a power generator company. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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18 pages, 3541 KiB  
Article
A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey
by Ibrahim Yilmaz
Sustainability 2023, 15(14), 11267; https://doi.org/10.3390/su151411267 - 19 Jul 2023
Cited by 6 | Viewed by 1020
Abstract
The production of renewable energy is becoming one of the most important issues for communities due to the increasing energy demand. The purpose of this paper is to develop a systematized, sustainability-focused evaluation framework for determining the efficiency of wind farms in Turkey. [...] Read more.
The production of renewable energy is becoming one of the most important issues for communities due to the increasing energy demand. The purpose of this paper is to develop a systematized, sustainability-focused evaluation framework for determining the efficiency of wind farms in Turkey. The environmental impact and long-term viability of wind farms are evaluated using an evaluation framework centered on sustainability. The evaluation of their sustainability involves analyzing their energy production, environmental impacts and economic viability. In this study, DEA–Fuzzy COPRAS aims to evaluate the efficiency of 11 wind power plants located in Turkey in the Marmara Region. As inputs, the number of wind turbines, investment cost and distance from the grid are selected. As output, electricity is produced, and daily production time is considered. The proposed DEA–Fuzzy COPRAS aims to eliminate the disadvantages of the conventional methods and to be able to make better decisions regarding the weight value under uncertain conditions. The main advantages of the proposed DEA–Fuzzy COPRAS include a more accurate evaluation of efficiency and the ability to consider multiple criteria simultaneously. Additionally, the proposed DEA–Fuzzy COPRAS considers uncertainty in the inputs and outputs of wind energy production. The results of the proposed work are validated by comparing them with those obtained from a sensitivity analysis of the criteria. Therefore, decision makers can evaluate the efficiency of wind power plants accurately under an imprecise environment. Wind power plant managers or investors and other renewable energy projects can benefit from the proposed method’s implementation by allowing governments and stakeholders to save money and make better use of resources during the planning phase. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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22 pages, 7176 KiB  
Article
A Model to Reduce Machine Changeover Time and Improve Production Efficiency in an Automotive Manufacturing Organisation
by Mariusz Niekurzak, Wojciech Lewicki, Hasan Huseyin Coban and Milena Bera
Sustainability 2023, 15(13), 10558; https://doi.org/10.3390/su151310558 - 4 Jul 2023
Cited by 2 | Viewed by 2283
Abstract
One of the key postulates of the modern automotive industry is the increase in production efficiency while minimizing costs. In the opinion of experts from the automotive industry, meeting this condition may be the first stage on the way to preventing waste generation [...] Read more.
One of the key postulates of the modern automotive industry is the increase in production efficiency while minimizing costs. In the opinion of experts from the automotive industry, meeting this condition may be the first stage on the way to preventing waste generation and implementing a circular economy model. The article presents a case study of issues related to the lean manufacturing methodology in terms of the impact of shortening the changeover time of the assembly line on the overall production efficiency. The presented considerations focus on the optimization of the production process using the SMED (Single Minute Exchange of Die) technique of a selected spare part. From the point of view of the Lean Manufacturing concept, the main goal of the SMED technique is to increase the flexibility of responding to changing customer needs by shortening the changeover times and faster responses to changing orders. The article describes the stages of implementing the SMED method and its impact on the increase in the OEE (Overall Equipment Efficiency) index, which allows for the percentage recognition of the degree of machine park utilization, which is one of the key factors for assessing energy efficiency. In addition, the benefits that have been achieved by using this method in terms of time and economy have been presented. The theoretical aspects related to the method used were supplemented with its practical implementation in order to improve the changeovers in a manufacturing company in the automotive industry. Based on the obtained test results, an analysis of the effectiveness of the measures taken to reduce the changeover time was carried out. The use of the SMED methodology contributed to a significant reduction in changeover time—by as much as 291.4 s. The burden on operators was significantly reduced—the total time and number of operations performed by them (both internal and external) was reduced. Operator paths have also been shortened using simple procedures such as changing the layout of the lines and modifying the changeover tool trolleys and tool locking system at the stations. The presented research may be helpful in answering the question whether the implementation of the SMED idea may be the key to effective resource management and, at a later stage, to the implementation of the circular economy model. In addition, the research results can find their practical application among both manufacturers of spare parts and the vehicles themselves, considering introducing process changes on their production lines in order to increase production efficiency and implementing the idea of industrial sustainability. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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22 pages, 2265 KiB  
Article
Q-ROF Fuzzy TOPSIS and VIKOR Methods for the Selection of Sustainable Private Health Insurance Policies
by Babek Erdebilli, Ebru Gecer, İbrahim Yılmaz, Tamer Aksoy, Umit Hacıoglu, Hasan Dinçer and Serhat Yüksel
Sustainability 2023, 15(12), 9229; https://doi.org/10.3390/su15129229 - 7 Jun 2023
Cited by 9 | Viewed by 1444
Abstract
As a result of the inability of people to meet their demands in the face of increasing demands, people tend to have private health insurance in addition to the general health insurance offered as a public service. Due to the increasing trend of [...] Read more.
As a result of the inability of people to meet their demands in the face of increasing demands, people tend to have private health insurance in addition to the general health insurance offered as a public service. Due to the increasing trend of taking out private sustainable health insurance, the number of private sustainable health insurance plans in the health insurance market has increased significantly. Therefore, people may be confronted by a wide range of private health insurance plan options. However, there is limited information about how people analyze private health insurance policies to protect their health in terms of benefit payouts as a result of illness or accident. Thus, the objective of this study is to provide a model to aid people in evaluating various plans and selecting the most appropriate one to provide the best healthcare environment. In this study, a hybrid fuzzy Multiple Criteria Decision Making (MCDM) method is suggested for the selection of health insurance plans. Because of the variety of insurance firms and the uncertainties associated with the various coverages they provide, q-level fuzzy set-based decision-making techniques have been chosen. In this study, the problem of choosing private health insurance was handled by considering a case study of evaluations of five alternative insurance companies made by expert decision makers in line with the determined criteria. After assessments by expert decision makers, policy choices were compared using the Q-Rung Orthopair Fuzzy (Q-ROF) sets Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Q-ROF VIšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods. This is one of the first attempts to solve private health policy selection under imprecise information by applying Q-ROF TOPSIS and Q-ROF VIKOR methods. At the end of the case study, the experimental results are evaluated by sensitivity analysis to determine the robustness and reliability of the obtained results. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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30 pages, 4057 KiB  
Article
Green Closed-Loop Supply Chain Networks’ Response to Various Carbon Policies during COVID-19
by Sina Abbasi and Babek Erdebilli
Sustainability 2023, 15(4), 3677; https://doi.org/10.3390/su15043677 - 16 Feb 2023
Cited by 102 | Viewed by 3164
Abstract
As concerns about the environment continue to increase and restrictions become tougher, professionals in business and legislators are being compelled to investigate the environmental effects of the activities associated with their supply chains. The control of carbon emissions by governments all over the [...] Read more.
As concerns about the environment continue to increase and restrictions become tougher, professionals in business and legislators are being compelled to investigate the environmental effects of the activities associated with their supply chains. The control of carbon emissions by governments all over the world has involved the adoption of a variety of strategies to lower such emissions. This research optimizes COVID-19 pandemic logistics management as well as a green closed-loop supply chain design (GCLSCD) by basing it on carbon regulatory rules. This research looks at three of the most common types of normal CO2 restrictions. In the models that have been proposed, both costs and emissions are optimized. When it comes to supply chain (SC) activities, there is a delicate balance to strike between location selection, the many shipment alternatives, and the fees and releases. The models illustrate these tensions between competing priorities. Based on the numerical experiment, we illustrate the impact that a variety of policies have on costs in addition to the efficiency with which they reduce emissions. By analyzing the results of the models, managers can make predictions concerning how regulatory changes may affect overall emissions from SC operations. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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41 pages, 4597 KiB  
Article
Analyzing Healthcare and Wellness Products’ Quality Embedded in Online Customer Reviews: Assessment with a Hybrid Fuzzy LMAW and Fermatean Fuzzy WASPAS Method
by Çiğdem Sıcakyüz
Sustainability 2023, 15(4), 3428; https://doi.org/10.3390/su15043428 - 13 Feb 2023
Cited by 8 | Viewed by 3379
Abstract
With the high impetus in global digitization, online shopping (OS) is anticipated to increase further in the near future. Contrary to this anticipation, however, recent studies have emphasized a certain amount of drop in a considerable number of online purchasing transactions in 2022. [...] Read more.
With the high impetus in global digitization, online shopping (OS) is anticipated to increase further in the near future. Contrary to this anticipation, however, recent studies have emphasized a certain amount of drop in a considerable number of online purchasing transactions in 2022. One of the reasons might be customer dissatisfaction. To analyze online customer reviews, manual sentiment analysis was conducted to detect which quality criteria cause the dissatisfaction of online shoppers. The quality parameters are categorized into product, delivery service, and aftersales service quality (SQ). These main quality criteria are then divided into sub-factors. Eight health category products, including personal care products, wellness products, and household cleaners, were ranked to the importance of the sub-quality parameters using the multi-criteria decision-making (MCDM) method. In this study, a new hybrid MCDM method was also proposed, which combines the triangular fuzzy logarithm methodology of additive weights (F-LMAW) and the Fermatean fuzzy weighted aggregated sum product assessment method (FF-WASPAS). The study reveals that the most important criteria were products’ performance, as well as their side effects, pay-back, and change possibility, while the products’ reasonable price was the least important criterion. Aftersales service was more significant than delivery service. Furthermore, moisturizing creams and medical pillows were the most popular products bought in OS compared with hair conditioners and washing liquids. The study’s multifold contributions and managerial implications were elaborately discussed. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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13 pages, 2580 KiB  
Article
A Voxelization Algorithm for Reconstructing mmWave Radar Point Cloud and an Application on Posture Classification for Low Energy Consumption Platform
by Jiacheng Wu, Han Cui and Naim Dahnoun
Sustainability 2023, 15(4), 3342; https://doi.org/10.3390/su15043342 - 11 Feb 2023
Cited by 2 | Viewed by 1879
Abstract
Applications for millimeter-wave (mmWave) radars have become increasingly popular in human activity recognition. Many researchers have combined radars with neural networks and gained a high performance on various applications. However, most of these studies feed the raw point cloud data directly into the [...] Read more.
Applications for millimeter-wave (mmWave) radars have become increasingly popular in human activity recognition. Many researchers have combined radars with neural networks and gained a high performance on various applications. However, most of these studies feed the raw point cloud data directly into the networks, which can be unstable and inaccurate under certain circumstances. In this paper, we define a reliability measure of the point cloud data and design a novel voxelization algorithm to reconstruct the data. Experiments show that our algorithm can improve the stability of the point cloud generated from mmWave radars in terms of error reduction and scene re-construction. We demonstrate the effectiveness of our proposed algorithm using a neural network-based system for identifying a person’s sitting direction. In our experiment, compared with the baseline, our voxelization algorithm can improve the system in terms of accuracy (4.3%), training time (55.6%), and computational complexity, which is more suitable for light-weighted networks and low energy consumption platforms. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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17 pages, 330 KiB  
Article
The Evaluation and Improvement of the Production Processes of an Automotive Industry Company via Simulation and Optimization
by Durdu Hakan Utku
Sustainability 2023, 15(3), 2331; https://doi.org/10.3390/su15032331 - 27 Jan 2023
Cited by 3 | Viewed by 2144
Abstract
Production delays are significant problems for the loss of goodwill of the customers and the loss of profits associated with them. The delays may accrue as a result of insufficient resource planning and poorly designed unsatisfactory procedures. In this study, a new mathematical [...] Read more.
Production delays are significant problems for the loss of goodwill of the customers and the loss of profits associated with them. The delays may accrue as a result of insufficient resource planning and poorly designed unsatisfactory procedures. In this study, a new mathematical model is proposed to optimize the production processes by minimizing production delays, and a simulation model is developed to test the alternative facility designs. The purpose is to increase customer satisfaction by ensuring that the products are delivered timely and preventing lost sales in an automotive company that manufactures garbage collectors by using real data. The mixed-integer programming problem related to the minimization of production delays is solved by the GAMS CPLEX 24.1.3 software. In this way, the total delay in the production area is minimized by the mathematical model to prevent labor and time loss. Accordingly, the alternative designs are investigated for the improvement of the production processes by using discrete system simulation. A system analysis is performed to determine the bottlenecks in the production processes by developing a simulation model via the ARENA simulation software. With the proposed facility layout alternatives, the delays are eliminated, the total production time is reduced, and an increase in production efficiency is observed. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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16 pages, 4232 KiB  
Article
High-Order Sliding Mode Magnetometer for Excitation Fault Detection of Elevator Traction Synchronous Motor under the Background of Industrial Engineering
by Peng Shao, Xiaozhou Tang, Bo Zheng, Dongyang Li, Shu Chen and Huipin Lin
Sustainability 2023, 15(2), 1239; https://doi.org/10.3390/su15021239 - 9 Jan 2023
Cited by 1 | Viewed by 1084
Abstract
In order to solve the excitation problem of elevator traction permanent magnet synchronous motors (PMSMs), a new high-order sliding mode flux observer based on a hybrid reaching rate is proposed under the background of industrial engineering to detect loss of excitation faults in [...] Read more.
In order to solve the excitation problem of elevator traction permanent magnet synchronous motors (PMSMs), a new high-order sliding mode flux observer based on a hybrid reaching rate is proposed under the background of industrial engineering to detect loss of excitation faults in real time. Firstly, a new high-order sliding mode flux observer is designed to solve the problem of the traditional sliding mode observer not being able to accurately detect the loss of excitation fault when the load resistance changes. Then, based on the sliding mode variable structure equivalent control principle, a PMSM flux estimation formula is established. The sinusoidal input function replaces the traditional symbolic process, and a mixed approach law is designed to replace the constant speed approach rate. The adaptive adjustment of the boundary layer of the sinusoidal input function is realized through a fuzzy control system, which effectively suppresses the chattering problem caused by the sliding mode variable structure and improves the observation accuracy of rotor position. The stability of the system is verified by Lyapunov’s second method. MATLAB/Simulink is used to build the simulation model of the PMSM control system with the new sliding mode observer, and the simulation results are compared with those of a traditional sliding mode observer. The results show that compared with the conventional observer, the new sliding mode observer can track the rotor position quickly, and the system has better anti-interference abilities and stability. Finally, the feasibility and effectiveness of this method are verified via simulations and experiments. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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22 pages, 722 KiB  
Article
A Novel Hybrid Methodology to Study the Risk Management of Prefabricated Building Supply Chains: An Outlook for Sustainability
by Tian Zhu and Guangchen Liu
Sustainability 2023, 15(1), 361; https://doi.org/10.3390/su15010361 - 26 Dec 2022
Cited by 13 | Viewed by 2522
Abstract
The management of the prefabricated building supply chain involves the entire process of prefabricated buildings. There are many uncertain factors, and the risk factors in any link will affect the overall operation of the supply chain. In order to achieve the “dual carbon” [...] Read more.
The management of the prefabricated building supply chain involves the entire process of prefabricated buildings. There are many uncertain factors, and the risk factors in any link will affect the overall operation of the supply chain. In order to achieve the “dual carbon” goal as soon as possible and promote the sustainable development of the building supply chain, it is very important to study the risk management of the assembly building supply chain. The risk management of the prefabricated building supply chain involves risk recognition, risk prediction, risk assessment, and risk response. In this study, on the basis of literature research, the WBS-RBS (Work Breakdown Structure–Risk Breakdown Structure) method comprehensively uses the working link and risk type of the prefabricated building supply chain to establish an indicator system for risk factors in the prefabricated building supply chain. Then, the risk prediction and evaluation model of the neural network of BP (Back Propagation) through Python software is established to predict the risk of prefabricated building supply chains. After verification, it was found that the accuracy of the training set and test set reached 100% and 96.6667%. The results showed that the BP neural network had good effects on the risk forecast of the prefabricated building supply chain, which provided certain risk predictions for the risk prediction of the prefabricated building supply chain. For reference, on the basis of risk prediction, in order to explore the importance of risk factors to the results of BP neural network prediction results, the characteristic importance algorithm of machine learning replacement features further analyzes the risk factors of the prefabricated building supply chain. Finally, based on the prefabricated construction project of enterprise A, risk prediction and evaluation of its supply chain management were carried out, countermeasures for targeted risks were proposed, and we provided new research on the sustainable development of the assembled building supply chain to provide new research ideas. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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14 pages, 2401 KiB  
Article
The Impact of Sustainable Development on the Public Health System of the Elderly in the Internet of Things Environment
by Huimin Li
Sustainability 2022, 14(24), 16505; https://doi.org/10.3390/su142416505 - 9 Dec 2022
Cited by 3 | Viewed by 1448
Abstract
In order to explore how to establish an effective public health and long-term health care system for the elderly in the Internet of Things environment, sustainable development of the public health system for the elderly in the Internet of Things environment was proposed. [...] Read more.
In order to explore how to establish an effective public health and long-term health care system for the elderly in the Internet of Things environment, sustainable development of the public health system for the elderly in the Internet of Things environment was proposed. Through field research, the need of the elderly for home-based care can be divided into the following four categories: daily care, medical care, emergency care, and emotional care. Through the key technical problems and solutions of information recommendation represented by the Internet of Things, we explored the research on how to establish the elderly care system. Existing research shows that nearly 90% of the elderly chose their own home or their children’s to provide care for the elderly, while the proportion of rural elderly who chose family members to provide care for the elderly reaches 97%. However, as an important supplement to family support, the acceptance of institutional support in the public is not optimistic; among them, the overall proportion of the elderly who favored nursing homes as providers for elderly care in the future was less than 5%, and the willingness and attitude of the rural elderly regarding the institutional elderly care model were more disapproving, with only 1.44% of them recognized. Therefore, sustainable development in the Internet of Things environment is not only a key measure to effectively solve the mismatch between supply and demand of elderly care services, but also a favorable exploration for information technology to play an important role in the field of public services. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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19 pages, 13092 KiB  
Article
Simulation Optimization of an Industrial Heavy-Duty Truck Based on Fluid–Structure Coupling
by Xinyu Song, Fang Cao, Weifeng Rao and Peiwen Huang
Sustainability 2022, 14(21), 14519; https://doi.org/10.3390/su142114519 - 4 Nov 2022
Viewed by 1217
Abstract
In order to realize the sustainable development of the field of automotive industrial engineering and reduce the emissions of heavy-duty trucks (HDTs), a simulation analysis method that combined fluid–structure coupling and a discrete phase model was proposed in this study. The pressure, velocity, [...] Read more.
In order to realize the sustainable development of the field of automotive industrial engineering and reduce the emissions of heavy-duty trucks (HDTs), a simulation analysis method that combined fluid–structure coupling and a discrete phase model was proposed in this study. The pressure, velocity, and other parameters of an HDT air filter and its cartridge were analyzed by using CFX and the Static Structure module in the ANSYS software. The results showed that under six different flow rates, the error between the simulation results and the test results was basically less than 3% (the maximum error was 3.4%), and the pressure distribution of the fluid in the air filter was very uneven, leading to a severe deformation of 3.51 mm in the filter element. In order to reduce the pressure drop of the air filter and the deformation of the filter element, the position of the air inlet duct, the height of the filter element, and the number of folds of the air filter were optimized in this study. The optimization results showed that when the rated flow was 840 m3/h, compared with the original structure, the pressure drop of the air filter was reduced by 445 Pa, the maximum deformation of the filter element was reduced by 54.1% and the average deformation is reduced by 39.8%. After the optimization, the structural parameters of the air filter were as follows: the position of the air inlet moved down 126 mm along the shell, the filter height was 267 mm, and the pleat number of the filter element was 70. The simulation method and optimization design method of an air filter based on fluid–structure interaction presented in this study can be used to reduce the pressure drop, improve the engine performance, and reduce the amount of harmful emissions. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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24 pages, 1920 KiB  
Article
Strategic Alignment of Management Information System Functions for Manufacturing and Service Industries with an F-MCGDM Model
by Ugur Bac
Sustainability 2022, 14(21), 14428; https://doi.org/10.3390/su142114428 - 3 Nov 2022
Viewed by 1519
Abstract
Considering constantly increasing global competition in the market and developing technologies, information systems (ISs) have become an important component of the business world and a vital component of intelligent systems. An IS provides support for planning, controlling, analyzing activities, and support in decisions [...] Read more.
Considering constantly increasing global competition in the market and developing technologies, information systems (ISs) have become an important component of the business world and a vital component of intelligent systems. An IS provides support for planning, controlling, analyzing activities, and support in decisions by managing data throughout the organization to assist executives in their decisions. The main function of an IS is to collect data spread between various parts of the organization and business partners and to process these collected data to form reliable information, which is required for decision making. Another critical function of an IS is to transfer the necessary information to the point-of-need in a timely manner. ISs assist in the conversion of data and information into meaningful outcomes. An IS is a combination of software, data storage hardware, related infrastructure, and people in the organization that use the system. Many business organizations rely on management information systems (MISs), and they conduct their critical operations based on these systems. The existence of an efficient MIS is a requirement for the sustainability of any business. However, MIS’s efficiency depends on the business’s requirements and nature. The compatibility of MIS with business in the company is vital for the successful implementation of these systems. The current study analyzes differences in expectations of manufacturing and service industries from MISs. For this aim, a fuzzy multi-criteria group decision-making (F-MCGDM) model is proposed to determine the differentiating success factors of MIS in both manufacturing and service industries. Findings indicate that there are considerable differences in the needs of both industries from MIS. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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19 pages, 1193 KiB  
Article
A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0
by Esra Boz, Sinan Çizmecioğlu and Ahmet Çalık
Sustainability 2022, 14(21), 13839; https://doi.org/10.3390/su142113839 - 25 Oct 2022
Cited by 11 | Viewed by 2190
Abstract
The COVID-19 pandemic has led to major disruptions in workflows across all industries. All sectors are trying to sustain operations during this extremely difficult time and the healthcare sector is the most important of them. It is unthinkable to stop the operations of [...] Read more.
The COVID-19 pandemic has led to major disruptions in workflows across all industries. All sectors are trying to sustain operations during this extremely difficult time and the healthcare sector is the most important of them. It is unthinkable to stop the operations of the health system because it serves human life. Health institutions must supply the products such as masks, gloves, and ventilators subject to service on time for certain activities to continue indefinitely under all conditions. By adopting modern logistics activities and technologies, healthcare organizations can provide sustainable diagnosis and treatments to patients by automating their various operations. With the COVID-19 pandemic, how to select an appropriate sustainable supplier has become an important task in the era of Logistics 4.0. From this viewpoint, a sustainable supplier selection framework is implemented for a health institution under the effect of the pandemic. To determine the direct effects of the pandemic in the health sector, fuzzy Multi-Criteria Decision-Making (MCDM) methods are utilized in the application. After a thorough review of the literature and interviews with experts, the criteria are organized in a comprehensive hierarchical structure. The fuzzy Best-Worst Method (F-BWM) technique is employed to find the weights for the determined criteria. Consequently, the fuzzy Additive Ratio Assessment Method (F-ARAS) method was applied to rank the alternative suppliers. In addition, with a comprehensive sensitivity analysis, alternative situations are examined against possible breaks in the supply chain. Thus, from the perspective of Logistics 4.0 and sustainability, this study contributes to the literature with an analysis of the health system’s survival in difficult and fragile periods, such as COVID-19. Investigating the importance of SSS can be a road map for the policymakers and the decision-makers is beneficial since the impact of COVID-19 on SSS is studied from the perspective of Logistics 4.0. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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24 pages, 727 KiB  
Article
Population Aging, Industrial Intelligence and Export Technology Complexity
by Kexu Wu, Zhiwei Tang and Longpeng Zhang
Sustainability 2022, 14(20), 13600; https://doi.org/10.3390/su142013600 - 20 Oct 2022
Cited by 4 | Viewed by 2432
Abstract
The ageing of the population has become a serious test for all countries and regions, and industrial intelligence, as a new development model that integrates traditional industries with modern technology, will contribute to the deep integration of the industrial and innovation chains and [...] Read more.
The ageing of the population has become a serious test for all countries and regions, and industrial intelligence, as a new development model that integrates traditional industries with modern technology, will contribute to the deep integration of the industrial and innovation chains and thus to the enhancement of national core competitiveness. Based on the dual influence of population ageing and industrial intelligence, this paper uses the 2016 version of the World Input-Output Database (WIOD) data for 16 manufacturing industries in 43 countries from 2000 to 2014 to construct an econometric regression model to empirically test the relationship between population ageing, industrial intelligence and technological complexity of exports. The results of the study show, firstly, that population ageing plays a positive role in the technical complexity of exports. Secondly, the introduction of industrial intelligence mitigates the adverse effects of an ageing population through a complementary substitution mechanism on the one hand, and promotes industrial upgrading and transformation through the infiltration and expansion effects of industrial intelligence on the other, which in turn has a positive impact on the increase in technological sophistication of exports. In addition, the paper further divides the level of industry technology, the level of national development and the age structure of the ageing population, and explores the impact of industry intelligence in different dimensions. The results show that industrial intelligence can have a positive impact on export technological sophistication at the industry level, at the national level and in terms of ageing demographics. The research results provide a new way of thinking, through which countries around the world can formulate population policies and industrial policies and improve the complexity of export technology under the background of aging. Full article
(This article belongs to the Special Issue Sustainable Development of Industrial Engineering With the Application of Intelligent Systems)
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