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

Deadline for manuscript submissions: closed (23 March 2024) | Viewed by 27601

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Prof. Dr. Dragomir Mihai

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Department of Design Engineering and Robotics, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
Interests: quality engineering and management; low carbon production; digital transformation
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Prof. Dr. Calin Gheorghe Dan Neamtu

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Guest Editor

Department of Design Engineering, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Interests: CAD in production systems; digital heritage; virtual reality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The goal of this special issue is to showcase theoretical and practical contributions regarding sustainable production and sustainable operations management from a variety of industries, especially in the wake of an accelerating transformation towards a carbon neutral economy and an advanced digital society. This effort is meant to complement and supplement existing scientific literature in the field by providing a database of new concepts and tools, as well as industrially validated good practices, that can inspire academics and production engineers to improve the performances of present-day production systems by implementing them within the organizations and networks where they are active.

The focus of this anthology is on the manufacturing industry which is undergoing complex transformations and has to answer to difficult challenges related not only to sustainability and digitalization, but also supply chain disruptions, resource depletion and engineering personnel shortages. However, other industries going through similar changes regarding their operations can represents possible topics to be approached by the authors seeking to submit to this issue. Also, the editors encourage the submission of interdisciplinary and multidisciplinary approaches that can bring new insights into the field, stimulating and reinforcing competitiveness in harmony with the natural environment and the social landscape, which are in need of protection and nurturing.

Prof. Dr. Dragomir Mihai
Prof. Dr. Calin Neamtu
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 production
sustainable operations
smart products
smart processes

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Sustainable Production & Operations Management—2nd Edition in Sustainability (1 article)

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Research

25 pages, 6363 KiB

Open AccessArticle

Risk Assessment in Sustainable Production: Utilizing a Hybrid Evaluation Model to Identify the Waste Factors in Steel Plate Manufacturing

by Kuei-Kuei Lai, Sheng-Wei Lin, Huai-Wei Lo, Chia-Ying Hsiao and Po-Jung Lai

Sustainability 2023, 15(24), 16583; https://doi.org/10.3390/su152416583 - 6 Dec 2023

Cited by 2 | Viewed by 1296

Abstract

In the realm of industrial development, steel has consistently played a pivotal role due to its extensive applications. This research aims to refine the process of steel plate manufacturing, focusing on reducing waste as a critical step towards embracing sustainable development and aligning with the Sustainable Development Goals (SDGs). Our approach integrates a hybrid analytical model grounded in Failure Mode and Effects Analysis (FMEA) to thoroughly investigate the waste-producing elements in steel plate production. The methodology of this study is structured in a three-pronged approach, as follows: Initially, it involves meticulous on-site inspections across various factories to pinpoint potential sources of waste. Subsequently, we employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to intricately analyze the interconnectedness and impact of various risk factors. The final phase utilizes the Performance Calculation technique within the Integrated Multiple Multi-Attribute Decision-Making (PCIM-MADM) framework for aggregating and evaluating risk scores. This multifaceted approach aids in establishing the priorities for corrective actions aimed at waste reduction. Our findings present innovative solutions for identifying and mitigating critical waste factors, contributing to a more efficient and sustainable steel manufacturing process. These strategies promise scalability and adaptability for broader industrial applications and provide critical insights into resource optimization. This research directly supports the objectives of SDG 9, which focuses on building resilient infrastructure and promoting sustainable industrialization. Furthermore, it resonates with SDG 12, advocating for sustainable consumption and production patterns. By enhancing the efficiency and cost effectiveness of steel plate production, this study significantly contributes to minimizing waste and elevating the sustainability of industrial practices. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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20 pages, 4623 KiB

Open AccessArticle

Enhancing Aerospace Industry Efficiency and Sustainability: Process Integration and Quality Management in the Context of Industry 4.0

by Gheorghe Ioan Pop, Aurel Mihail Titu and Alina Bianca Pop

Sustainability 2023, 15(23), 16206; https://doi.org/10.3390/su152316206 - 22 Nov 2023

Cited by 2 | Viewed by 4526

Abstract

This paper delves into the multifaceted domain of the aerospace industry, examining its evolution, current challenges, and imperative focus on quality management and process integration. The aerospace sector, driven by technological advancements and a burgeoning global demand for air travel and freight transport, necessitates a thorough analysis of its industrial fabric and operational intricacies. This research endeavors to analyze the dynamics of the aerospace industry, pinpoint its challenges, and propose an integrated approach to enhance efficiency, quality, and sustainability. The primary goals encompass understanding the evolving industry landscape, identifying critical challenges, and offering innovative solutions by amalgamating the principles of Industry 4.0 into quality management and processes within the aerospace sector. Through an in-depth exploration of various facets, this research underscores the pivotal role of efficient processes and integrated quality management in achieving sustainable growth and competitiveness in the aerospace industry. By aligning with the paradigm of Industry 4.0, organizations can optimize their operations and contribute to the industry’s advancement, delivering safer and more cost-effective aerospace products. The study adopts a multifaceted approach, incorporating an extensive literature review, a critical analysis of industry trends, the examination of quality management frameworks, and a thorough evaluation of the integration potential of Industry 4.0 technologies. The research also involves case studies and expert insights to validate the proposed approach. The investigation reveals that by leveraging Industry 4.0 technologies and embracing an integrated approach to quality management, the aerospace industry can significantly enhance operational efficiency, product quality, and overall sustainability. The seamless integration of processes and the implementation of advanced quality frameworks pave the way for a more competitive and future-ready aerospace industry, meeting the evolving demands of a globalized world. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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24 pages, 5174 KiB

Open AccessArticle

Revolutionizing the Garment Industry 5.0: Embracing Closed-Loop Design, E-Libraries, and Digital Twins

by Semih Donmezer, Pinar Demircioglu, Ismail Bogrekci, Gokcen Bas and Muhammet Numan Durakbasa

Sustainability 2023, 15(22), 15839; https://doi.org/10.3390/su152215839 - 10 Nov 2023

Cited by 4 | Viewed by 2227

Abstract

This study presents an innovative approach for modernizing the garment industry through the fusion of digital human modeling (DHM), virtual modeling for fit sizing, ergonomic body-size data, and e-library resources. The integration of these elements empowers manufacturers to revolutionize their clothing design and production methods, leading to the delivery of unparalleled fit, comfort, and personalization for a wide range of body shapes and sizes. DHM, known for its precision in representing human bodies virtually and integrating anthropometric data, including ergonomic measurements, enhances the shopping experience by providing valuable insights. Consumers gain access to the knowledge necessary for making tailored clothing choices, thereby enhancing the personalization and satisfaction of their shopping experience. The incorporation of e-library resources takes the garment design approach to a data-driven and customer-centric level. Manufacturers can draw upon a wealth of information regarding body-size diversity, fashion trends, and customer preferences, all sourced from e-libraries. This knowledge supports the creation of a diverse range of sizes and styles, promoting inclusivity and relevance. Beyond improving garment fit, this comprehensive integration streamlines design and production processes by reducing the reliance on physical prototypes. This not only enhances efficiency but also contributes to environmental responsibility, fostering a more sustainable and eco-friendly future for the garment industry and embracing the future of fashion, where technology and data converge to create clothing that authentically fits, resonates with consumers, and aligns with the principles of sustainability. This study developed the mobile application integrating with the information in cloud database in order to present the best-suited garment for the user. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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18 pages, 7507 KiB

Open AccessArticle

FabricNET: A Microscopic Image Dataset of Woven Fabrics for Predicting Texture and Weaving Parameters through Machine Learning

by Mine Seçkin, Ahmet Çağdaş Seçkin, Pinar Demircioglu and Ismail Bogrekci

Sustainability 2023, 15(21), 15197; https://doi.org/10.3390/su152115197 - 24 Oct 2023

Cited by 4 | Viewed by 3895

Abstract

This research presents an approach aimed at enhancing texture recognition and weaving parameter estimation in the textile industry to align with sustainability goals and improve product quality. By utilizing low-cost handheld microscopy and machine learning, this method offers the potential for more precise production outcomes. In this study, textile images were manually labeled for texture, specific mass, weft, and warp parameters, followed by the extraction of various texture features, resulting in a comprehensive dataset comprising four hundred and fifty-eight inputs and four outputs. Prominent machine learning algorithms, including XGBoost, RF, and MLP, were applied, resulting in noteworthy achievements. Specifically, XGBoost demonstrated an impressive texture classification accuracy of 0.987, while RF yielded the lowest MAE (5.121 g/cm) in specific mass prediction. Additionally, weft and warp estimations displayed superior accuracy compared to manual measurements. This research emphasizes the crucial role of AI in improving efficiency and sustainability within the textile industry, potentially reducing resource wastage, enhancing worker safety, and increasing productivity. These advancements hold the promise of significant positive environmental and social impacts, marking a substantial step forward in the industry’s pursuit of its objectives. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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23 pages, 1344 KiB

Open AccessArticle

Impact of Digitalization on Process Optimization and Decision-Making towards Sustainability: The Moderating Role of Environmental Regulation

by Yixuan Peng, Sayed Fayaz Ahmad, Muhammad Irshad, Muna Al-Razgan, Yasser A. Ali and Emad Marous Awwad

Sustainability 2023, 15(20), 15156; https://doi.org/10.3390/su152015156 - 23 Oct 2023

Cited by 7 | Viewed by 4610

Abstract

Digitalization has brought a significant improvement in process optimization and decision-making processes, in particular in pursuing the goal of sustainability. This study examines how digitalization has affected process optimization and decision-making towards sustainability, focusing on Pakistan’s manufacturing sector. This study also examines the moderating role of environmental regulations between digitalization and sustainable practices. This study is based on quantitative methodology. Purposive sampling was used to gather primary data from 554 managers and engineers working in manufacturing industries in Pakistan through a closed-ended questionnaire. Smart PLS was used for data analysis. The findings show digitalization’s positive and significant influence on process optimization and decision-making. The results also show that environmental regulations have a significant moderating effect on the digitalization of processes and decision-making towards sustainability practices. The findings provide a guideline for industries, decision-makers, and researchers for developing strategies that effectively use digitalization for sustainability and assist in achieving the Sustainable Development Goals (SGD-9, SGD-11, SGD-12, and SGD-13). Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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21 pages, 1074 KiB

Open AccessArticle

A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production

by Xuemei Chen, Bin Zhou, Anđelka Štilić, Željko Stević and Adis Puška

Sustainability 2023, 15(13), 10745; https://doi.org/10.3390/su151310745 - 7 Jul 2023

Cited by 10 | Viewed by 2455

Abstract

Green supplier selection is always one of the most important challenges in all of supply chain management, especially for production companies. The purpose is to have reliable suppliers which can fulfill all requests and be flexible in any supply chain stage. The aim of this paper is to create an adequate and strong MCDM (multicriteria decision making) model for the evaluation and selection of suppliers in a real environment. The main contribution of this study is proposing a novel fuzzy–rough MCDM model containing extension stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) methods with fuzzy–rough numbers (FRN). The integrated FRN SWARA–FRN ARAS model was implemented in a case study of eco-friendly material production. The FRN SWARA method was used to calculate the weights of 10 green criteria, while using FRN ARAS, 6 suppliers were evaluated. The results of the applied model show that supplier S3 received the highest ranking, followed by supplier S2, while supplier S5 performed the poorest. In order to verify the strengths of the developed fuzzy–rough approach, we created a comparative analysis, sensitivity analysis, and dynamic matrix, which confirm the robustness of our model. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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25 pages, 2077 KiB

Open AccessArticle

On Increasing Service Organizations’ Agility: An Artifact-Based Framework to Elicit Improvement Initiatives

by Mircea Fulea, Bogdan Mocan, Mihai Dragomir and Mircea Murar

Sustainability 2023, 15(13), 10189; https://doi.org/10.3390/su151310189 - 27 Jun 2023

Cited by 1 | Viewed by 1596

Abstract

The present research focuses on operational agility in service organizations, which are subject to variability through customers, service providers, suppliers, or unexpected events. As such, their management teams may face challenges in understanding their agility-related assets and success metrics, and furthermore in defining the scope of work for improvement initiatives. Previous research offers quite general insights into agility-related capabilities, practices, obstacles, or (agility-related) information quality evaluation. Yet, management teams need specific practices and techniques in order to improve operational agility capabilities, and thus increase their sustainable performance. We propose a conceptual framework and an artifact-centric algorithm that elicits and prioritizes improvement initiatives by (a) understanding agility-related assets by modelling operational business artifacts, (b) determining agility bottlenecks by identifying quality issues in operational artifacts, and (c) eliciting and prioritizing improvement initiatives to increase artifact quality. The framework application is discussed through a case study in a company operating in the rail freight industry, in which a set of initiatives to improve operational agility capabilities is obtained and prioritized. We conclude that the proposed algorithm is an applicable and relevant tool for management teams in service organizations, in their operational agility improvement endeavors. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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16 pages, 2101 KiB

Open AccessArticle

Sustainable Low-Carbon Production: From Strategy to Reality

by Denisa Szabo, Mihai Dragomir, Mihail Țîțu, Diana Dragomir, Sorin Popescu and Silvia Tofană

Sustainability 2023, 15(11), 8516; https://doi.org/10.3390/su15118516 - 24 May 2023

Cited by 2 | Viewed by 2018

Abstract

The present paper approaches the timely topic of sustainable production with low carbon emissions, investigating the link between existing strategies and policies and the reality that manufacturers must deal with, with the appraisal going from high-level national and international plans to specific firm needs. This is in line with the preoccupations of manufacturers in Europe to retain and regain their market shares under strict environmental excellence, one of the defining features of the continent’s economy. The existing strategies, specialized plans and mechanisms for the reduction of emissions were analyzed to discern their structural relationships and the clarity and palpability of their content when passing through the successive levels of interest. The research methodology employs the MEAL Plan for determining the state of the art, and based on the findings, two specific tools were used for policy analysis and informing a brainstorming and discussion session aimed at future improvements. The instruments used are SWOT-Radar Screen methodology and latent semantic analysis as implemented by the Tropes Zoom software. Structural connections were revealed, together with an improved understanding of the interventions proposed in 5 European-level strategies, 14 national-level strategies (with a focus on Romania) and a case analysis for a generic manufacturing company. Among the main findings, the authors propose improved awareness development for all the stakeholders, strengthened and correlated monitoring of sustainability results and a better implementation of an institutional ecosystem for providing support to companies. The results obtained are intended for the use of policy makers to improve their future planning cycles in a way that supports the companies in achieving these societal goals. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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16 pages, 669 KiB

Open AccessArticle

Exploring the Impact of Contingency Theory on Sustainable Innovation in Malaysian Manufacturing Firms

by Muhammad Fakhrul Yusuf, Nur Anis Imalyn Mohamad Nasarudin, Shahryar Sorooshian, Muhammad Ashraf Fauzi and Nur Muneerah Kasim

Sustainability 2023, 15(9), 7151; https://doi.org/10.3390/su15097151 - 25 Apr 2023

Cited by 3 | Viewed by 3753

Abstract

This study looks at the impact of contingency theory on sustainable innovation in Malaysian manufacturing firms. A quantitative approach was used, with convenience sampling to select participants from a target population of Malaysian manufacturing employees. An online survey distributed via email was used to collect 101 sets of data for the study. PLS-SEM (Partial Least Squares Structural Equation Modeling) was used to analyze the collected data. According to the findings, corporate sustainable support policies and sustainable incentives have a significant positive impact on sustainable innovation in Malaysian manufacturing firms, whereas top management commitment was found to be insignificant. Companies that prioritize sustainable practices through policies and incentives are more likely to promote sustainable innovation, according to the findings. As a result, businesses should prioritize developing these two attributes in order to foster sustainable innovation, thereby improving sustainability practices and contributing to the country’s long-term development goals. Future research should, however, investigate why top management commitment may not be a significant driver of sustainable innovation in Malaysian manufacturing firms. Full article

(This article belongs to the Special Issue Sustainable Production & Operations Management)

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