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Digital Transformation and Its Opportunities for Sustainable Manufacturing

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 39417

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Special Issue Editors

Dr. Jonathan Sze Choong Low

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Guest Editor

Agency for Science, Technology and Research (A*STAR), Singapore Institute of Manufacturing Technology (SIMTech), Singapore 138634, Singapore
Interests: Life Cycle Engineering; Sustainable Manufacturing; Life Cycle Assessment; Life Cycle Costing; Circular Economy

Dr. Mark Mennenga

E-Mail Website
Guest Editor

Technische Universität Braunschweig, Institute of Machine Tools and Production Technology, 38106 Braunschweig, Germany
Interests: Engineering Research Methodology, System of Systems Engineering, Sustainable Product-Service-Systems, Recycling 4.0, Research data management, Teaching and training for sustainability, Automotive Engineering, E-Mobility

Dr. Carlo Brondi

E-Mail Website1 Website2
Guest Editor

Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (CNR), 20133 Milano, Italy
Interests: production planning; process simulation; modeling; operations management; production; production management; optimization; sustainability metrics; integrated management systems; modular LCA assessment; industrial symbiosis; eco-design; technology substitution
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The digital transformation has been touted as the game changer especially for the manufacturing sector. Although mainly looked at from the perspective of economic growth (or recovery given the COVID-19 pandemic), businesses and governments recognise the potential of leveraging the same digital transformation enablers to facilitate the sector’s transition to sustainable manufacturing. For instance, the adoption of Industrial Internet-of-Things (IIoT), pervasive sensorisation of production systems at the shop floor- and factory-level, as well as the digitalisation of whole supply chains are generating an unprecedented amount of data. Coupled with the deployment of Cyber-Physical Production System (CPPS) and Digital Twins, these data open up new ways for how manufacturing systems and processes can be efficiently embedded in supply chains – so that the manufacturing and the whole life cycle of products consume less resources, emit less harmful emissions, and generate less waste and pollution.

This special issue aims to further explore the topics at the intersection of digital transformation and sustainable manufacturing. This special issue in particular explores research on intersection area between applicative sustainability aspects driving change in product chains and adoption of digital tools and methodologies to contextualize and improve related assessment, analysis and optimization. Both original research and review papers are welcome, from the various research disciplines, such as smart and sustainable manufacturing, life cycle engineering, eco-design, remanufacturing, circular economy and system of systems engineering. The following non-exhaustive list of topics can be addressed:

Data science and AI methods towards mitigating the environmental impacts of manufacturing;
Engineering and design of sustainable products, processes and/or supply chains;
Industry 4.0, Industrial Internet-of-Things (IIoT), Digital Twins and/or Cyber-Physical Production Systems (CPPS);
Sustainable cyber-physical product- and/or production-service-systems;
Shop-floor and/or dynamic life cycle assessment (LCA);
Sustainable operational and business model innovation;
Digital tracking and monitoring systems for sustainability;
Circular economy through management and digital tools;
Sustainability metrics;
Compliance with international standards.

Dr. Jonathan Sze Choong Low
Dr. Mark Mennenga
Dr. Carlo Brondi
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

Life Cycle Engineering
Industrial Sustainability
Eco-design
Industrial Ecology
Circular Economy
Digitalization
Industry 4.0
Cyber-Physical Production System (CPPS)
Industrial Internet-of-Things (IIoT)
Smart sensoring
LCA

Published Papers (10 papers)

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Research

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31 pages, 2242 KiB

Open AccessArticle

A Modular Tool to Support Data Management for LCA in Industry: Methodology, Application and Potentialities

by Davide Rovelli, Carlo Brondi, Michele Andreotti, Elisabetta Abbate, Maurizio Zanforlin and Andrea Ballarino

Sustainability 2022, 14(7), 3746; https://doi.org/10.3390/su14073746 - 22 Mar 2022

Cited by 14 | Viewed by 3891

Abstract

Life Cycle Assessment (LCA) computes potential environmental impacts of a product or process. However, LCAs in the industrial sector are generally delivered through static yearly analyses which cannot capture any temporal dynamics of inventory data. Moreover, LCA must deal with differences across background models, Life Cycle Impact Assessment (LCIA) methods and specific rules of environmental labels, together with their developments over time and the difficulty of the non-expert organization staff to effectively interpret LCA results. A case study which discusses how to manage these barriers and their relevance is currently lacking. Here, we fill this gap by proposing a general methodology to develop a modular tool which integrates spreadsheets, LCA software, coding and visualization modules that can be independently modified while leaving the architecture unchanged. We test the tool within the ORI Martin secondary steelmaking plant, finding that it can manage (i) a high amount of primary foreground data to build a dynamic LCA; (ii) different background models, LCIA methods and environmental labels rules; (iii) interactive visualizations. Then, we outline the relevance of these capabilities since (i) temporal dynamics of foreground inventory data affect monthly LCA results, which may vary by ±14% around the yearly value; (ii) background datasets, LCIA methods and environmental label rules may alter LCA results by 20%; (iii) more than 10⁵ LCA values can be clearly visualized through dynamically updated dashboards. Our work paves the way towards near-real-time LCA monitoring of single product batches, while contextualizing the company sustainability targets within global environmental trends. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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17 pages, 3055 KiB

Open AccessArticle

Ecological Planning of Manufacturing Process Chains

by Berend Denkena, Marcel Wichmann, Simon Kettelmann, Jonas Matthies and Leon Reuter

Sustainability 2022, 14(5), 2681; https://doi.org/10.3390/su14052681 - 25 Feb 2022

Cited by 1 | Viewed by 1740

Abstract

Production planning is a critical step for the implementation of sustainable production. It is necessary to consider energy and resource efficiency in all planning phases to promote sustainable production. In this paper, an approach for environmental impact assessment in all phases of process chain planning supported by process models is presented. The level of detail of the assessment is determined based on the level of detail of the planning phase. During the assessment, consumption of energy and resources is considered. This approach aims to align planning phases with the objective of sustainable production. In rough planning, the approach allows the selection of an ecologically favorable process chain. In detailed planning, process parameters can be selected based on their ecological sustainability. The approach can be integrated into the planning of process chains in order to consider ecological factors throughout all planning phases. The approach is evaluated by using an exemplary use case. The results indicate that rough planning under the consideration of uncertainties can form a reasonable prediction about resource efficiency for possible manufacturing routes. By systematically selecting a resource-efficient process chain, energy savings of up to 21% can be achieved for the presented use case. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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33 pages, 3463 KiB

Open AccessArticle

Self-Assessment Framework for Corporate Environmental Sustainability in the Era of Digitalization

by Eduard Eisner, Cadence Hsien, Mark Mennenga, Zi-Yu Khoo, Jasmin Dönmez, Christoph Herrmann and Jonathan Sze Choong Low

Sustainability 2022, 14(4), 2293; https://doi.org/10.3390/su14042293 - 17 Feb 2022

Cited by 9 | Viewed by 5794

Abstract

The shift towards a climate-neutral economy will affect businesses in the upcoming decades. Companies will need to increase their transformation towards environmentally sustainable businesses in the following years, in which digitalization might be a practical enabler to accelerate this transformation. However, as a starting point, companies require knowledge of their current sustainability performance to manage this transition and need a method that provides the necessary information. The use of self-assessment tools is a widely acknowledged method for such processes. Nevertheless, there is a lack of self-assessment tools that integrate sustainability and digitalization perspectives to overcome different organizational barriers. This paper focuses on how managers can be supported in planning their transformations by interlinking sustainability and digitization. Our objective is to enable the managers of companies to assess their current state in terms of corporate environmental sustainability and to explore their policies, information systems, and actions to support their transformation towards sustainable and digital businesses. A self-assessment tool based on a rapid questionnaire is presented after reviewing and synthesizing different approaches, including maturity modeling, sustainability reporting, and digital assessment tools. The self-assessment tool is improved upon evaluation by industry experts and the framework is tested on a case company. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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18 pages, 2957 KiB

Open AccessArticle

Systematic Development of Sustainability-Oriented Cyber-Physical Production Systems

by Christopher Rogall, Mark Mennenga, Christoph Herrmann and Sebastian Thiede

Sustainability 2022, 14(4), 2080; https://doi.org/10.3390/su14042080 - 11 Feb 2022

Cited by 4 | Viewed by 2125

Abstract

Manufacturing companies increasingly have to address the risks and contributions related to their environmental impacts. Therefore, more data are needed in order to provide full transparency with regard to production, and to highlight the potential relationships between the process data and the environmental impacts. In order to achieve this data transparency, targeted digitalization is needed that is tailored to the goal of reaching minimized environmental impacts. Cyber-physical production systems (CPPSs) are central for the digitalization of manufacturing. However, they may also come with an initial environmental backpack. Due to unawareness of relevant interdependencies when setting up CPPS, data may be collected which is not helpful or necessary for the development of sustainability-oriented CPPS. Therefore, a critical assessment is required which data is necessary to support sustainable manufacturing and to avoid unreflective data collection. This requires the identification of the relevant factors and their interdependencies within the context of sustainability in production. By identifying the influencing factors, the measurement strategy can be linked to the appropriate sensor technologies that explicitly contribute to the target fulfillment. The design of more sustainable data structures using a cross-impact analysis is illustrated in this paper as a generic methodological approach, which will be applied to a 3D-printing use case. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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19 pages, 904 KiB

Open AccessArticle

Role of Standards as an Enabler in a Digital Remanufacturing Industry

by Praneetha Pratapa, Ramesh Subramoniam and Jighyasu Gaur

Sustainability 2022, 14(3), 1643; https://doi.org/10.3390/su14031643 - 30 Jan 2022

Cited by 8 | Viewed by 3088

Abstract

There is plenty of research describing remanufacturing (reman) as the ultimate form of recycling. However, few studies have shown how standards that provide universally accepted definitions and practices can shift towards digitization and how digital technology can act as a catalyst for digital reman. Furthermore, there is no clear direction as to why and how standards and digital technology should work together in reman. Only minimal research (one article from the SCOPUS database) has explored the intersection of these three areas: reman challenges, standards, and digital technology. Many challenges that reman companies face prevent them from successfully transitioning to sustainable production methods. The challenges include high cost of resources, complex parts design, limited core availability, lack of internationally accepted definitions and protocols, poor design of reverse logistics networks, and poor consumer perceptions. On the other hand, digital technology can act as an enabler fueling environmental resilience through innovation. This paper studies how standards can play a role in helping digital technology solve reman challenges, thereby achieving the United Nations Sustainable Development Goal and providing significant opportunities for innovation for small and large enterprises transitioning towards digital reman. The current study is validated by highly experienced reman professionals using the analytical hierarchical process. It is intended to help practitioners assess their organization’s current manufacturing practices and improve resource productivity and business growth using the identified standards and technologies. Three-dimensional printing was found to have the most potential in solving reman challenges. Surprisingly, the Internet of Things ranked low despite lacking information on used products or cores being a significant challenge for suppliers. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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22 pages, 5363 KiB

Open AccessArticle

Digitalization Platform for Mechanistic Modeling of Battery Cell Production

by Matthias Thomitzek, Oke Schmidt, Gabriela Ventura Silva, Hassan Karaki, Mark Lippke, Ulrike Krewer, Daniel Schröder, Arno Kwade and Christoph Herrmann

Sustainability 2022, 14(3), 1530; https://doi.org/10.3390/su14031530 - 28 Jan 2022

Cited by 5 | Viewed by 3536

Abstract

The application of batteries in electric vehicles and stationary energy-storage systems is widely seen as a promising enabler for a sustainable mobility and for the energy sector. Although significant improvements have been achieved in the last decade in terms of higher battery performance and lower production costs, there remains high potential to be tapped, especially along the battery production chain. However, the battery production process is highly complex due to numerous process–structure and structure–performance relationships along the process chain, many of which are not yet fully understood. In order to move away from expensive trial-and-error operations of production lines, a methodology is needed to provide knowledge-based decision support to improve the quality and throughput of battery production. In the present work, a framework is presented that combines a process chain model and a battery cell model to quantitatively predict the impact of processes on the final battery cell performance. The framework enables coupling of diverse mechanistic models for the individual processes and the battery cell in a generic container platform, ultimately providing a digital representation of a battery electrode and cell production line that allows optimal production settings to be identified in silico. The framework can be implemented as part of a cyber-physical production system to provide decision support and ultimately control of the production line, thus increasing the efficiency of the entire battery cell production process. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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23 pages, 14432 KiB

Open AccessArticle

Riding the Digital Product Life Cycle Waves towards a Circular Economy

by Ramesh Subramoniam, Erik Sundin, Suresh Subramoniam and Donald Huisingh

Sustainability 2021, 13(16), 8960; https://doi.org/10.3390/su13168960 - 10 Aug 2021

Cited by 22 | Viewed by 5338

Abstract

Data driven organizations such as Amazon and Uber have raised the capabilities and expectations of customers to a new level by providing faster and cheaper products and services. The reviewed literature documented that 10–15% of the online products are returned and in many cases such products are not shelf-ready due to product obsolescence or slight wear and tear, thereby reducing profits. Many of these products are disposed of in landfills. There were very few publications that documented how integration of digitized product life cycle into the business model improves product returns and the remanufacturing processes. As societies continue on, environmentally responsible, digital journeys with connected devices and people, reverse supply chains and remanufacturing will play increased importance in fulfilling customers expanded expectations. The networks are evolving, wherein, data are collected from all phases of the product lifecycles from design, prototype, manufacturing, usage aftermarket, returns remanufacturing and recycling. The objective of this paper’s authors was to describe how all phases of product life cycles can be digitized to improve global reverse supply chains and remanufacturing. The authors performed a literature review and developed case studies to document current and to predict future transformational waves that will become increasingly used in many industrial sectors. The authors made recommendations about the importance of improved product design, reduced processing costs and increased use of remanufactured products based upon data on returns to manufacturers and service providers. This paper contributes to research by providing a framework of a digitized product life cycle integrated with the business process phases including remanufacturing and supported with real-world case studies for practitioners and academicians. The authors outlined potential future topics for academic researchers and practitioners, for expanding usage of digital tools in real-time predictive analytics to improve remanufacturing system’s efficiency and quality. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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35 pages, 934 KiB

Open AccessArticle

A Hybrid MCDM Model Combining DANP and PROMETHEE II Methods for the Assessment of Cybersecurity in Industry 4.0

by Witold Torbacki

Sustainability 2021, 13(16), 8833; https://doi.org/10.3390/su13168833 - 7 Aug 2021

Cited by 22 | Viewed by 3244

Abstract

IT technologies related to Industry 4.0 facilitate the implementation of the framework for sustainable manufacturing. At the same time, Industry 4.0 integrates IT processes and systems of production companies with IT solutions of cooperating companies that support a complete manufactured product life cycle. Thus, the implementation of sustainable manufacturing implies a rapid increase in interfaces between IT solutions of cooperating companies. This, in turn, raises concerns about security among manufacturing company executives. The lack of a recognized methodology supporting the decision-making process of choosing the right methods and means of cybersecurity is, in effect, a significant barrier to the development of sustainable manufacturing. As a result, the propagation of technologies in Industry 4.0 and the implementation of the sustainable manufacturing framework in companies are slowing down significantly. The main novelty of this article, addressing the above deficiencies, is the creation, using the combined DEMATEL and ANP (DANP) and PROMETHEE II methods, of a ranking of the proposed three groups of measures, seven dimensions and twenty criteria to be implemented in companies to ensure cybersecurity in Industry 4.0 and facilitate the implementation of the sustainable production principles. The contribution of Industry 4.0 components and the proposed cybersecurity scheme to achieve the Sustainable Development goals, reducing the carbon footprint of companies and introducing circular economy elements was also indicated. Using DANP and PROMETHEE II, it can be concluded that: (i) the major criterion of cybersecurity in companies is validation and maintaining electronic signatures and seals; (ii) the most crucial area of cybersecurity is network security; (iii) the most significant group of measures in this regard are technological measures. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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19 pages, 1401 KiB

Open AccessArticle

Industry 4.0 Accelerating Sustainable Manufacturing in the COVID-19 Era: Assessing the Readiness and Responsiveness of Italian Regions

by Dominique Lepore, Alessandra Micozzi and Francesca Spigarelli

Sustainability 2021, 13(5), 2670; https://doi.org/10.3390/su13052670 - 2 Mar 2021

Cited by 47 | Viewed by 5210

Abstract

An unpredictable shock hit the Italian economy in February 2020 when the spread of the COVID-19 virus began in Italy and other countries worldwide. In this context, Industry 4.0 (I4.0) technologies can be a fundamental tool for economic recovery by favouring the shift towards sustainable manufacturing. Therefore, it is necessary to measure the readiness of countries for I4.0 in order to guide policies in defining incentives to promote I4.0 and unlock its potential in the pandemic era. In this context, the paper aims to understand the readiness and responsiveness of the Italian Regions with respect to I4.0 concepts prior to the pandemic and identify best practices that are supporting companies in I4.0 adoption, with a focus on those incentivizing sustainable practices. An assessment framework before the pandemic is provided based on two dimensions: the readiness of firms to invest in I4.0 and favourable structural conditions. The assessment shows a group of alert regions as opposed to a group of unprepared, mostly linked Northern and Southern differences. Assuming that the “alert regions” are more likely to effectively manage and overcome the post- COVID-19 crisis, we provide a picture of how the Italian Regions have sought to encourage the adoption of digital technologies to improve resilience after the shock. The analysis shows that supporting measures mainly address Small and Medium-sized Enterprises. Furthermore, the tenders encouraging the adoption of I4.0 suggest that collaboration among stakeholders will become imperative. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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Review

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22 pages, 486 KiB

Open AccessReview

Systematic Literature Review on Dynamic Life Cycle Inventory: Towards Industry 4.0 Applications

by Simone Cornago, Yee Shee Tan, Carlo Brondi, Seeram Ramakrishna and Jonathan Sze Choong Low

Sustainability 2022, 14(11), 6464; https://doi.org/10.3390/su14116464 - 25 May 2022

Cited by 6 | Viewed by 2603

Abstract

Life cycle assessment (LCA) is a well-established methodology to quantify the environmental impacts of products, processes, and services. An advanced branch of this methodology, dynamic LCA, is increasingly used to reflect the variation in such potential impacts over time. The most common form of dynamic LCA focuses on the dynamism of the life cycle inventory (LCI) phase, which can be enabled by digital models or sensors for a continuous data collection. We adopt a systematic literature review with the aim to support practitioners looking to apply dynamic LCI, particularly in Industry 4.0 applications. We select 67 publications related to dynamic LCI studies to analyze their goal and scope phase and how the dynamic element is integrated in the studies. We describe and discuss methods and applications for dynamic LCI, particularly those involving continuous data collection. Electricity consumption and/or electricity technology mixes are the most used dynamic components in the LCI, with 39 publications in total. This interest can be explained by variability over time and the relevance of electricity consumption as a driver of environmental impacts. Finally, we highlight eight research gaps that, when successfully addressed, could benefit the diffusion and development of sound dynamic LCI studies. Full article

(This article belongs to the Special Issue Digital Transformation and Its Opportunities for Sustainable Manufacturing)

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