Digital twin supporting environmental performance evaluation according to ISO certification: an application case in the tire industry

ABSTRACT

The link between digital evolution and environmental sustainability is reshaping how companies enhance their processes, contributing to address circular manufacturing (CM). The extant literature does not explain how to improve the tire production process to limit environmental negative impacts, which are its most critical phases, which Industry 4.0 technologies could be exploited and how they could intervene in the process to facilitate effective data management. This research proposes a framework indicating how digital technologies could support tire producers in reducing the ecological footprint of their operations. The proposed framework addresses ISO 14,046 and 14,067 International Organization for Standardization (ISO) certifications. Digital twin (DT) was chosen as the most suitable technology. The related framework was further detailed according to data-driven CM principles, providing the set of sensors to be embedded on the production process and defining the data and information to be gathered through them to address the requested ISO certifications.

KEYWORDS:

• Tire production process
• digital technologies
• water consumption
• carbon footprint
• circular economy

1. Introduction

Technological developments have transformed how companies operate in many industries, opening wide opportunities to optimise production processes, improve product quality and reduce environmental impact (Porter & Heppelmann, 2014). In particular, the automotive and tire industries are experiencing constant growth, characterised by the search for efficiency and quality (Cozza et al., 2023). Approximately 2.35 billion tires are produced worldwide, with an expected increase to 10 billion annually by 2035 due to increased distribution and transportation (Tsai et al., 2022). The role of tyres is crucial both for movement and for a vehicle’s safety, serving a variety of purposes (e.g. bearing the weight of the vehicle and distributing the load to the surface (Zakrajsek & Mall, 2017), acting as vibration absorbers to improve road comfort and safety, and providing grip between the car and the pavement for braking and acceleration).

The fast expansion of the automotive industry is the main factor propelling the global tire market. The world’s need for passenger cars has increased due to factors such the growing population, fast urbanisation, and rising consumer spending power, particularly in emerging nations. In addition, the market is growing considerably faster than expected because of the growing demand for construction trucks brought on by the expansion of infrastructure projects. To enhance tire design and rubber quality, a number of top manufacturers are making significant investments in research and development (R&D) initiatives.

Growing awareness of environmental issues is driving companies to commit to reducing greenhouse gas emissions (Colangelo et al., 2023), using recyclables and adopting eco-sustainable production practices (Richardson et al., 2023). Araujo-Morera et al. (2021) analysed and detailed tire management considering the 7Rs approach (Redesign, Repair and Reuse, Recycle, Recover, Renew, Reduce) in the early stage of production, consumption stage, and post consumption stage. They also unveiled the need to both develop a widespread and systematized system for managing used tires, and to modify the paradigm to change end-of-life tires from waste to resource. However, in the early stage of production, the attention of researchers has been dedicated only to the optimization of innovative and experimental designs (i.e. the use of machine learning to classify steel for tire reinforcement (Cuartas et al., 2021)), neglecting the importance of the manufacturing process to cope with environmental challenges.

Tire production is one of the main industries causing negative consequences for the environment, with about 36.000 l of water and about 333 kg of CO₂ to produce a single tire (Piotrowska et al., 2019). These activities impact the environment, the consumption of natural resources (dealing with more than 80 raw materials (Abou-Ali & Khamis, 2003)) and, especially, emissions of harmful substances and waste production (Facchini et al., 2021). Associated air pollution poses a serious risk to human health, leading to respiratory, cardiac and even cancer problems (Katarzyna et al., 2020). It turns out that this industry is a key contributor in terms of negative impacts for most of the environmental planetary boundaries (Richardson et al., 2023). Therefore, it is urgent to enhance the related production process in terms of efficiency, materials consumption, and pollution and wastes production. So far, the extant literature does not explain how this process could be improved, which are its most critical phases, which type of Industry 4.0 technologies (Rüßmann et al., 2015) could be exploited to foster a more sustainable production and the adoption of Circular Economy (CE) practices in the entire organization.

In addition, it is also unclear how and where in the process these technologies could intervene to allow an effective tracking and monitoring of data and information to address both companies technical requirements and regulatory and standards’ limits (Shinohara et al., 2017). In this context, digital transformation offers innovative solutions to tackle complex environmental challenges (Chiappetta Jabbour et al., 2020) and ensure the achievement of ISO certifications, recognising the company’s commitment through standardised work.

Therefore, to address this gap, this research examines the link between digital transformation and CE in manufacturing in the specific industry of tyre production. Given the lack of extant literature on this domain in the tyre industry, authors considered as best practices the most effective implemented strategies and solutions applied in different industries (e.g. cement factory (Jena et al., 2020)) to support tyre producers to reduce the environmental impact of their processes and achieve International Organization for Standardization (ISO) certifications. Therefore, this research aims to propose a framework indicating how digital technologies could bolster tire producers in reducing the ecological footprint of their operations. In particular, the framework proposed addresses water consumption and carbon footprint ISO certifications (respectively ISO 14,046 and 14,067).

First, a scientific literature review (in a threefold research context: Industry 4.0, CE in manufacturing, and ISO certification) has been conducted and the practical requirements have been defined with a tire manufacturer (Company A). Based on them, two frameworks (one per each digital technology detected as suitable for the purpose of this research (i.e. DT and blockchain)) have been developed. Leveraging the expertise and experience of a consulting company (Consultant A), both have been submitted and discussed with Company A, leading to the selection of one technology (i.e. DT) as the most effective for their process. The selected framework has been further detailed according to the data-driven Circular Manufacturing paradigm (Acerbi et al., 2022, 2023), providing the set of sensors to be embedded on the production process and defining the data and information to be gathered through them to manage to address the ISO certifications related to water consumption and carbon footprint.

The paper is structured as follows. The research context is described in the Section 2, introducing Industry 4.0, CE in manufacturing, and the ISO certifications for water and carbon footprint. Section 3 depicts the methodology employed to develop the model based on the existing scientific knowledge. Sections 4 and 5 presented and discussed the results, reporting contributions to knowledge and practice, together with the managerial implications of the results achieved. Finally, Section 6 concludes the paper, specifying limitations and possibilities for further research.

2. Research context

2.1. Industry 4.0

The term Industry 4.0 became the reference paradigm of a new industrial revolution and goes beyond the simple introduction of automated systems in industry (Kagermann et al., 2011). The Boston Consulting Group has declined it into nine pillars (i.e. big data and analytics, simulation, additive manufacturing, Internet of Things (IoT), cloud computing, cybersecurity, augmented reality, horizontal and vertical system integration), each of which represents an enabling technology (Rüßmann et al., 2015). The current challenge is the integration of these enabling technologies to develop a single flow in the organizations’ processes, which would benefit in operational, organisational and strategic terms, starting from the plant (with the increase in productivity, flexibility, etc.) down to the entire supply chain (Roblek et al., 2016; Sassanelli et al., 2023).

However, the correct application of Industry 4.0 also requires overcoming obstacles and limitations to achieve the goal set, such as inadequate information on the potential of these technologies (Sassanelli, Rossi, et al., 2020), the lack of coherent infrastructures for data collection (Acerbi et al., 2024; De Carolis et al., 2017), legal uncertainties (Zhou et al., 2023) and, finally, the lack of clear and unambiguous standards (Cugno et al., 2021).

2.2. CE in manufacturing

The CE is commonly defined as a global economic model aimed at minimising the consumption of finite resources by focusing on the intelligent design of materials, products, and systems. It seeks to overcome the dominant linear economic model (i.e. take, make, and dispose), which is a traditional open-ended economy developed without an inherent tendency for recycling (The Ellen MacArthur Foundation, 2013; Kirchherr et al., 2017).

The traditional linear lifecycle of products (Ulrich & Eppinger, 2012) was replaced by closed-loop patterns practices (Bocken et al., 2016). The CE promotes the adoption of practices, such as Design for X approaches, that keep materials and products within the economic system for as long as possible (Sassanelli, Urbinati, et al., 2020). Consistent with this end, the CE can contribute to address current environmental challenges and create a more sustainable and resource-efficient future, mainly through the exploitation of Industry 4.0 technology employment (Chiappetta Jabbour et al., 2020; Rosa et al., 2020).

2.3. ISO certification

ISO is the most authoritative organisation in the field of defining technical standards that companies can adopt to establish effective and globally compliant management processes (ISO - International Organization for Standardization, 2023). ISO certifications represent a series of international standards to ensure that organisations meet certain universally recognised evaluation criteria. These standards are extremely numerous, each identified by a numerical code and a specific definition that indicates the business context it applies to. The adherence to ISO certifications is voluntary (Erauskin-Tolosa et al., 2020), despite the benefits associated with pursuing and implementing the specific guidelines for each standard are substantial, both within a single site and by expanding certification to all sites of the enterprise (ISO/TC, 2019). Figure 1 shows the number of ISO certifications annually released globally.

Figure 1. Number of ISO certificates and sites in 2021 adopted by the ISO survey (2022).

In particular, series 14,000 holds great importance because it leads companies, in line with Agenda’s 2030 requirements (ISO survey, 2022), along a path of reducing the environmental impact resulting from their activities, focusing particularly on emissions and water consumption (Ali et al., 2023).

2.3.1. ISO 14,046: the water footprint

ISO 14,046, titled ‘The Water Footprint’, is an international standard that provides detailed guidelines for assessing the water footprint of a product, process, or organisation. This standard focuses on defining the water footprint assessment system, identifying the stages of the product or process life cycle, quantifying water use at each stage, and analysing associated environmental impacts (ISO survey, 2022).

This is a valuable tool for organisations wishing to assess and manage water usage sustainably. The implementation of this standard led the organisations to identify areas with the highest environmental impact related to water usage and adopt measures to reduce the overall water footprint. This may include adopting more water-efficient technologies, optimising production processes and implementing water recycling and reuse practices.

2.3.2. ISO 14,067: the carbon footprint

ISO 14,067, titled ‘The Carbon Footprint of Products’, is an international standard that provides guidelines for assessing the carbon footprint of a product throughout its entire life cycle. The main purpose of this standard includes identifying the product life cycle stages, acquiring the necessary data to quantify greenhouse gas emissions at each stage and analysing the associated emissions. This provides organisations with a tool to assess and manage the impact of greenhouse gas emissions associated with their products and processes. The implementation of this standard led the organisations to identify areas of greatest environmental impact in terms of greenhouse gas emissions and adopt measures to reduce the overall carbon footprint. This may include adopting low-emission technologies, optimising production processes, promoting energy efficiency, and offsetting emissions through emission reduction projects or purchasing carbon credits.

3. Research methodology

To address the aim to investigate and assess which digital technologies could better support tire production companies in reducing the ecological footprint of their operations and obtaining 14,046 and 14,067 ISO certifications, a research process (summarised in Figure 2) has been defined and is described in the following sub-sections.

Figure 2. The research process, adapted by Sassanelli et al. (2019).

3.1. Conceptualisation phase

This phase is aimed to conceptualise the framework proposed to address the research scope. First, a systematic literature review has been conducted to investigate the state of the art, identify similar cases and appropriate technologies suitable to the research aim, and gather insights for planning the development of the proposed framework. Subsequently, the sample selected to collect the data and information to grasp practical requirements of this framework to be developed is presented. Finally, how the market analysis was performed to identify the differences and convergences between Company A and its main competitors is shown.

3.1.1. Systematic literature review

The systematic literature analysis was conducted to identify similar cases, also from other sectors, and to collect information and suggestions to support the planning of Company A’s strategy to provide a solid foundation of knowledge, information, and insights from the literature.

To get started, the searched topic keywords have been defined to identify all possible contributions available in scientific literature. The collection phase was carried out through research on the Scopus database in June 2023. Twelve keywords were selected (i.e. Industry 4.0, digital tech*, tire, ISO, footprint, optimise, production process, automotive, water footprint, carbon footprint, CM, and CE) and connected to achieve the desired results. In total, 667 articles were identified using 14 queries given by the combination of the selected keywords, as shown in Table 1.

Table 1. Queries performed on Scopus.

N	Searches by keywords	Results on Scopus
1	“Industry 4.0” OR “digital tech*” AND “tire”	28
2	“Industry 4.0” OR “digital tech*” AND “ISO”	261
3	“Industry 4.0” OR “digital tech*” AND “water footprint”	1
4	“Industry 4.0” OR “digital tech*” AND “carbon footprint”	93
5	“Industry 4.0” OR “digital tech*” AND “production process” AND “optimise”	100
6	“Industry 4.0” OR “digital tech*” AND “tire production process”	1
7	“circular manufacturing” OR “digital tech*” AND “tire”	15
8	“circular economy” AND “tire” AND “digital tech*” OR “Industry 4.0”	0
9	“digital tech*” AND “production process” AND “optimise”	24
10	“digital tech*” AND “production process” AND “industry 4.0”	77
11	“digital tech*” AND “production process” AND “automotive”	10
12	“digital tech*” AND “industry 4.0” AND “automotive”	36
13	“digital tech*” OR “industry 4.0” AND “automotive” AND “ISO”	15
14	“digital tech*” OR “industry 4.0” AND “automotive” AND “footprint”	6
Total		667

Subsequently, the evaluation phase was conducted, and no restrictions were imposed on the year of publication or the type of publication. An analysis was carried out to eliminate redundancies in the sample collected, reducing the number of articles to 525. Then, two further selections (first on title, abstract and keywords and then on the entire manuscript) were conducted to identify the articles dealing with the adoption of Industry 4.0 technology to enhance the environmental performance of tires production process, reducing the total number of articles to 181 and 87, respectively.

Among the selected articles, a preliminary evaluation of the full articles led to exclude 37 papers since they were considered not consistent with the objective of this research. Thus, 50 articles were collected (Figure 3) for the third stage of the systematic literature review (i.e. the analysis). A descriptive analysis led to classify the articles based on the nationality of the first author, year, type of research (divided into Theoretical analysis, Practical cases, and Analytical analyses), industry, and journal.

Figure 3. Literature review process.

The Sort, Label, Integrate and Prioritise (SLIP) method (Maeda, 2006; Sassanelli, Urbinati, et al., 2020) was adopted to detect and group the contributions selected. The most common themes became the reference categories of the articles within which they were classified. The entire process of selection and examination of the articles was carried out by two researchers. Results were compared and then reviewed by an academic expert in the research domain to avoid the bias of the analysis throughout the examination.

3.1.2. The selected sample

The company involved in this research operates in the automotive sector, particularly in the tire industry, characterised by intense competition and in which three major companies in the world are identified as ‘Company A’, ‘Company B’ and ‘Company C’ for confidentiality reasons.

Companies B and C were benchmarked to identify points of convergence and divergence with Company A. Company B has 75 plants and 16 technology centres, while Company C has 123 plants and 9 technology centres. Both are involved in producing tires for all types of vehicles, including farm machinery and aircraft. The data and information characterising them, used in the market analysis, have been identified as secondary data. They have been identified by considering the online verified documentation consultation. Therefore, the staff of these companies has not been directly involved in the research project.

The company directly involved in this research is an international group (Company A) specialised in producing innovative tires for cars, motorcycles and bicycles that currently owns 20 production plants and 10 technology centres distributed around the world. The information and characteristics of the group reported were obtained through 10 meetings held within a month with an Italian manager of the company’s R&D area. These meetings aimed to define the current configuration of the company’s production process, identify its specific requirements, and assess the initial challenges. The primary data have been collected using a specific protocol detailed in Annex 1. In this step, valuable elements for the analysis have been provided by an Italian digital consulting and services company (Consultant A) supporting Company A in IT solutions. Several meetings were organised with their associate managers and solution architects to evaluate the possible collaboration and adequacy of the skills and services offered according to the needs expressed by Company A, using a specific protocol detailed in Annex 2.

3.1.3. Market analysis

The market analysis was conducted to provide a detailed view of the target market (i.e. tires for the automotive industry). The main purpose was to assess the competitiveness and innovation level of Company A. This step allowed to identify the technological context in which the company operates and to assess the distinctive features and potential beneficial applications. The data collection was carried out using the companies’ annual reports and examining and verifying for Company A the information on the specific plant’s technologies. Particular attention was paid to suitable and relevant technologies detected from literature analysis as those more able to focus on monitoring and reducing environmental impact. In addition, the status of CE projects and their implementations was verified.

Through this in-depth market analysis, it was possible to gain a complete view of both the competitive landscape and the key technologies adopted by the main competitors. This provided a solid knowledge base, useful for identifying opportunities for improvement and developing innovative strategies for Company A.

3.2. Development phase

The meetings with Company A and the questions reported in Annex 1 allowed to identify the needs and characteristics relevant to planning the most effective strategy. Starting from the results of the literature analysis combined with the as-is configuration of Company A’s production process, a twofold framework, each one focused on a specific technology, blockchain and DT, has been defined with the support of Consultant A. The two proposed strategies have been defined considering the needs and characteristics that emerged from the interaction with Company A, as well as the analysis of the production process and the literature review.

The first recommended strategy consists of blockchain technology implementation. This approach meets the company’s needs, recognising the importance of interaction with its upstream and downstream supply chain. The framework shows the hypothetical functioning of the blockchain, highlighting the crucial information regarding the environmental impacts at each stage, the interactions between them and the possibility of creating a passport of reference in collaboration with other actors.

The second recommended strategy consists of DT implementation. The reference framework has been proposed as the result of three distinct phases: 3D modelling of the production process, identification of the sensors needed for data collection, and integration of the platform with other existing solutions.

3.3. Validation phase

During the research period, which lasted for two months (from April to May 2023), several interviews were conducted with Company A and Consultant A. Seven interviews with the plant manager and lead developer of Company A, and approximately five consultations were carried out with the software architect and the project manager of Consultant A. Two protocols were adopted, detailed in Annexes 3 and 4, respectively, to interview them and to collect feedback and issue about the framework and the solution proposed.

4. Results

The results achieved have been analysed according to different perspectives. The first is focused on the classification, assessment, and description of the papers already published on the research topic. The second is focused on the results of the benchmarking conducted between Company A’ and its main competitors. The third aspect is focused on the results of strategies proposed based on the twofold framework consisting of Blockchain and DT technologies’ implementation.

4.1. Conceptualization phase

4.1.1. Systematic literature review: descriptive analysis

The 50 selected articles were analysed from different points of view to include common features before their categorisation. For the year of publication, as shown in Figure 4, there are recent articles from 2017 to 2023, with a peak of publications in 2022, outlining how the themes sought are also relatively recent in literary research.

Figure 4. Historical publication trend by year.

Analysing the nationality of the first author, the main articles were written by Italian, German, and Russian authors, with 6, 5 and 4 reference articles, respectively (Figure 5).

Figure 5. Publishing countries.

The articles have been classified according to three categories (Figure 6): ‘theoretical analysis’, including 30 articles with literature review and frameworks; ‘practical cases’, concerning 14 papers focused on application and study cases; and ‘analytical analyses’, including 6 articles relating to surveys or statistical analyses.

Figure 6. Articles categorisation.

Most articles are focused on the automotive industry (Figure 7(a)), and around 70% were published in international journals (Figure 7(b)).

Figure 7. Classification according to business area (a) and article type (b).

4.1.2. Systematic literature review results

Four categories have been identified (Figure 8) to cluster the articles selected according to common issues in the research context analysed:

1. Digital transformation barriers & advantages: in this sample are included 10 papers addressing digital transformation’s positive and negative aspects.

2. Quality-driven digital economy: in this sample are included 8 papers dealing with the CE in terms of waste and quality.

3. Green and digital: in this sample are included 10 papers relating to the parallelism between digital transformation and sustainability.

4. Smart Eco-optimization: in this sample are included 22 papers related to process optimisation and monitoring through smart devices, of which 10 papers are more focused on sustainability aspects, such as energy and consumption.

Figure 8. Research categorization framework.

1. Digital transformation barriers & advantages

The first cluster (i.e. Digital transformation barriers & advantages) provides an outlook on digital transformations, including challenges, but also offers tangible benefits due to these kinds of innovations in different sectors, such as the automotive industry, agriculture with an increase in crop productivity (Zolkin et al., 2021) and the steel industry (Branca et al., 2020). According to Zolkin et al., the low adoption of digital technologies in agriculture depends on economic barriers and the technical complexity of digital systems, requiring highly skilled workers. Although limits can be changed according to the target market, the authors claim these barriers are common to all sectors and globally (Zolkin et al. (2021).

With regard to highly skilled workers, Zimmermann et al. (2019) highlighted the resistance to change and acceptance of Industry 4.0 technologies. Many recommendations to address these limitations have been provided, including transparency and user engagement, training, and support to understand the benefits and to overcome privacy and security concerns. To this concern, training is considered the most effective strategy to improve the plant’s adaptability to the digital transformation process (Branca et al., 2020). Although it may lead to job polarisation, with a reduction in intermediate-level jobs and a deskilling of the labour force.

Another critical aspect concerns the quality of the data collected as a primary source for analysis and to make the best decisions. The huge amount of data from different sources is a challenge but also a necessity. Perez-Castillo et al. (2018) proposed an approach based on ISO/IEC 25,000 and ISO 8000 standards for data management in connected intelligent products. They identified 23 best practices to address the challenges of data acquisition, processing, and usage, particularly for the IoT. Santos et al. (2020) also identified the barriers related to the lack of data connectivity and the appropriate use of data, in line with the authors above.

Digitalisation has a significant impact on organisational performance in terms of operational efficiency, flexibility, responsiveness to customer needs and product quality, as well as reducing production costs and increasing profitability (Calış Duman & Akdemir, 2021). Branca et al. (2020) also pointed out four key elements for the successful implementation of digital transformation: digital data, automation, connectivity and customer access. Digital transformation thus influences business integration, competitiveness and direct customer dialogue (i.e. transform a factory into a smart factory)(Orellana & Torres, 2019), making a significant contribution to reducing human errors and increasing Overall Equipment Effectiveness (OEE).

In particular, digital transformation has a major impact on the automotive industry’s relationship between manufacturers and suppliers. The use of digital technologies and product-related services enables a stronger relationship. It increases the resilience of the manufacturing ecosystem (Jankovic-Zugic et al., 2023) but also requires (Shinohara et al., 2017) adequate infrastructure, staff training, technical support, system and tool integration. Digitisation not only improves efficiency but also contributes to sustainability by reducing environmental impact and total investments, both for existing factories and for new products (Alptekin et al., 2021), allowing the faster entry of new players in the automotive sector, redefining the concept of ‘factory’.

• (b) Quality-driven digital economy

The second cluster (i.e. Quality-driven digital economy) is focused on innovative strategies to reduce waste and maximise the use of resources according to a CE approach. This can be achieved by exploiting digital technologies and adopting Component Business Models (CBM) (Lacy et al., 2016), allowing a balance between economic development and environmental protection. The Resource Recovery CBM was investigated to identify the benefits of 3D printing, DT and IoT technologies in achieving carbon footprint reduction goals and a low environmental impact (Islam et al., 2022).

Similarly, the use of structured methodologies such as Lean 6S, together with these technologies, would provide great support for obtaining zero-defect products (Jiménez et al., 2021). Quality management and traceability are essential to reduce product and process defects. In this regard, Sousa et al. (2022) developed a new framework based on IEC 62,264 for Quality Operations Management (QOM) and an interface to receive and send information, allowing tracking and assessment of the production performance in the ERP environment.

Regarding the automotive industry, several articles have focused on approaches, technologies, and techniques that would positively impact product quality, generating a positive effect on the environment. For instance, IoT is used to detect tire defects (Massaro et al., 2019), to extend the product’s life and to act promptly on the defects. Consistent with this end, systems with artificial neural networks have been tested in tire work environments (Massaro et al., 2020). Shakenov et al. (2022) showed that the probability of early failure of Off The Road (OTR) tires is high, with negative consequences on the environment, wildlife and costs. To this concern, recycling and reusing tires, whether defective tires during the production process or end-of-life tires, are important for reducing carbon emissions (Tsai et al., 2022) despite only 10% of the more than one billion end-of-life tires are currently recycled. So, a new circular rubber production model to reduce rubber waste and optimise resource use was proposed by Yin et al. (2021).

• (c) Green and digital

The third cluster (i.e. Green and digital) is focused on the digital technologies’ benefits from an environmental perspective. Several authors found a positive correlation between the implementation of technologies and sustainability and energy and environmental management systems (EN ISO 50,001 and EN ISO 14,001) (Medojevic et al., 1983). This correlation is particularly important in terms of competitiveness (Javaid et al., 2022). It would increase the value of company assets in terms of commercial and environmental performance (Hübner et al., 2022).

The survey discussed by Schöggl et al. (2023) reports that the most implemented technologies to achieve sustainability goals are IoT, followed by AI, especially in the construction sector. Although DT is still underused, it is considered a technology with the highest potential (Golovina et al., 2020), while currently, there are very few applications of blockchain implementation (Upadhyay et al., 2021). The application of Abdullah and Dr Murat (2019) on Banbury is one of the few examples of blockchain implementation in tire manufacturing. The authors proved significant improvements in terms of materials and energy saving to produce a tire. To assess and predict the impact of digital technologies on the company, 11 sustainability tools have been introduced in de Freitas et al. (2021), including Ethos indicators, GM Metric for Sustainable Manufacturing, and ISO 14,031 environmental performance standards. These tools can support the companies during the implementation of Industry 4.0 technologies.

If, on the one hand, the implementation of smart technologies led to reducing CO₂ emissions, on the other hand, the emissions due to their production and implementation require a careful evaluation. The negative impacts may outweigh the benefits, especially if the implementation is for the nominal use of individual users. Delanoë et al. (2023) suggested focusing on percentage reduction rather than absolute emissions to assess the efficiency of technologies, as proved in many case studies where there was an unfavourable balance between CO₂-produced and CO₂-saved for AI implementation. However, a structured framework for evaluating CO₂ emissions from digitisation is lacking to promote sustainable growth. A partnership between companies, governments, and institutions could create neutral digital systems that solve this problem, as argued by Patsavellas and Salonitis (2019).

• (d) Smart eco-optimization

The fourth cluster (i.e. Smart Eco – optimization) concerns the application of the related technologies to the production processes, focusing on two overlapping directions: advanced tools for optimising the production chain and specific technologies for sustainable production (Branca et al., 2020). Regarding process optimisation, Chernoded et al. (2022) proposed the use of Artificial Intelligence (AI) to identify the factors that most affect production, providing support for managerial decisions. Torres (2022) addressed a vehicle routing problem in the mining industry; consistent with this end, the author proposes a digital tool to reduce the transport routes aiming to decrease the emissions due to transport routes in the extraction operations. A similar approach was adopted to improve the under-fitting production of a metal frame, reducing the travel distance and human errors in order to adapt the production parameters in response to changing conditions (Stevanov et al., 2022).

Regarding DT, Eirinakis et al. (2022) developed a framework to support resilience in industrial production, making it possible to identify and manage anomalies or disruptive events. This technology has been applied in several industries (i.e. petroleum refineries, automotive electronics, and the textile industry). However, few protocols are available to standardise formats and data exchange (Lattanzi et al., 2021). Anderl et al. (2021) proposed the application of Standard for the Exchange of Product Model Data (STEP) to three case studies with different testing of control strategies and data acquisition for process control. The results proved STEP’s effectiveness in increasing production processes’ performance. Further case studies including the application of DT, such as the treatment of engine blocks (Sujová et al., 2023), the battery cell (Kampker et al., 2023), the production of hand carts (Finke et al., 2023) proved the capability of this technology to support and optimise the process in production terms. In agriculture, Howard et al. (2020) and Howard et al. (2020) applied technology to greenhouses, providing decision support to optimise product quality and manage production timelines. The RFID technology was applied to identify the tires’ location to enhance the logistics and process stages in tire disposal (Caccami et al., 2019). Margherita and Braccini (2020) highlighted how smart technologies can support the organisation, generating value in different flexible productions.

Regarding the technologies for sustainable production, generally, their application starts with the Sustainable Value Stream Mapping (Phuong & Guidat, 2018) followed by an assessment of key indicators required to predict the potential for environmental benefits (Zoubek et al., 2021). Consistent with this approach, the AI system was implemented in open pit mines to monitor the energy consumption and the quality of the electricity network in compliance with ISO 50,001 (Laayati et al., 2022). Yu et al. (2022) proposed an energy digital twin (EDT) to monitor carbon emissions. Similarly, Kovalyov (2022) developed a DT-based Distributed Energy Resources (DER) management platform. A cloud-based energy system to monitor in real-time the production line consumption data in accordance with DIN EN ISO 50,001 was presented by Javied et al. (2018). The integration of this system with other components, such as industrial networks and terminals, in a cement factory led to a reduction in waste, carbon emissions, and water consumption of 12.79%, 9.33%, and 3.12%, respectively (Jena et al., 2020). Elbadawi et al. (2023) highlighted the advantages in terms of product quality and environmental impact of 3D printing technology compared to traditional methods. Similarly, the application of blockchain in the textile and clothing sector allowed the accounting and traceability of the carbon footprints due to the company’s industrial processes (Chen et al., 2022).

4.1.3. The configuration of the as-is production process of company A

A prominent article identified in the literature analysis describes a case of digital technologies application in the battery cells context. Showing the potential of digital replicas of products, Kampker et al. (2023) developed a reference framework to identify the correlations and the functioning of the reference technology (i.e. DT) within the production process, as summarised in Figure 9.

Figure 9. Reference framework for DT adapted by Kampker et al. (2023).

Consistent with this approach, an interview, using the questions detailed in Annex 1, was conducted in this research to collect the information needed to identify the current configuration of Company A. As a result, the tire production process consists of 5 different phases:

1. Mixing: the raw materials are mixed chemically into a machine called ‘Banbury’ in specific proportions to obtain the desired compound. Then, the extruder processes the compound, and another machine performs adhesive and cooling action to get a roll from the compound.

2. Semi-finishing: the compound is combined with other materials to create all the necessary layers. The machining operation occurs on different machines: the calender realises the liner, rubberised metallic and textile fabric. The extruder realised the tread and sidewall, and the operator realised the beads.

3. Building: the layers produced in the previous step are assembled to realise the final product. A packaging machine superimposes the layers in sequence to realise the so-called ‘raw’ tire. Additional layers were adopted to increase the tire resistance.

4. Curing: a curing press bonds together all the layers and gives the final shape and resistance to the product.

5. Finishing: it’s the last phase of the tire production process, during which the product is completed, and several operations are performed to ensure the quality, aesthetic appearance, and performance of the tire, such as the elimination of any imperfection present on the tire surface.

Therefore, the process’s most critical and relevant phases are mixing and curing in terms of quality and environmental performance. Both operate at high temperatures and pressures, significantly impacting consumption on the production process and quality of the product. A different dosage or mix, as well as an inadequate vulcanisation, would directly affect the finished product’s physical, chemical, and structural properties. This means that further actions are needed to improve environmental performance in achieving key ISO standards by digital technologies.

4.1.4. The market analysis

Company A stands out for its high competitiveness and attention to emerging technologies. To manage production and related activities, such as maintenance, the company makes use of several IT tools and systems that play a key role in improving efficiency, quality, and traceability. It allows the complete management of the production system, the use of the SAP application, especially for the management of raw materials and the finished product and the adoption of several tools, like computerized maintenance management system (CMMS). Production management was conducted according to the lean perspective, exploiting Kanban cards and tracing the tires using a barcode along the production process.

Regarding emerging technologies, the application varies according to the plant under consideration. There is a strong push towards convergence between Information Technology (IT) and Operational Technology (OT). The objective is integrating and converging the several systems available for a more complete management.

Currently, the company is focusing on data security validation and information protection as a top priority to prevent threats, but there is an interest in innovation and in the use of technologies such as AI and the Industrial Internet of Things (IIoT). Regarding DT and 3D printing, there is no relevant information about their use and application for operations and logistics, except for the use of the DT for staff training purposes.

According to environmental impact and CE practices, the collected data suggested that the company generates approximately 550 ktonCO₂eq of annual emissions, mainly due to steam production for vulcanisers. In addition, energy consumption is around 11,000,000 GJ, while water consumption reaches about 6,000,000 m³, where 90% is used directly in production. In particular, the analysis of the production process has shown that the mixing and curing phases contribute to the most significant environmental impact: 30% of the water consumption is due to the mixing phase and 20% to the curing phase, while 20% of the emissions depend on mixing phase and 50% to the curing phase. The strategies adopted are consistent with the suggestions provided by Katarzyna et al. (2020): Company A has a water loop system in several plants, and it uses about 4% of recycled raw materials from abandoned tires (mainly carbon black), but it’s also exploring the use of silicon from rice waste. Although the consumptions are monitored and reported in sustainability articles, there is still no standardisation according to ISO 14,046 and 14,067.

The comparative analysis carried out on the three companies (Company A, B, and C) shows a marked focus on innovation and sustainability (detailed in Annex 5). Consistent with the objectives of the Agenda 2030 (United Nations, 2015) and the need to reduce emissions and consumption, all three companies are actively engaged in research and development activities. A common point among them is the commitment to the CE. They are involved in projects to recover used tires, obtaining carbon black and pyrolytic oil that was reused exclusively by Company B. In addition, Company C, considering the versatility of the rubber, has agreements with other companies for external uses, such as in the field of sports.

Several emerging technologies have been identified to be embedded on the product itself to enhance its lifecycle performance, and most of them are still in the experimental stage. All three companies use sensors on top-of-the-range tires to monitor physical conditions and transmit data to the onboard system. However, the use of RFID technology is still being evaluated or limited for companies A and B; on the contrary, company C has planned to implement it fully by 2024. All the companies adopt AI algorithms. Company C stands out as the most audacious in terms of technological innovation, launching several experimental programs linked to blockchain and 3D printing to produce tire parts. In addition, DT technology was used for several years to test product alternatives before their actual implementation. Companies A and B, on the other hand, are at an early stage but are developing into the implementation of emerging technologies. There is no information on using 3D printing and DT for these two companies.

Therefore, there is a clear trend towards innovation and the adoption of advanced technologies, stimulated by new environmental regulations and the desire to grow and gain a competitive advantage.

4.2. Development phase: the twofold framework

A twofold framework, based on Blockchain and DT technologies and grounded on the results coming from the conceptualisation phase, was proposed to Company A.

4.2.1. The blockchain framework

Chen et al. (2022) applied blockchain technology in the production process in the clothing industry to ensure a close connection in the supply chain. Similarly, the need for a relationship between a focal company and supplier along the supply chain in the automotive sector was described by Jankovic-Zugic et al. (2023). The idea consists of using the blockchain platform (provided by Consultant A) to develop a data structure in which all the information, deemed valuable on the batch in production, is collected. In other words, each block includes transactions or data and a cryptographic link to the previous block to keep complete records of the production process, verify the integrity of data, and quickly identify any problem. The encryption’s goal is also to solve governance and data breach problems (Morrow & Zarrebini, 2019).

The proposed framework focuses on the supply and distribution phase to create continuity and increase the amount of important data in the distributed register. In particular, the traceability of raw materials allows data collection based on the origin, quality and characteristics of the materials included in the tire compound. The use of this technology in the distribution part allows the management of information related to the warranty or impact on the use of the tire (including the set of services provided in this phase, such as installation and maintenance) to have an accurate investigation of tires’ life cycle tracking.

The shareable information to be collected related to environmental impacts during production process can be:

• Mixing: percentage of raw material used, water consumption, and carbon footprint. Quality data and testing analysis conducted.

• Semi-finishing: percentage of textile and metals used and carbon footprint.

• Building: tissue alignment.

• Curing: percentage of water consumption and carbon footprint. Tire size and shape. Testing and analysis conducted.

• Finishing: weight and thickness, model name, test and analysis conducted.

The platform managed the data according to flow information shown in Figure 10, aiming to develop a secure and connected register, which allows the consultation of transparent and unchangeable information data on emissions generated and water consumption. Blockchain allows the reliable sharing of information about environmental performance with other actors to facilitate compliance with the ISO 14,067 and 14,046 certification requirements.

Figure 10. Blockchain framework.

4.2.2. The DT framework

The second technology assessed consists of DT application in the tire production process. In the scientific literature, there is not a single definition for DT (Anderl et al., 2021; Golovina et al., 2020). Therefore, the DT of the proposed strategy consists of a software reproduction of a physical object (3D model) that allows the modelling of the internal processes, technical characteristics (Tao et al., 2019) and behaviours of the real object under given conditions. The functionality of the proposed technology ensures the instant monitoring (like on smart vehicle (Bhatti et al., 2021; Dai & Zhang, 2022; Magargle et al., 2017)) and simulations of the virtual object from the historical data collected. The three distinct phases (i.e. virtual design, monitoring, collection, and analysis) have enabled the realisation of the reported framework.

The virtual design phase consists of modelling and simulation of all production stages. This allows to optimise the layout, test different configurations, and identify potential problems or inefficiencies before implementing them. The virtual 3D model is an example of how the production process could be virtually visualised. The monitoring phase allowed to identify the sensors present, and not, on the machines and on the line and then integrate them into the DT. Sensors provide real-time information on the operational variables of the process and an accurate view of the operating conditions and processes of the machine. This information is essential for performance simulation and analysis. The needed sensors for quantifying water consumption and carbon emissions according to ISO 14,046 and 14,067 are classified according to the single production phases (Figure 11):

• Mixing: CO₂ gas sensor, humidity sensor, water consumption sensor, temperature sensor,

• Semi-finishing: CO₂ gas sensors,

• Building: temperature sensor, pressure sensor,

• Curing: temperature sensor, water consumption sensor, pressure sensor, humidity sensor, CO₂ gas sensor,

• Finishing: vision system.

Figure 11. The 3D model with sensors in each phase.

The quantity of higher sensors in the mixing and vulcanisation phase derives from the need to monitor their impact more accurately in the production process and evaluate the savings in water consumption due to adopting a water loop system.

In the collection and analysis phase, the data identified are supposed to be collected and elaborated by a reference dashboard, allowing the verification of the current trend in real-time and a simulation section to verify how to modify the current setting parameters to improve the results achieved without affecting the quality of the product. The dashboard (to be developed and implemented by Company A with the support of Consultant A to carry on the digitalization of its production process) has been conceptualized in this way. It should allow operators to focus either on one of the phases of the production process (i.e. mixing, semi-finishing, building, curing, finishing) or to perform a comparison among them (also giving the possibility of simulating the system in which tests could be performed to look for better operating parameters). The value of the different parameters tracked by the sensors installed on the system should be available on-time and exploitable to perform gap analyses between the real system and the DT. Some of the possible initial building blocks composing the dashboard could be: pressure sensors OPB series (measuring volume and service level), water consumption level (reporting volume and service level), total CO₂ emission and comparison among timeframes, steam level, and sensors monitoring the curing phase (e.g. PT100 RTD temperature sensor, FGB Strain sensor, HS1101 humidity sensor and ML3 ThetaProbe soil moisture sensor, CO₂ gas sensor, water consumption sensor).

In general, the application of the DT in the tire manufacturing process offers a wide range of possibilities. It can be customised to the company’s specific needs with respect to environmental impacts. In other words, an accurate and real-time virtual replication of the process was developed to optimise operations, improve quality, and ensure efficient and competitive production. The final reference framework for applying the proposed DT is shown in Figure 12.

Figure 12. Reference framework for DT.

4.3. Validation: the twofold blockchain and DT framework

A series of meetings with Company A and Consultant A allowed to discuss and validate the two frameworks. Regarding Company A, the managers interviewed discarded the first framework, based on blockchain, due to the main barrier identified (i.e. lack of trust in sharing the data obtained (Abou-Ali & Khamis, 2003; Upadhyay et al., 2021). On the contrary, the second framework based on the DT was well received, thanks to the company’s familiarity with this technology and the use of DT in some plants for training purposes. The analysed frameworks were considered suitable to the current challenges faced by the company and capable of supporting decisions and choices, especially in the field of research and development. The only concern with their implementation was the timing needed to address the ISO requirements for the certifications considered.

According to a technical evaluation conducted by Consultant A, both frameworks are highly adaptable and editable to meet the specific requirements of customers and the structures in which they are applied. The main constraint to DT framework implementation depends on the presence of obsolete machinery, requiring a preliminary assessment and retrofitting to ensure real-time monitoring.

5. Discussion

The results achieved showed that the degree of interconnection and development of each company depends on the technological barriers and limits, as well as on the specific characteristics of the related sector. The correct and efficient evolution of an interconnected system requires the acceptance of individuals, data protection security, and the actors’ reliability, confidence, and commitment in the supply chain. Through the employment of Industry 4.0 technologies such as blockchain and DT, allowing the monitoring and analysis of data and information related to the production process, this study could also support companies to directly involve all the potential stakeholders in circular business models (Dallasega et al., 2018). Indeed, the final scope of the developed frameworks is not only to address the environmental constraints provided by ISO standards but also to trigger knowledge sharing and collaborative dynamics fostering the adoption of CE paradigm practices.

The digital transformation is positively related to sustainability. Technologies such as AI, DT, IoT and blockchain offer flexibility, customisation, and adaptability, enabling process monitoring and optimisation. These technologies identify elements, phases or characteristics that mainly affect the production line’s performance, consumption, and emissions, favouring and strengthening relationships and sharing along the entire supply chain. The smart technology is a strategic element to improve the company’s competitiveness, paying particular attention to issues of sustainability and CE, as demonstrated by the comparison between Companies A, B, and C.

However, digital transformations do not always require the use of innovative technologies but depend on the needs and specifications of each case. Generally, their introduction requires a trade-off between the benefits achieved, the costs of the investment and the changes needed. The analysis proved that there are numerous case studies related to the application of innovative technologies for process optimisation and sustainable monitoring. The most relevant technologies to ensure sustainable monitoring are DT and blockchain since the former can simulate situations without involving problems or waste, while the second encourages a perspective that considers the entire lifecycle of the product instead of focusing on a single phase. In general, digital technology is redefining the concept of industrialisation, promoting lean systems that adapt to significant changes in layout and basic structure. However, the shortage of articles about ISO certifications (14046 and 14,067) did not allow for more in-depth analysis to understand better how to get the requirements in practice and help companies along the way.

In addition, during the research case, meetings with managers and technology architects from Company A and Consultant A revealed numerous concerns. The implementation of the proposed frameworks brings several constraints and factors that present additional challenges, particularly regarding the proper collection and management of data. On the other side, they also offer several benefits to Company A, including improved product quality, cost reduction, and increased profitability.

To achieve these results, a close and direct collaboration between Consultant A and Company A is crucial also in the future. Brainstorming sessions and in-depth meetings are needed to perform a comprehensive analysis of the company’s current systems and to go beyond the theoretical analysis carried out within this research (representing only a part of the operating plants of Company A’s group, characterized by a highly automated process). This decision-making approach aligns the specific needs and requirements of the Company A, using and exploiting Consultant A skills, resources, and support. Collaboration, in this perspective, becomes a dual-growth approach that yields benefits for both the actors involved in the relation. On the one hand, it creates a path that ensures to Company A the achievement of its objectives, on the other hand, it fosters professional growth and technical specialization to Consultant A.

The case analysed on Company A contributes to the list of practical adoption of innovative technologies, bringing a new contribution to the tire sector. The identified solutions, such as DT and blockchain, are consistent with literature analysis. However, there are no case studies related to the tire industry that envisage its application; this research is the first in this specific industry. The only similar case study was presented by Abdullah and Dr Murat (2019), focusing on blockchain implementation in tire manufacturing but referred to the production process’s start phases (i.e. mixing).

The implementation of the twofold framework proposed with this research offers benefits such as traceability, transparency, and data validation, promoting a more efficient and responsible management of the environmental aspects of the production process. According to ISO 14,046 and ISO 14,067, this approach contributes to monitoring and quantifying water consumption and greenhouse gas emissions, respectively. It has to be said that integrating DT and blockchain technologies with existing MRP and ERP systems would strongly improve corporate adhesion, functionality, and overall performance, leading the company to increase the production line’s performance. At the same time, implementing together the two frameworks (and the related technologies) would raise new problems and lead to further planning of future steps. The limits imposed by the market in terms of competitiveness and professional secrecy are also confirmed in this research; their existence binds and hinders the digital transformation underway.

5.1. Contributions to knowledge and to practice, and managerial and policy implications

This research contributes with multiple results to both knowledge and practice, also providing managerial implications.

Concerning contribution to knowledge, this research systematizes the literature on the research domain of environmental performance evaluation, including Industry 4.0, CM and ISO certifications, with a focus on the tyre industry. It gathers the selected contributions in four main categories (i.e. Digital transformation barriers & advantages, Quality-driven digital economy, Green and Digital, Smart Eco-optimization) and provides a starting point for researchers willing to further analyse this research topic with analytical techniques or to apply the selected specific technologies in the tire industry based on the framework proposed. In addition, this research develops and proposes a twofold framework allowing clear and immediate visualisation of process and product information in the tire production process. The framework suggests two technologies (DT and blockchain) as particularly suitable for optimising and monitoring environmental impacts of the tire production process. In particular, the blockchain framework defines the key information to be shared along the supply chain to evaluate the environmental impact of the production process; while the DT framework defines the sensors to be installed in each production phase and a hypothetical reference dashboard through which to the impacts caused by the process could be monitored. The analysis of the literature (together with the market analysis and the application case) also suggested other promising technologies (AI, for optimizing and monitoring the environmental impacts, and RFID, for product monitoring and for easier product management and recovery) that could be integrated to further address the objective of this research in the tyre industry.

Concerning contributions to practice and managerial implications, the twofold framework, detailed per each technology considered (i.e. DT and blockchain), can represent for practitioners a reference starting point able to initiate them in effectively integrating these technologies into their production processes. The framework can be supportive also to address different types of ISO (and therefore to manage diverse flows of resources and energy involved in the process), providing a solid ground for future implementations and developments of digital technologies in the tire industry.

In particular, this research identifies the set of sensors useful for monitoring the production process, also proposing a hypothetical dashboard to be integrated with the framework for clear and intuitive visualization of relevant information. This practical tool, if implemented, would empower managers to make informed and strategic decisions to optimize their production operations, enhancing overall efficiency and sustainability.

Furthermore, given the tire industry’s relevance and its environmental impact, this research can bridge the gap between theoretical research and practical policymaking. Indeed, it can affect policymaker decisions by providing valuable insight into which technologies may be adopted to achieve environmental impact reduction goal, such as Net Zero goals. This could influence fund allocation and the definition of targeted actions to address environmental challenges in the specific industry.

6. Conclusions

This research aimed to investigate and assess innovative technologies able to support companies in reducing the ecological footprint of their operations and obtaining ISO certifications, such as 14,046 and 14,067. Consistent with this end, a research methodology has been designed to address this scope, leading to the development of a twofold framework detailing the technologies more suitable to be adopted (blockchain and DT). Among them, the DT was finally selected and for the related framework developed to support Company A, the sensors to be deployed, and the data to be gathered were also detailed.

The analysis revealed that the tire production process is beginning its digital transformation path. At the extant status, the industry is characterized by a limited deployment and employment of technological assets, not fully able to address sustainability commitments. For this purpose, literature suggested technologies such as AI, DT, IoT and blockchain to enhance production processes and assets in terms of flexibility, customisation, and adaptability, enabling process monitoring and optimisation. The study of Company A and of its competitors clarified that technology is useful and strategic for the company to strengthen its competitiveness. Together with the literature review analysis, the specific needs of Company A led to the development of a twofold framework that visually summarise all the needed characteristics related to the application of digital technologies in the tire production process. While the blockchain framework allows the collection and sharing in the value chain of data about the environmental impact of the production process, the DT framework instead adopts sensors useful for monitoring and a related dashboard to manage and improve the production system performance.

Thanks to the development and exploitation of these frameworks, blockchain and DT technologies could be practically leveraged to enable and support the active involvement of both internal and external users during all the phases of the production process. The use and the application of the proposed framework doesn’t exclude the possibility of integrating other technologies within the same project. Combining different technologies, the customer’s requirements can be met more effectively, in a more complete and high performing manner.

However, due to the distrust towards knowledge sharing enabled by the blockchain technology, the DT framework was finally selected to be actually employed in Company A’s production process with the final aim of supporting the achievement of the water and carbon footprint ISO standards. For this purpose, in this specific framework, the sensors to be deployed, and the data to be gathered were also detailed and represent a key result of this research.

Finally, the research has clarified elements that link technology to environmental monitoring, whose benefits go beyond the walls of the company involved but at the same time it is limited from several perspectives. Indeed, even if multiple results have been obtained with this research, several limitations have been detected, both in terms of the research method adopted and the research output obtained. First, the analysis directly involved only one specific company in the automotive tires industry (even if a benchmarking analysis was carried out with its main competitors). Moreover, the result achieved was generated at a company organisation macro level, without considering a particular reference plant. This research doesn’t provide detailed information or specific KPIs that could be useful for monitoring environmental impacts. At this purpose, descriptive statistics, correlation matrices, or other pertinent analytical techniques capable to delve deeper into the data would offer crucial insights into the relationships among the variables studied, thereby further bolstering the robustness of the study. Moreover, the analysis of the technologies useful for improving the product lifecycle performance under a CE perspective has not been challenged, since the focus of this research was the related production process.

The work carried out so far could serve as a starting point for the practical implementation of the technological solutions proposed in the specific industry. It would be interesting to include more detailed and quantitative analyses. First, a cost/benefits analysis would allow to consider the relationship between the benefits of the individual technology implemented and its related emissions. Second, the application of the research can be extended to other ISO certifications or environmental variables related to the tire industry to obtain a comprehensive vision about environmental dynamics connected. Third, through the interaction with the considered supply chain actors, eventual external needs or elements affecting the characteristics of the digitalized production system could be identified through appraisal of the suppliers. Finally, a gap analysis between the DT and the real production process should be conducted to understand how the company, based on the framework proposed, could control the water consumption and emissions and which remedial measures could be implemented by the company to cope with the gap detected.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3 - Call for tender No. 341 of 15/03/2022 of Italian Ministry of University and Research funded by the European Union– NextGenerationEU. Award Number: PE00000004, Concession Decree No. 1551 of 11/10/2022 adopted by the Italian Ministry of University and Research, CUP D93C22000920001, MICS (Made in Italy - Circular and Sustainable).This research work was partially supported also by the DESDEMONA project (DEcision Support system for the Diagnosis and Evaluation of the Maintenance OperatioNs Activities) of the Italian Ministry for Universities and Research MUR (Project PRIN – CUP D53D2301836 0001) funded by the European Union – NextGenerationEU, component M4C2, investment 1.1., by the RESILIENCE project, funded by the Italian Ministry of University and Research (MUR) (Project PRIN2022 – CUP D53D2301836 0001), and by the PlasmaPilot (“Flexible Ladle Preheating Procedures using Plasma Heated Refractory”) project (GA899223) funded the Research Fund for Coal and Steel (RFCS) of the European Commission.