Next Article in Journal
Study on Quality Measurement and Influencing Factors of Russian Wood Forest Products Imported from China under the Background of High-Quality Development
Next Article in Special Issue
Maritime Bilateral Connectivity Analysis for Sustainable Maritime Growth: Case of Morocco
Previous Article in Journal
The Impact of Renewable Electricity Output on Sustainability in the Context of Circular Economy: A Global Perspective
Previous Article in Special Issue
Life Cycle Assessment in the Agri-Food Supply Chain: Fresh Versus Semi-Finished Based Production Process
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Industry 4.0 Implementation Projects: The Cleaner Production Strategy—A Literature Review

by
Walter Cardoso Satyro
1,2,*,
Jose Celso Contador
3,
Sonia Francisca de Paula Monken
4,
Anderson Ferreira de Lima
2,
Gilberto Gomes Soares Junior
2,
Jansen Anderson Gomes
2,
João Victor Silva Neves
2,
José Roberto do Nascimento
2,
Josiane Lima de Araújo
2,
Eduardo de Siqueira Correa
2 and
Leandro Simplício Silva
1
1
Postgraduate Program in Project Management, Nove de Julho University (UNINOVE), São Paulo 01525-000, SP, Brazil
2
Postgraduate Program in Production Engineering, Nove de Julho University (UNINOVE), São Paulo 01525-000, SP, Brazil
3
Postgraduate Program in Administration, Paulista University (UNIP), São Paulo 04026-002, SP, Brazil
4
Faculty of Public Health, University of São Paulo (USP), São Paulo 01246-904, SP, Brazil
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2161; https://doi.org/10.3390/su15032161
Submission received: 26 December 2022 / Revised: 14 January 2023 / Accepted: 16 January 2023 / Published: 24 January 2023
(This article belongs to the Special Issue Cleaner Production in Contemporary Operations)

Abstract

:
The industrial impacts on the environment need to be minimized to reduce climate change, which will benefit human beings. Industry 4.0, the new production paradigm, promises productivity gains for companies that manage to implement it, but it is also dependent on natural resources, impacting the environment. The aim of this study is to identify and analyze possible cleaner production strategies associated with Industry 4.0 to optimize manufacturing systems in Industry 4.0 implementation projects, in addition to reducing the environmental impacts of these companies. Through a literature search, cleaner production strategies associated with Industry 4.0 were identified and classified into ten dimensions (strategy, waste, recycling, life cycle, resources, energy, production, work, performance and environment) contributing to the theory. The possibilities of using Industry 4.0 technologies were analyzed to meet each dimension. The relevance of this study lies in presenting possibilities for using and developing technologies and applications to meet these dimensions of cleaner production and helping those involved in Industry 4.0 projects to implement it more stably, contributing to the theory and practice.

1. Introduction

Industry 4.0, the new production paradigm, promises to improve the productivity of the companies that manage to implement it [1,2,3,4], but like other production paradigms, it is dependent on natural resources. Cleaner production strategies can be used to optimize or reduce the use of resources [5], representing a gain for the companies involved in Industry 4.0 implementation projects, which is the object of this study.
Cleaner production aims to increase the efficiency of production lines, reducing risk to people and to the environment, through the use of preventive environmental strategies for products, services and processes [5,6]. The adoption of cleaner production practices helps to preserve energy, water and raw materials, eliminating or reducing the emission of toxic material and residues in the production process [5,7]. Cleaner production strategies can also increase the energy efficiency of production lines by harnessing the residual heat generated by the operations, reducing energy consumption [8].
Despite the apparent complexity that cleaner production can represent initially, there are several ways to achieve cleaner production, such as by reducing the effects of greenhouse gases [9], reducing the volume of water discharged into the environment [10], minimizing water consumption [11,12] and using other methods.
For cleaner production to spread across all companies and countries, the involvement and support of government representatives and industrial decision-makers [13], universities [14], consultants and non-governmental organizations (NGO) [15,16], leaders and people in general is required. This joint effort could guide the establishment of public policies [17], regulating the emission limits of pollutants in the air, soil and water [5], in addition to stimulating the adoption of technical standards such as ISO 14000 [18,19], related to the protection and preservation of the environment, to prevent pollution and the potential problems that this can bring to the economy and society. It is also relevant that the government, banks and other financial institutions can provide financial incentives to encourage companies to adopt cleaner production [5], with privileged interest rates if possible.
Industry 4.0, the new industrial paradigm, has received much attention due to the possibility of improving the productivity of companies that can implement it [20]. In order to optimize the production process to increase productivity, Industry 4.0 uses high technology to integrate automation and information systems to exchange information and data between humans and machines [21,22].
Although Industry 4.0 can bring about opportunities for companies, the implementation process involves barriers and risks [1,2,3,4]. The adoption of a cleaner production strategy in the Industry 4.0 implementation process is defined as the use of cleaner production practices in production systems for the companies to reach the Sustainable Development Goals (SDGs) through this process [3].
To guide this implementation process, some models have been developed, but in most of these models cleaner production practices are not considered or mentioned. Few models consider cleaner production practices as essentials tool in the implementation of Industry 4.0 [3]. Shayganmehr et al. [23] proposed a model that sees Industry 4.0 as an instrument to strengthen the circular economy and cleaner production to increase the quality of the products or services available to the market. Amjad et al. [24] developed a model combining lean manufacturing, lean green manufacturing, the circular economy and Industry 4.0 to minimize waste and maximize production. Lu et al. [25] suggested that the environmental, legal, philanthropic, economic and ethical aspects should be analyzed at all phases of the Industry 4.0 implementation processes. Ma et al. [26] suggested a model to use Industry 4.0 technology to save energy costs; in a similar approach, Rajput and Singh [27] developed a model to reduce energy consumption with Industry 4.0, helping to reach cleaner production and circular economy goals. In some models, cleaner production is the antecedent, while in others it is the consequent. In these models, the cleaner production strategy is superficially addressed, a gap that this study intends to analyze. Therefore, the following research question was formulated.
RQ1: What are the possible cleaner production strategies associated with Industry 4.0 to optimize manufacturing systems in Industry 4.0 implementation projects?
Given that Industry 4.0 uses cutting-edge technologies to improve production, why not use these technologies to improve the cleaner production strategies as well? Thus, the following research question was formulated.
RQ2: How can Industry 4.0 technologies and applications be developed and used to meet these cleaner production strategies?
Using a literature search, cleaner production strategies associated with Industry 4.0 were identified and classified into ten dimensions, and Industry 4.0 technologies and applications are suggested for development and use to address these cleaner production strategies.
This study, which aims to contribute to cleaner production and to the Industry 4.0 body of knowledge, is divided into sections. After this introduction, Section 2 presents the literature review on Industry 4.0 and cleaner production. Section 3 discusses the methods used; Section 4 presents the dimensions of cleaner production strategies; and Section 5 addresses the conclusions, limitations and future study directions.

2. Literature Review

2.1. Industry 4.0

Although some authors question whether the evolution of industrial systems occurred by evolution or revolution [28,29], until now four industrial revolutions have been studied.
The first industrial revolution, or Industry 1.0, was possible with the use of steam power and the mechanization of the weaving loom around 1780, when industry managed to reduce the dependence on human physical strength, reaching new levels of productivity [3,30].
The second industrial revolution, or Industry 2.0, took place around 1870, due to the mass production; the division of labor; and the use of assembly lines, electricity [30,31] and steel mills, enabling the intensive use of steel.
The third industrial revolution or Industry 3.0 began in 1969, with the use of electronics, robotics, telecommunications and computing, enabling automation in production systems. The milestone was the emergence of the first programmable logic controller (PLC) [32,33].
The fourth industrial revolution or Industry 4.0 emerged in 2011, launched at the Hannover Fair, as part of a high-tech program by the German government with the aim of enhancing the competitiveness of German companies [34,35,36,37,38,39,40], based on three pillars: the Internet of Things (IoT), cyber–physical systems (CPS) and the Internet of Services (IoS) [2,21,41,42,43,44,45].
There are also concepts that support Industry 4.0, including horizontal integration, vertical integration, modular production, service orientation, virtual applications, real-time capabilities, interoperability, decentralized systems and virtual applications [46,47,48,49].
The integration of automation and information technologies is a pillar of Industry 4.0 [49,50], enabling information and data to be processed, monitored, controlled and analyzed in real time in order to increase operational efficiency [51,52,53,54,55], helping to manage production [56] and the entire company efficiently [57] and allowing better decision-making [58] with flexibility [59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80].
Supply chains can be restructured with Industry 4.0 to supply components and raw materials from different sources [33,81,82,83], allowing for better inventory control of work-in-process and finished goods [56,81,82], simplifying production planning and control [84,85,86,87,88,89,90] and assisting managerial functions and operations for the effective use of human resources [91].
For Industry 4.0, the core technology is the Internet, not the computer [92]. It is expected that by 2030, every economic person with Internet access will use digital data once every 18 s, or 5000 times a day [93,94].
Industry 4.0 can reduce costs, provide customized products and services to customers and increase sustainability and productivity [33,82,95], improving process and product quality [46,47,96], increasing production efficiency [2,3,43,45,49,82] and enabling mass customization [97].
Society is putting pressure on the private sector to become effective and efficient and to reduce environmental pollution and climate change, with Industry 4.0 being critical in this process [98], although it consumes more electricity than previous production paradigms.
The world economy has been affected by the difficulty of accessing reliable energy sources. Currently, approximately one-seventh of the people around the world still do not have access to electricity [99]. It is estimated that by 2030, the global demand for energy will increase by 30% [93].

2.2. Industry 4.0 Technologies

Industry 4.0 is an umbrella term that incorporates several technologies [100,101], some of which are presented below.
  • Cyber–physical systems
Through the integration of technologies, the cyber–physical systems (CPS) promote interdependencies and interconnections between networked cyber components and physical components [37,41]. CPS can be considered embedded systems that allow the exchange of data between humans and physical or mechanical systems, through software controlled by actuators, controllers, sensors and smart objects [41].
2.
Internet of Things
The Internet of Things (IoT) enables humans to interact with machines, mobile devices, sensors and actuators, supporting humans in their daily activities [28,102]. In IoT, objects are animated via computation, actuation and sensing, so they can be accessed and controlled from anywhere around the world [41].
3.
Internet of Services
The Internet of Services (IoS) can be considered as the new possibility for relationships with stakeholders or the general public to offer new services that can be found, used and paid for online, bringing about new business models [41].
4.
Computer simulation
Computer simulation, also known as virtual commissioning or digital twin, involves the virtual simulation of a system or object to study their movements, interferences and handling in order to optimize them, reducing potential problems before their implementation and production [103].
5.
Additive manufacturing
Additive manufacturing (AM), 3D printing or additive layer manufacturing (ALM) is a technology that allows the manufacture of three-dimensional objects via the deposition of successive layers of material, commanded by software [104,105].
6.
Collaborative robotics
Unlike the robots designed during Industry 3.0, in Industry 4.0 the robots are designed to work or interact with humans, reducing human risk and effort while working [37].
7.
Virtual reality
Virtual reality (VR) is characterized by the creation of a virtual environment, making the user feel as if the virtual universe is a reality, generating an immersive experience through observation [37,106].
8.
Augmented reality
Augmented reality (AR) is a technology that allows virtual objects or data to be introduced into the observer’s visual field, expanding the physical environment, so that human beings can interact with them in a superior way [1,37].
9.
Radio Frequency Identification
Radio frequency identification (RFID) technology is used in a wide variety of products to allow remote identification and better control [1,107].
10.
Big Data analytics
Through big data analytics, it is possible to collect, manipulate, compile and analyze large amounts of data from many different sources [108].
11.
Artificial intelligence
Artificial intelligence (AI) is a system capable of interpreting and learning from external data and using this learning process to reach specific tasks and goals while adjusting to different conditions or situations in a flexible way [109].
12.
Cybersecurity
It is important that systems that support Industry 4.0 can be protected from cyber-attacks, as the Internet is the main vehicle for communication and data exchange in Industry 4.0 [1,102].
13.
Integrated system
The many different systems from various equipment manufacturers need to communicate with each other; therefore, these systems must be integrated to make the equipment interoperable [41].
14.
Cloud computing
The data received from the various devices, IoT objects, sensors and actuators can be stored and processed in servers that can be located anywhere in the world; therefore, such data are said to be in the “cloud”, as one has no idea where the server is located [102].

2.3. Cleaner Production

To minimize climate change, companies are pressured by non-governmental organizations, policymakers and customers to reduce the operational impacts of their operations on the environment [110,111,112].
The expression cleaner production was first used at the Council of the United Nations Environment Programme (UNEP) in 1989 [113,114,115,116,117,118,119,120]. According to the UNEP [114,115,116,117,118,119,120], cleaner production can be defined as a preventive environmental strategy that is constantly applied to production processes, products and services to improve overall efficiency while minimizing risks to humans and the environment.
Cleaner production is an umbrella term that includes terms such as green productivity, pollution prevention, eco-efficiency [111,121,122], green manufacturing [123,124,125], environmentally benign manufacturing and sustainable manufacturing, among others [123].
Cleaner production can be implemented not only in any industrial process, but also in the products themselves, as well as in the most diverse services offered to society [110,111,112,113]. While increasing industrial efficiency, cleaner production protects the consumer, the environment and the worker, increasing competitiveness and profitability [116]. Production planning and control is an important ally when implementing cleaner production strategies in a company [45,119].
The focus of cleaner production is “prevention”, avoiding unnecessary costs and reducing the use of natural resources and the production of waste, moving towards a more sustainable and safe society [124].
The aims of cleaner production are the minimization of pollutant emissions and waste generation [112,126,127,128], the efficient use of energy and water and the reuse of waste [111,114,127,128,129,130,131], while minimizing operating costs [128], increasing the environmental performance [112,125], improving the operational performance by optimizing production resources, increasing the quality of products and services made available to society [101], improving occupational health and safety [132,133,134] and minimizing the use of non-renewable natural resources and the production of pollution resulting from manufacturing processes [113,114,118,119,120,121,122,129].
These possibilities allow the implementation of cleaner production to increase the economic performance of companies, contributing to the value of the company in the market [132] and economic gains while cooperating for the development of a culture of environmental protection [3,20,113].

2.4. Cleaner Production Strategy

The integration of Industry 4.0 technologies and cleaner production practices and strategies enables people involved in the implementation of Industry 4.0 to implement sustainable business models [115]. The adoption of Industry 4.0, cleaner production practices and circular economy initiatives can increase the sustainable performance of manufacturing organizations [134].
Large corporations are adopting Industry 4.0 and cleaner production strategies to increase their performance and innovate faster, while preserving the environment [135]. Industry 4.0 technologies can be used to reinforce cleaner production strategies in organizations, providing competitive advantage to these organizations [22,23,27], due to the optimizations of the utilization of resources and the possibility of increasing the follow-up of the product life cycle [136].
In the holistic and sustainable model for implementing Industry 4.0 [3], the cleaner production strategy and social stakeholders, composed of unions (workers and employers), governments, academic institutions, banks, private companies and other organizations and institutions, are the basis to consider in the implementation process, not a consequence (see Figure 1).
Other models that emphasize the cleaner production strategy or practice as a pillar to be taken into account for implementing Industry 4.0 are also superficial about this pillar. It is relevant to highlight which cleaner production strategy should be considered, to help those involved in Industry 4.0 projects to implement it more stably, thereby contributing to the theory and practice, the objective of this study.

3. Materials and Methods

The literature search was employed as research method to identify and analyze possible cleaner production strategies associated with Industry 4.0 to optimize manufacturing systems in Industry 4.0 implementation projects.
The Scopus and Web of Science databases were used in the literature search, as presented in Table 1, when no filter was used.
The largest number of documents found in the Web of Science database was due to an error in the search software, which considered the name of the journal in the search field along with title, abstract and keywords.
After excluding duplicates and filtering to choose only journals, 73 journals were identified for full reading, so 32 papers were selected where there were proposals for cleaner production strategies to optimize manufacturing systems in Industry 4.0 implementation projects.
This reduced number of documents found with the theme of this study (32) in relation to “cleaner production” and “Industry 4.0” points to the scarcity of the theme.

4. Results

Table 2 presents possible cleaner production strategies associated with Industry 4.0, as found in the literature research, to optimize manufacturing systems in Industry 4.0 implementation projects, in addition to reducing the environmental impact of these companies.
The ten dimensions that classify cleaner production strategies are addressed below, answering RQ1.

Cleaner Production Strategies for Industry 4.0 Implementation

1. Strategy
The strategy dimension covers the selection of the process and technologies to be used in the implementation of Industry 4.0 [121,137,138,139,140,141,142,143,144,145,146]; that is, this selection must be made to meet cleaner production strategies, so that cleaner production can guide the implementation project from the beginning, not as a consequence as presented in some implementation models.
2. Waste
This dimension encompasses the minimization of emissions or pollutants [22,25,27,57,96,134] and the optimization of waste disposal [121,137,138,139,140,141,142,143,144,145,146,147,148] and management [48,57,82,119,124,147,148], which should be a concern from the beginning of the implementation of Industry 4.0.
3. Recycling
The recycling dimension addresses the waste recycling [93,94,119,148,149], the possibility of digitally identifying the materials that make up the products, facilitating their disposal or reuse [121,150,151,152], and the possibility of recycling materials in company [147], contributing to the reduced use of new raw materials and industrial costs.
4. Life cycle
The life cycle dimension ranges from designing to extend the life cycle of a product [121,147,150,151,152,153,154,155,156,157,158,159] to using Industry 4.0 to manage the entire life cycle of a product [22,26,57,119,124,148,160,161,162,163,164,165,166,167,168,169,170], supporting the production of differentiated products.
5. Resources
The resources dimension includes the use of Industry 4.0 to manage resources efficiently [26,57,119,124,147,148,169,171] and optimize resource utilization [172], preserving the environment while improving productivity.
6. Energy
This dimension addresses the management of a renewable energy grid system [57], as well as the reuse of the heat generated by the company in the operations and offices [98] and the use of Industry 4.0 to optimize energy consumption [26,27,57,82,96,151,168,169,173,174], reducing industrial costs and carbon footprints.
7. Production
The production dimension encompasses the largest number of cleaner production strategies. It considers the use Industry 4.0 to manage or map the supply chain [25,135,170], control the inventory of in-process and finished goods [23,27], manage production efficiently [3,22,25,45,49,57,124,151], enable production system integration [23,96], manage production and maintenance through energy consumption [119], allow production integration throughout the organization [23,25,96] and optimize the production planning and control processes [27] and the utilization of human resources [151], with the aim of increasing productivity while reducing the environmental impacts.
8. Work
Coming second in the number of cleaner production strategies, the work dimension covers the use of Industry 4.0 to improve work safety [172], collaborative working [47], knowledge-sharing [47] and workplace conditions [171], focusing on providing a better working environment.
9. Performance
The performance dimension uses Industry 4.0 to engage all stakeholders to optimize the organizational performance [25], showing the need to unite ideals to achieve the implementation of Industry 4.0.
10. Environment
The environmental dimension, which encompasses all of the other dimensions, is formed by the use of Industry 4.0 to increase environmental management [25,48], with the aim of reducing the environmental impacts of these companies while optimizing manufacturing systems.
Table 2. Cleaner production strategies associated with Industry 4.0.
Table 2. Cleaner production strategies associated with Industry 4.0.
DimensionCleaner Production StrategiesStudies
StrategySelection of an adequate process considered environmentally friendly[121,137,138,139]
Selection of technologies considered environmentally friendly[121,137,138,139]
WasteUse Industry 4.0 to minimize emissions/pollutants[22,25,27,57,96,134]
Optimization of waste disposal[121,137]
Use Industry 4.0 to manage waste[48,57,82,119,124,147,148]
RecyclingUse Industry 4.0 for waste recycling[93,94,119,148,149]
Digitally identify the materials that make up the products, facilitating their disposal/reuse[121,150,151,152,153,154,155,156,157,158,159]
On-site recycling[147]
Life cycleDesign to prolong the life cycle of products[121,147,150,151,152]
Use Industry 4.0 to manage life cycle[22,26,57,119,124,148,160,161,162,163,164,165,166,167,168,169,170]
ResourcesUse Industry 4.0 to efficiently manage resources [26,57,119,124,147,148,169,171]
Use Industry 4.0 to optimize resource utilization[172]
EnergyManagement of a renewable energy grid system[57]
Reuse of the heat generated by the company (operations and offices)[98]
Use Industry 4.0 to optimize energy consumption[26,27,57,82,96,151,168,169,173,174]
ProductionUse Industry 4.0 to manage/map the supply chain [25,135,170]
Use Industry 4.0 to efficiently manage production [3,22,25,45,49,57,124,151]
Use Industry 4.0 to control in-process and finished goods inventory [23,27]
Use Industry 4.0 to manage production and maintenance through energy consumption, [119]
Use Industry 4.0 to enable production system integration [23,96]
Use Industry 4.0 to enable production integration across the organization[23,25,96]
Use Industry 4.0 to optimize production planning and control[27]
Use Industry 4.0 to optimize the utilization of human resources[151]
WorkUse Industry 4.0 to improve work safety[172]
Use Industry 4.0 to improve collaborative work[47]
Use Industry 4.0 to improve knowledge-sharing[47]
Use Industry 4.0 to improve workplace condition[171]
PerformanceUse Industry 4.0 to engage all stakeholders to optimize organizational performance[25]
EnvironmentUse Industry 4.0 to increase environmental management[25,48]

5. Discussion

A discussion about the ten dimensions and their cleaner production strategies is presented here. Possible Industry 4.0 technologies and applications for development and use are also suggested to meet these cleaner production strategies, answering RQ2.

5.1. Strategy Dimension

The selection of an adequate process, as proposed by [121,137,138,139,140,141,142,143,144,145,146], and the selection of technologies, as indicated by [121,137,138,147], considered environmentally friendly should guide Industry 4.0 implementation projects, preceding all phases.
This is in line with the holistic and sustainable model for implementing Industry 4.0 [3], which considers that cleaner production strategies should be the basis for any process or technology selection; that is, the implementation of Industry 4.0 should consider cleaner production strategies antecedents and not consequences of the implementation processes.
In this way, the concern for the preservation of the environment guides the entire implementation of the Industry 4.0 strategy, also focusing on maintaining sustainable development.

5.2. Waste Dimension

Industry 4.0 technologies should also be considered to minimize emissions and pollutants [22,25,27,57,83,96,134], contributing to reduced waste generation [112,125].
The optimization of waste disposal [117,137,138,139,140,141,142,143,144,145,146,147,148] is another possibility with Industry 4.0, helping to improve occupational health and safety [131].
For example, bins equipped with sensors and actuators and accessed via an IoT application (i.e., smart bins) could inform users via the Internet when the bin is almost full, requesting its collection. They could also manage the generated waste rate by the week, day, hour or minute, triggering alerts when necessary.
The use of Industry 4.0 technologies to manage waste [48,57,82,119,124,147,148] contributes to moving towards a more sustainable and secure society [124].

5.3. Recycling Dimension

The technologies of Industry 4.0 can be used for waste recycling [93,94,119,148,149], optimizing the use of resources [136].
These technologies can also be used to digitally identify the materials that make up the products, facilitating their disposal or reuse [121,150,151,152,153,154,155,156,157,158,159] by providing adequate technical information to assist in the disposal or reuse process.
This could be facilitated by the use of RFID tags or QR codes inserted in strategic locations on the products, with instructions on how to disassemble and recycle the parts.
Another possibility for Industry 4.0 technologies is to perform on-site recycling [147], using cleaner production strategies and circular economy initiatives to increase the sustainable performance of manufacturing organizations [83,134,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167].

5.4. Life Cycle Dimension

The cleaner production strategy should be used as the basis for implementing Industry 4.0, not just processes [121,137,138,139] and technologies [121,137,138,147], which should be selected to reinforce this strategy. Products should be designed to extend their life cycle [121,147,151,152], reinforcing the use of a preventive environmental strategy that is constantly applied to products and services to improve their overall efficiency while minimizing the risks to humans and the environment, as stated by the UNEP [120].
Industry 4.0 technologies should also be used to manage the life cycles of the products [26,57,119,124,148,160,161,162,163,164,165,166,167,168,169,170], using this management information as feedback to redesign products with superior efficiency [120], protecting the consumer, the environment and the worker, and increasing competitiveness and profitability, as stated by UNEP [120].
Enhancing these products with IoT, i.e., making them “smart”, would allow the products to alert users over the Internet when maintenance is required or when an upgrade is possible to extend their life cycle.

5.5. Resources Dimension

In the implementation of Industry 4.0, the technologies and processes should be used to support the resources management efficiently [57,119,124,147,148,169,171], in order to reduce the use of natural resources and waste, contributing to a safer and more sustainable society [120].
Industry 4.0 technological applications should also be used to optimize resource utilization [172], thereby optimizing the productive resources [5,113,133], representing a gain for companies involved in Industry 4.0 implementation projects.
Artificial intelligence could be trained to control processes and big data analytics to help keep the processes optimized in order to use resources efficiently.

5.6. Energy Dimension

In order to cooperate to reduce global energy increases [94], Industry 4.0 can be used to manage a renewable energy grid system [57], where the surplus of electricity generated can be offered to the public electric system, thereby benefiting society, as recommended by the UNEP [120].
Another way to reduce energy consumption is to reuse the heat generated by the company, as found various in operations and office equipment [98], thereby minimizing the operating costs [128] and increasing the environmental performance [112,125].
Industry 4.0 can also be used to optimize energy consumption [26,27,57,82,96,147,164,169,170], helping to save energy through its cleaner production strategy [5,7,113].
By identifying potential heat sources using sensors or IoT, they could be monitored to direct their surplus energy to the company’s electrical grid.

5.7. Production Dimension

There are many possibilities to use Industry 4.0 technologies and concepts to improve operations systems effectively and efficiently.
Industry 4.0 can be applied to manage or map the supply chain [25,131,166], enabling individuals to manage production efficiently [3,22,25,45,49,57,120,147], minimizing the use of non-renewable natural resources and pollution resulting from manufacturing processes [113,118].
Industry 4.0 technologies can also be employed to control the in-process and finished goods inventories [23,27], enabling the provision of a better information service to the customer and society [101].
The control of production and maintenance management processes through energy consumption [119] is a possibility that Industry 4.0 presents [8].
The use of Industry 4.0 can allow the integration of the production system [23,96] and the use of this system throughout the organization [23,25,96], contributing to the unification of information, an important point when implementing sustainable business models [119].
Industry 4.0 technologies can lead to improved production planning and control [27,45,84,85,86,87,88,89,90,123], creating opportunities to implement cleaner production processes [45] and optimize the use of human resources [151,173,174,175,176], contributing to improving productive resources and lives [101].
Computer simulations could be used to improve processes, prior to their practical implementation, and integrated systems could be used to improve production processes through their optimization. Additive manufacturing could help in the production of customized products.

5.8. Work Dimension

Workplace safety can be improved using Industry 4.0 [172], enabling the improvement of collaborative working [47] and workplace conditions [171], increasing the occupational health and safety of workers [133] and collaborating toward cleaner production.
The knowledge-sharing opportunities provided by Industry 4.0 [47] can help people move towards a more sustainable, safe and educated society [124].
Virtual reality could be used to train workers and augmented reality could be used to help with their daily tasks or for special occasions when advanced features are need. Collaborative robots could be used to help workers with their tasks.

5.9. Performance Dimension

The integrated information provided by Industry 4.0 technologies can be used to engage all stakeholders to optimize organizational performance [25], while preserving the environment and enabling increased competitiveness and profitability, as recommended by UNEP [120].
IoS could help in this task, maintaining transparent communication with all stakeholders and providing real-time information about the company; what has been planned and accomplished; and its goals by year, month, week or day, among other factors.

5.10. Environment Dimension

There are diverse ways to use Industry 4.0 to increase environmental management [25] to contribute to achieving cleaner production, just as cleaner production strategies should be considered as a pillar to implement Industry 4.0, not its consequence [3], in order to minimize industrial impacts on the environment. Cybersecurity is an important concern in Industry 4.0; as with all data and information circulating over the Internet, attacks must be repelled.

6. Conclusions

This study aimed to identify and analyze possible cleaner production strategies associated with Industry 4.0 to optimize manufacturing systems in Industry 4.0 implementation projects, in addition to reducing the environmental impacts of these companies.
This paper contributes to the theory by identifying in the academic literature cleaner production strategies associated with Industry 4.0, classified here into ten dimensions. Each dimension was analyzed according to its cleaner production strategies, and based on this discussion some possibilities for developing technologies and applications to meet these dimensions of cleaner production have been presented, potentially influencing further research in this field.
The contribution to the practice is the identification of cleaner production strategies that could guide the Industry 4.0 implementation process, helping those involved in Industry 4.0 projects to implement it more stably. Policy-makers can use this study to guide Industry 4.0 implementation projects to adopt the cleaner production strategies identified here, and they could also stimulate researchers to develop the technologies and applications proposed here, such as establishing incentives for this line of research via initiatives in favor of the environment and manufacturing systems.
Although the cleaner production strategies presented here are not exhaustive, which is a limitation, this study could stimulate academics and professionals in general to develop or study other relevant cleaner production strategies to support Industry 4.0, contributing to reducing the environmental impacts of these companies.

Author Contributions

All authors contributed to the study design. Conceptualization: W.C.S., J.C.C. and S.F.d.P.M.; methodology: W.C.S., S.F.d.P.M., A.F.d.L., J.A.G. and J.R.d.N.; validation: J.V.S.N., G.G.S.J., E.d.S.C. and J.L.d.A.; writing—original draft preparation: W.C.S.; writing—review and editing: S.F.d.P.M. and J.C.C., visualization, L.S.S. and J.C.C.; supervision, W.C.S. and J.C.C.; project administration, S.F.d.P.M., L.S.S. and J.C.C.; funding acquisition, A.F.d.L., J.L.d.A. and G.G.S.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES) of the Federal Government of Brazil.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Our gratitude is extended to Dinan Dhom Pimentel Satyro for providing linguistic help.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ribeiro, D.B.; Coutinho, A.d.R.; Satyro, W.C.; Campos, F.C.D.; Lima, C.R.C.; Contador, J.C.; Gonçalves, R.F. The DAWN readiness model to assess the level of use of Industry 4.0 technologies in the construction industry in Brazil. Constr. Innov. 2022. ahead-of-print. [Google Scholar] [CrossRef]
  2. Satyro, W.C.; Spinola, M.M.; Sacomano, J.B.; da Silva, M.T.; Gonçalves, R.F.; Pessoa, M.S.P.; Contador, J.C.; Contador, J.L.; Schiavo, L. Implementation of Industry 4.0 in Germany, Brazil and Portugal: Barriers and Benefits. In Advances in Production Management Systems. Towards Smart Production Management Systems, Proceedings of the APMS 2019. IFIP Advances in Information and Communication Technology, Austin, TX, USA, 1–5 September 2019; Ameri, F., Stecke, K., von Cieminski, G., Kiritsis, D., Eds.; Springer: Cham, Switzerland, 2019; p. 567. [Google Scholar] [CrossRef]
  3. Satyro, W.C.; Contador, J.C.; Contador, J.L.; Fragomeni, M.A.; Monken, S.F.d.P.; Ribeiro, A.F.; de Lima, A.F.; Gomes, J.A.; do Nascimento, J.R.; de Araújo, J.L.; et al. Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model. Sustainability 2021, 13, 12479. [Google Scholar] [CrossRef]
  4. Contador, J.C.; Satyro, W.C.; Contador, J.L.; Spinola, M.d.M. Taxonomy of organizational alignment: Implications for data-driven sustainable performance of firms and supply chains. J. Enterp. Inf. Manag. 2021, 34, 343–364. [Google Scholar] [CrossRef]
  5. de Oliveira Neto, G.C.; Ferreira Correia, J.M.; Silva, P.C.; de Oliveira Sanches, A.G.; Lucato, W.C. Cleaner Production in the Textile Industry and its Relationship to Sustainable Development Goals. J. Clean. Prod. 2019, 228, 1514–1525. [Google Scholar] [CrossRef]
  6. Alkaya, E.; Demirer, G.N. Sectoral assessment of the Turkish textile industry for the diffusion of sustainable production approach. J. Text. Inst. 2014, 106, 1212–1225. [Google Scholar] [CrossRef]
  7. Ghazinoory, S. Cleaner production in Iran: Necessities and priorities. J. Clean. Prod. 2005, 13, 755–762. [Google Scholar] [CrossRef]
  8. Rakib, M.I.; Saidur, R.; Mohamad, E.N.; Afifi, A.M. Waste-heat utilization—The sustainable technologies to minimize energy consumption in Bangladesh textile sector. J. Clean. Prod. 2017, 142, 1867–1876. [Google Scholar] [CrossRef]
  9. Ali, I.; Kim, S.; Kim, S.; Kim, J. Recycling of textile wastewater with a membrane bioreactor and reverse osmosis plant for sustainable and cleaner production. Desalinat. Water Treat. 2016, 57, 27441–27449. [Google Scholar] [CrossRef]
  10. Yukseler, H.; Uzal, N.; Sahinkaya, E.; Kitis, M.; Dilek, F.B.; Yetis, U. Analysis of the best available techniques for wastewaters from a denim manufacturing textile mill. J. Environ. Manag. 2017, 203, 1118–1125. [Google Scholar] [CrossRef]
  11. Bhuiyan, M.A.R.; Ali, A.; Islam, A.; Hannan, M.A.; Kabir, S.M.F.; Islam, M.N. Coloration of polyester fiber with natural dye henna (Lawsonia inermis L.) without using mordant: A new approach towards a cleaner production. Fash. Text. 2018, 5, 2. [Google Scholar] [CrossRef] [Green Version]
  12. Hossain, L.; Sarker, S.K.; Khan, M.S. Evaluation of present and future wastewater impacts of textile dyeing industries in Bangladesh. Environ. Dev. 2018, 26, 23–33. [Google Scholar] [CrossRef]
  13. Schaltegger, S.; Viere, T.; Zvezdov, D. Paying attention to environmental payoffs: The case of an Indonesian textile manufacturer. Int. J. Glob. Environ. Issues 2012, 12, 56–75. [Google Scholar] [CrossRef]
  14. Petek, J.; Glavic, P. Improving the sustainability of regional cleaner production programs. Resour. Conserv. Recycl. 2000, 29, 19–31. [Google Scholar] [CrossRef]
  15. Manring, S.L.; Moore, S.B. Creating and managing a virtual interorganizational learning network for greener production: A conceptual model and case study. J. Clean. Prod. 2006, 14, 891–899. [Google Scholar] [CrossRef]
  16. Taylor, B. Encouraging industry to assess and implement cleaner production measures. J. Clean. Prod. 2006, 14, 601–609. [Google Scholar] [CrossRef]
  17. Zhang, C.; Beck, M.B.; Chen, J. Gauging the impact of global trade on China’s local environmental burden. J. Clean. Prod. 2013, 54, 270–281. [Google Scholar] [CrossRef]
  18. Ortolano, L.; Sanchez-Triana, E.; Afzal, J.; Ali, C.L.; Rebellón, S.A. Cleaner production in Pakistan’s leather and textile sectors. J. Clean. Prod. 2014, 68, 121–129. [Google Scholar] [CrossRef] [Green Version]
  19. Yuan, Z.W.; Zhu, Y.N.; Shi, J.K.; Liu, X.; Huang, L. Life-cycle assessment of continuous pad-dyeing technology for cotton fabrics. Int. J. Life Cycle Assess. 2013, 18, 659–672. [Google Scholar] [CrossRef]
  20. Moktadir, M.A.; Ali, S.M.; Kusi-Sarpong, S.; Shaikh, M.A.A. Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process Saf. Environ. Prot. 2018, 117, 730–741. [Google Scholar] [CrossRef]
  21. Hermann, M.; Pentek, T.; Otto, B. Design principles for Industrie 4.0 Scenarios: A literature review. In Working Paper No. 01/2015; Technische. Universität Dortmund: Dortmund, Germany; Fakultät Maschinenbau and Audi Stiftungslehrstuhl—Supply Net, Order Management: Ingolstadt, Germany, 2015; pp. 1–15. [Google Scholar]
  22. Piwowar-Sulej, K. Human resources development as an element of sustainable HRM—With the focus on production engineers. J. Clean. Prod. 2021, 278, 124008. [Google Scholar] [CrossRef]
  23. Shayganmehr, M.; Kumar, A.; Garza-Reyes, J.A.; Moktadir, M.A. Industry 4.0 enablers for a cleaner production and circular economy within the context of business ethics: A study in a developing country. J. Clean. Prod. 2021, 281, 125280. [Google Scholar] [CrossRef]
  24. Amjad, M.S.; Rafique, M.Z.; Khan, M.A. Leveraging optimized and cleaner production through Industry 4.0. Sustain. Prod. Consum. 2021, 26, 859–871. [Google Scholar] [CrossRef]
  25. Lu, J.; Ren, L.; Zhang, C.; Rong, D.; Ahmed, R.R.; Streimikis, J. Modified Carroll’s pyramid of corporate social responsibility to enhance organizational performance of SMEs industry. J. Clean. Prod. 2020, 271, 122456. [Google Scholar] [CrossRef]
  26. Ma, S.; Zhang, Y.; Liu, Y.; Yang, H.; Lv, J.; Ren, S. Data-driven sustainable intelligent manufacturing based on demand response for energy-intensive industries. J. Clean. Prod. 2020, 274, 123155. [Google Scholar] [CrossRef]
  27. Rajput, S.; Singh, S.P. Industry 4.0 Model for circular economy and cleaner production. J. Clean. Prod. 2020, 277, 123853. [Google Scholar] [CrossRef]
  28. Lucato, W.C.; Pacchini, A.P.T.; Facchini, F.; Mummolo, G. Model to evaluate the Industry 4.0 readiness degree in Industrial Companies. IFAC-PapersOnLine 2019, 52, 1808–1813. [Google Scholar] [CrossRef]
  29. Pinheiro, P.; Putnik, G.D.; Castro, A.; Castro, H.; Dal Bosco, F.R.; Romero, F. Industry 4.0 and industrial revolutions: An assessment based on complexity. FME Trans. 2019, 47, 831–840. [Google Scholar] [CrossRef] [Green Version]
  30. Türkes, M.C.; Oncioiu, I.; Aslam, H.D.; Marin-Pantelescu, A.; Topor, D.I.; Căpuşneanu, S. Drivers and barriers in using industry 4.0: A perspective of SMEs in Romania. Processes 2019, 7, 153. [Google Scholar] [CrossRef] [Green Version]
  31. Singh, S.; Mahanty, B.; Tiwari, M.K. Model and modelling of inclusive manufacturing system. Int. J. Comput. Integr. Manuf. 2019, 32, 105–123. [Google Scholar] [CrossRef]
  32. Virmani, N.; Salve, U.R.; Kumar, A.; Luthra, S. Analyzing roadblocks of Industry 4.0 adoption using graph theory and matrix approach. IEEE Trans. Eng. Manag. 2021, 70, 454–463. [Google Scholar] [CrossRef]
  33. Colombo, A.W.; Karnouskos, S.; Yu, X.; Kaynak, O.; Luo, R.C.; Shi, Y.; Leitão, P.; Ribeiro, L.; Haase, J. A 70-Year Industrial Electronics Society Evolution through Industrial Revolutions: The rise and flourishing of Information and Communication Technologies. IEEE Ind. Electron. Mag. 2021, 15, 115–126. [Google Scholar] [CrossRef]
  34. Hallioui, A.; Herrou, B.; Santos, R.S.; Katina, P.F.; Egbue, O. Systems-based approach to contemporary business management: An enabler of business sustainability in a context of industry 4.0, circular economy, competitiveness and diverse stakeholders. J. Clean. Prod. 2022, 373, 133819. [Google Scholar] [CrossRef]
  35. Ke, J.; Khanna, N.; Zhou, N. Analysis of water–energy nexus and trends in support of the sustainable development goals: A study using longitudinal water–energy use data. J. Clean. Prod. 2022, 371, 133448. [Google Scholar] [CrossRef]
  36. Shukla, I. Potential of renewable agricultural wastes in the smart and sustainable steelmaking process. J. Clean. Prod. 2022, 370, 133422. [Google Scholar] [CrossRef]
  37. Soares Júnior, G.G.; Satyro, W.C.; Bonilla, S.H.; Contador, J.C.; Barbosa, A.P.; Monken, S.F.P.; Martens, M.L.; Fragomeni, M.A. Construction 4.0: Industry 4.0 enabling technologies applied to improve workplace safety in construction. Res. Soc. Dev. 2021, 10, e280101220280. [Google Scholar] [CrossRef]
  38. Viles, E.; Kalemkerian, F.; Garza-Reyes, J.A.; Antony, J.; Santos, J. Theorizing the Principles of Sustainable Production in the context of Circular Economy and Industry 4.0. Sustain. Prod. Consum. 2022, 33, 1043–1058. [Google Scholar] [CrossRef]
  39. Fernando, Y.; Halili, M.; Tseng, M.-L.; Tseng, J.W.; Lim, M.K. Sustainable social supply chain practices and firm social performance: Framework and empirical evidence. Sustain. Prod. Consum. 2022, 32, 160–172. [Google Scholar] [CrossRef]
  40. Richnák, P.; Fidlerová, H. Impact and Potential of Sustainable Development Goals in Dimension of the Technological Revolution Industry 4.0 within the Analysis of Industrial Enterprises. Energies 2022, 15, 3697. [Google Scholar] [CrossRef]
  41. Satyro, W.C.; Sacomano, J.B.; da Silva, M.T.; Gonçalves, R.F.; Contador, J.C.; von Cieminski, G. Industry 4.0: Evolution of the Research at the APMS Conference. In Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing, Proceedings of the Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing, Hamburg, Germany, 3–7 September 2017; Lödding, H., Riedel, R., Thoben, K.D., von Cieminski, G., Kiritsis, D., Eds.; Springer: Cham, Switzerland, 2017; Volume 513, pp. 39–47. [Google Scholar] [CrossRef]
  42. Anderson, M.M.; Fort, K. From the ground up: Developing a practical ethical methodology for integrating AI into industry. AI Soc. 2022, 1–15. [Google Scholar] [CrossRef]
  43. Satyro, W.C.; Martens, M.L.; Spinola, M.D.M.; Vanalle, R.M.; Lucato, W.C.; De Oliveira Neto, G.C.; Rodrigues Pinto, L.F. Industry 4.0 in Brazil, Ireland and Argentina: Challenges and opportunities. In Proceedings of the International Conference on Computers and Industrial Engineering, Beijing, China, 18–21 October 2019; pp. 1–10. [Google Scholar]
  44. Cao, H.; Yang, X. Auto-configurable Event-Driven Architecture for Smart Manufacturing. In Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing, Proceedings of the IFIP Advances in Information and Communication Technology, Hamburg, Germany, 3–7 September 2017; Lödding, H., Riedel, R., Thoben, K.D., von Cieminski, G., Kiritsis, D., Eds.; Springer: Cham, Switzerland, 2017; Volume 513, pp. 30–38. [Google Scholar]
  45. Satyro, W.C.; Spinola, M.D.M.; de Almeida, C.M.V.B.; Giannetti, B.F.; Sacomano, J.B.; Contador, J.C.; Contador, J.L. Sustainable industries: Production planning and control as an ally to implement strategy. J. Clean. Prod. 2021, 281, 124781. [Google Scholar] [CrossRef]
  46. Ghobakhloo, M. The future of manufacturing industry: A strategic roadmap toward Industry 4.0. J. Manuf. Technol. Manag. 2018, 29, 910–936. [Google Scholar] [CrossRef] [Green Version]
  47. Ghobakhloo, M.; Fathi, M. Industry 4.0 and opportunities for energy sustainability. J. Clean. Prod. 2021, 295, 126427. [Google Scholar] [CrossRef]
  48. Chauhan, C.; Singh, A.; Luthra, S. Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. J. Clean. Prod. 2021, 285, 124809. [Google Scholar] [CrossRef]
  49. Satyro, W.C.; de Almeida, C.M.V.B.; Pinto Jr, M.J.A.; Contador, J.C.; Giannetti, B.F.; de Lima, A.F.; Fragomeni, M.A. Industry 4.0 implementation: The relevance of sustainability and the potential social impact in a developing country. J. Clean. Prod. 2022, 337, 130456. [Google Scholar] [CrossRef]
  50. Srivastava, P.R.; Sengupta, K.; Kumar, A.; Biswas, B.; Ishizaka, A. Post-epidemic factors influencing customer’s booking intent for a hotel or leisure spot: An empirical study. J. Enterp. Inf. Manag. 2022, 35, 78–99. [Google Scholar] [CrossRef]
  51. Peraković, D.; Periša, M.; Zorić, P. Challenges and issues of ICT in industry 4.0. In Design, Simulation, Manufacturing: The Innovation Exchange; Springer: Cham, Switzerland, 2019; pp. 259–269. [Google Scholar] [CrossRef]
  52. Roblek, V.; Thorpe, O.; Bach, M.P.; Jerman, A.; Meško, M. The fourth industrial revolution and the sustainability practices: A comparative automated content analysis approach of theory and practice. Sustainability 2020, 12, 8497. [Google Scholar] [CrossRef]
  53. Reis, J.Z.; Goncalves, R.F.; Lage, E.S.; Nääs, I.A. Internet of services-based business model: A case study in the livestock industry. Innov. Manag. Rev. 2022. in Press. [Google Scholar] [CrossRef]
  54. Despeisse, M.; Acerbi, F. Toward eco-efficient and circular industrial systems: Ten years of advances in production management systems and a thematic framework. Prod. Manuf. Res. 2022, 10, 354–382. [Google Scholar] [CrossRef]
  55. Petroni, B.C.A.; Reis, J.Z.; Gonçalves, R.F. Blockchain as an Internet of Services Application for an Advanced Manufacturing Environment. In Advances in Production Management Systems. Towards Smart Production Management Systems, Proceedings of the APMS 2019. IFIP Advances in Information and Communication Technologyp, Austin, TX, USA, 1–5 September 2019; Ameri, F., Stecke, K., von Cieminski, G., Kiritsis, D., Eds.; Springer: Cham, Switzerland, 2019; Volume 567. [Google Scholar] [CrossRef]
  56. Rossini, M.; Costa, F.; Tortorella, G.L.; Portioli-Staudacher, A. The interrelation between Industry 4.0 and lean production: An empirical study on European manufacturers. Int. J. Adv. Manuf. Technol. 2019, 102, 3963–3976. [Google Scholar] [CrossRef]
  57. Eldrandaly, K.A.; El Saber, N.; Mohamed, M.; Abdel-Basset, M. Sustainable Manufacturing Evaluation Based on Enterprise Industry 4.0 Technologies. Sustainability 2022, 14, 7376. [Google Scholar] [CrossRef]
  58. Oztemel, E.; Gursev, S. Literature review of Industry 4.0 and related technologies. J. Intell. Manuf. 2020, 31, 127–182. [Google Scholar] [CrossRef]
  59. Contador, J.C.; Satyro, W.C.; Contador, J.L.; Spinola, M.M. Flexibility in the Brazilian Industry 4.0: Challenges and Opportunities. Glob. J. Flex. Syst. 2020, 21, 15–31. [Google Scholar] [CrossRef]
  60. Asim, M.; Nasim, S. Modeling Enterprise Flexibility and Competitiveness for Indian Pharmaceutical Firms: A Qualitative Study. Glob. J. Flex. Syst. 2022, 23, 551–571. [Google Scholar] [CrossRef]
  61. Saha, P.; Talapatra, S.; Belal, H.M.; Jackson, V. Unleashing the Potential of the TQM and Industry 4.0 to Achieve Sustainability Performance in the Context of a Developing Country. Glob. J. Flex. Syst. 2022, 23, 495–513. [Google Scholar] [CrossRef]
  62. Kumar, V.; Vrat, P.; Shankar, R. Factors Influencing the Implementation of Industry 4.0 for Sustainability in Manufacturing. Glob. J. Flex. Syst. 2022, 23, 453–478. [Google Scholar] [CrossRef]
  63. Parameswar, N.; Dhir, S.; Khoa, T.T.; Galati, A.; Ahmed, Z.U. Dynamics of the termination of global alliances: Probing the past, analyzing the present and defining the frontiers for future research. Int. Mark. Rev. 2022, 39, 1093–1121. [Google Scholar] [CrossRef]
  64. Dieste, M.; Sauer, P.C.; Orzes, G. Organizational tensions in industry 4.0 implementation: A paradox theory approach. Int. J. Prod. Econ. 2022, 251, 108532. [Google Scholar] [CrossRef]
  65. Enrique, D.V.; Marcon, É.; Charrua-Santos, F.; Frank, A.G. Industry 4.0 enabling manufacturing flexibility: Technology contributions to individual resource and shop floor flexibility. J. Manuf. Technol. Manag. 2022, 33, 853–875. [Google Scholar] [CrossRef]
  66. Awan, U.; Sroufe, R.; Bozan, K. Designing Value Chains for Industry 4.0 and a Circular Economy: A Review of the Literature. Sustainability 2022, 14, 7084. [Google Scholar] [CrossRef]
  67. Mbakop, A.M.; Voufo, J.; Biyeme, F.; Meva’a, J.R.L. Moving to a Flexible Shop Floor by Analyzing the Information Flow Coming from Levels of Decision on the Shop Floor of Developing Countries Using Artificial Neural Network: Cameroon, Case Study. Glob. J. Flex. Syst. 2022, 23, 255–270. [Google Scholar] [CrossRef]
  68. Bappy, M.M.; Key, J.; Hossain, N.U.I.; Jaradat, R. Assessing the Social Impacts of Additive Manufacturing Using Hierarchical Evidential Reasoning Approach. Glob. J. Flex. Syst. 2022, 23, 201–220. [Google Scholar] [CrossRef]
  69. Cazeri, G.T.; Anholon, R.; Santa-Eulalia, L.A.; Rampasso, I.S. Potential COVID-19 impacts on the transition to Industry 4.0 in the Brazilian manufacturing sector. Kybernetes 2022, 51, 2233–2239. [Google Scholar] [CrossRef]
  70. Hui, H.; Bao, M.; Ding, Y.; Song, Y. Exploring the integrated flexible region of distributed multi-energy systems with process industry. Appl. Energy 2022, 311, 118590. [Google Scholar] [CrossRef]
  71. Maurya, D.; Srivastava, A. Controlling Partner Opportunism in Cross-Sectoral Alliance: Dynamics of Governance Flexibility. Glob. J. Flex. Syst. Manag. 2022, in press. [Google Scholar] [CrossRef]
  72. Bakon, K.; Holczinger, T.; Sule, Z.; Jasko, S.; Abonyi, J. Scheduling Under Uncertainty for Industry 4.0 and 5.0. IEEE Access 2022, 10, 74977–75017. [Google Scholar] [CrossRef]
  73. Sony, M.; Antony, J.; Mc Dermott, O. How do the technological capability and strategic flexibility of an organization impact its successful implementation of Industry 4.0? A qualitative viewpoint. Benchmarking 2022. in Press. [Google Scholar] [CrossRef]
  74. Adamtsevich, L. Industry 4.0 Technologies for Ensuring the Functionality of Urban Infrastructure Socially Significant Elements: A Review. Lect. Notes Civ. Eng. 2022, 231, 3–22. [Google Scholar]
  75. Grobelna, I.; Karatkevich, A. A Deadlock Recovery Policy for Flexible Manufacturing Systems with Minimized Traversing within Reachability Graph. In Proceedings of the 2022 21st International Symposium INFOTEH-JAHORINA, INFOTEH, East Sarajevo, Bosnia and Herzegovina, 16–18 March 2022. [Google Scholar]
  76. Almeida, R.P.; Ayala, N.F.; Benitez, G.B.; Kliemann Neto, F.J.; Frank, A.G. How to assess investments in industry 4.0 technologies? A multiple-criteria framework for economic, financial, and sociotechnical factors. Prod. Plan. Control. 2022, 1–20. [Google Scholar] [CrossRef]
  77. Tambare, P.; Meshram, C.; Lee, C.-C.; Ramteke, R.J.; Imoize, A.L. Performance measurement system and quality management in data-driven industry 4.0: A review. Sensors 2022, 22, 224. [Google Scholar] [CrossRef]
  78. Contieri, P.G.S.; Anholon, R.; De Santa-Eulalia, L.A. Industry 4.0 enabling technologies in manufacturing: Implementation priorities and difficulties in an emerging country. Technol. Anal. Strateg. Manag. 2022, 34, 489–503. [Google Scholar] [CrossRef]
  79. Tran, T.-A.; Ruppert, T.; Eigner, G.; Abonyi, J. Retrofitting-Based Development of Brownfield Industry 4.0 and Industry 5.0 Solutions. IEEE Access 2022, 10, 64348–64374. [Google Scholar] [CrossRef]
  80. Franke, F.; Franke, S.; Riedel, R. Retrofit Concept for Textile Production. In Advances in Production Management Systems. Towards Smart and Digital Manufacturing; APMS 2020, Proceedings of the IFIP Advances in Information and Communication Technology, Novi Sad, Serbia, 30 August–3 September 2020; Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D., Eds.; Springer: Cham, Switzerland, 2020; Volume 592. [Google Scholar] [CrossRef]
  81. Ramelli, S.; Wagner, A. What the stock market tells us about the consequences of COVID-19. In Mitigating the COVID Economic Crisis: Act Fast and Do Whatever; CEPR Press: London, UK, 2020; Volume 63. [Google Scholar]
  82. Kumar, R.; Singh, R.K.; Dwivedi, Y.K. Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges. J. Clean. Prod. 2020, 275, 124063. [Google Scholar] [CrossRef] [PubMed]
  83. Gupta, S.; Bag, S.; Modgil, S.; Beatriz Lopes de Sousa Jabbour, A.; Kumar, A. Examining the influence of big data analytics and additive manufacturing on supply chain risk control and resilience: An empirical study. Comput. Ind. Eng. 2022, 172, 108629. [Google Scholar] [CrossRef]
  84. Torres da Rocha, A.B.; Borges de Oliveira, K.; Espuny, M.; Salvador da Motta Reis, J.; Oliveira, O.J. Business transformation through sustainability based on Industry 4.0. Heliyon 2022, 8, e10015. [Google Scholar] [CrossRef]
  85. Borgianni, Y.; Maccioni, L.; Dignös, A.; Basso, D. A Framework to Evaluate Areas of Interest for Sustainable Products and Designs. Sustainability 2022, 14, 7931. [Google Scholar] [CrossRef]
  86. Turk, S. Taguchi Loss Function in Intuitionistic Fuzzy Sets along with Personal Perceptions for the Sustainable Supplier Selection Problem. Sustainability 2022, 14, 6178. [Google Scholar] [CrossRef]
  87. Zhang, M.; Lu, Y.; Hu, Y.; Amaitik, N.; Xu, Y. Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization. Sustainability 2022, 14, 5177. [Google Scholar] [CrossRef]
  88. Khaled, M.S.; Shaban, I.A.; Karam, A.; Hussain, M.; Zahran, I.; Hussein, M. An Analysis of Research Trends in the Sustainability of Production Planning. Energies 2022, 15, 483. [Google Scholar] [CrossRef]
  89. Popper, J.; Motsch, W.; David, A.; Petzsche, T.; Ruskowski, M. Utilizing multi-agent deep reinforcement learning for flexible job shop scheduling under sustainable viewpoints. In Proceedings of the 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Mauritius, Mauritius, 7–8 October 2021. [Google Scholar]
  90. Cañas, H.; Mula, J.; Campuzano-Bolarín, F.; Poler, R. A conceptual framework for smart production planning and control in Industry 4.0. Comput. Ind. Eng. 2022, 173, 108659. [Google Scholar] [CrossRef]
  91. Panicker, A.; Sharma, A.; Khandelwal, U. Factorization of AI Application in HRM. Lect. Notes Netw. Syst. 2022, 435, 637–646. [Google Scholar]
  92. Plattform Industrie 4.0. Available online: https://www.plattform-i40.de/IP/Navigation/EN/Industrie40/WhatIsIndustrie40/what-is-industrie40.html (accessed on 4 November 2022).
  93. Kurniawan, T.A.; Dzarfan Othman, M.H.; Hwang, G.H.; Gikas, P. Unlocking digital technologies for waste recycling in Industry 4.0 era: A transformation towards a digitalization-based circular economy in Indonesia. J. Clean. Prod 2022, 357, 131911. [Google Scholar] [CrossRef]
  94. Kurniawan, T.A.; Liang, X.; Singh, D.; Othman, M.H.D.; Goh, H.H.; Gikas, P.; Shoqeir, J.A. Harnessing landfill gas (LFG) for electricity: A strategy to mitigate greenhouse gas (GHG) emissions in Jakarta (Indonesia). J. Environ. Manag. 2022, 301, 113882. [Google Scholar] [CrossRef] [PubMed]
  95. Turner, C.; Moreno, M.; Mondini, L.; Salonitis, K.; Charnley, F.; Tiwari, A.; Hutabarat, W. Sustainable production in a circular economy: A business model for Re-distributed manufacturing. Sustainability 2019, 11, 4291. [Google Scholar] [CrossRef] [Green Version]
  96. Ghobakhloo, M. Industry 4.0, digitization, and opportunities for sustainability. J. Clean. Prod. 2020, 252, 119869. [Google Scholar] [CrossRef]
  97. Wang, Y.; Ma, H.-S.; Yang, J.-H.; Wang, K.-S. Industry 4.0: A way from mass customisation to mass personalisation production. Adv. Manuf. 2017, 5, 311–320. [Google Scholar] [CrossRef]
  98. Liang, X.; Goh, H.H.; Kurniawan, T.A.; Zhang, D.; Dai, W.; Liu, H.; Liu, J.; Goh, K.C. Utilizing landfill gas (LFG) to electrify digital data centers in China for accelerating energy transition in Industry 4.0 era. J. Clean. Prod. 2022, 369, 133297. [Google Scholar] [CrossRef]
  99. Zhu, M.; Kurniawan, T.A.; Liang, D.; Song, Y.; Hermanowicz, S.W.; Othman, M.H.D. Advances in BiOX-based ternary photocatalysts for water treatment and energy storage applications: A critical review. Rev. Environ. Sci. Biotechnol. 2022, 21, 331–370. [Google Scholar] [CrossRef]
  100. Butt, J. Exploring the interrelationship between additive manufacturing and industry 4.0. Designs 2020, 4, 13. [Google Scholar] [CrossRef]
  101. Nenadál, J.; Vykydal, D.; Halfarová, P.; Tylečková, E. Quality 4.0 Maturity Assessment in Light of the Current Situation in the Czech Republic. Sustainability 2022, 14, 7519. [Google Scholar] [CrossRef]
  102. Pacchini, A.P.T.; Lucato, W.C.; Facchini, F.; Mummolo, G. The degree of readiness for the implementation of Industry 4.0. Comput. Ind. 2019, 113, 103125. [Google Scholar] [CrossRef]
  103. Hu, D.; Mohamed, Y.; Taghaddos, H.; Hermann, U. A simulation-based method for effective workface planning of industrial construction projects. Constr. Manag. Econ. 2017, 36, 328–347. [Google Scholar] [CrossRef]
  104. Kanyilmaz, A.; Demir, A.; Chierici, M.; Berto, F.; Gardner, L.; Kandukuri, S.; Kassabian, P.; Kinoshita, T.; Laurenti, A.; Paoletti, I.; et al. Role of metal 3D printing to increase quality and resource-efficiency in the construction sector. Addit. Manuf. 2022, 50, 102541. [Google Scholar] [CrossRef]
  105. Lachmayer, L.; Ekanayaka, V.; Hürkamp, A.; Raatz, A. Approach to an optimized printing path for additive manufacturing in construction utilizing FEM modeling. Procedia. CIRP 2021, 104, 600–605. [Google Scholar] [CrossRef]
  106. Wen, J.; Gheisari, M. Using virtual reality to facilitate communication in the AEC domain: A systematic review. Constr. Innov. 2020, 20, 509–542. [Google Scholar] [CrossRef]
  107. Finkenzeller, K. RFID Handbook: Fundamentals and Applications in Contactless Smart Cards, Radio Frequency Identification and Near-Field Communication, 3rd ed.; Wiley: Chichester, UK, 2010; p. 478. [Google Scholar]
  108. De Mauro, A.; Greco, M.; Grimaldi, M. A formal definition of Big Data based on its essential features. Libr. Rev. 2016, 65, 122–135. [Google Scholar] [CrossRef]
  109. Darko, A.; Chan, A.P.; Adabre, M.A.; Edwards, D.J.; Hosseini, M.R.; Ameyaw, E.E. Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities. Autom. Constr. 2020, 112, 103081. [Google Scholar] [CrossRef]
  110. Oliveira Neto, G.C.D.; Tucci, H.N.P.; Correia, J.M.F.; da Silva, P.C.; da Silva, D.; Amorim, M. Stakeholders’ influences on the adoption of cleaner production practices: A survey of the textile industry. Sustain. Prod. Consum. 2021, 26, 126–145. [Google Scholar] [CrossRef]
  111. Oliveira Neto, G.C.D.; Tucci, H.N.P.; Correia, J.M.F.; da Silva, P.C.; da Silva, V.H.C.; Ganga, G.M.D. Assessing the implementation of Cleaner Production and company sizes: Survey in textile companies. J. Eng. Fibers Fabr. 2020, 15, 1–16. [Google Scholar] [CrossRef] [Green Version]
  112. Da Silva, P.C.; de Oliveira Neto, G.C.; Correia, J.M.F.; Tucci, H.N.P. Evaluation of economic, environmental and operational performance of the adoption of cleaner production: Survey in large textile industries. J. Clean. Prod. 2021, 278, 123855. [Google Scholar] [CrossRef]
  113. Leite, R.; Amorim, M.; Rodrigues, M.; Oliveira Neto, G. Overcoming barriers for adopting cleaner production: A case study in Brazilian small metal-mechanic companies. Sustainability 2019, 11, 4808. [Google Scholar] [CrossRef] [Green Version]
  114. Neto, G.C.O.; de Souza, M.T.S.; da Silva, D.; Silva, L.A. An assessment of the environmental and economic benefits of implementing reverse logistics in the textured glass sector. Ambiente Soc. 2014, 17, 199–220. [Google Scholar]
  115. de Oliveira Neto, G.C.; de Sousa, W.C. Economic and Environmental Advantage Evaluation of the Reverse Logistic Implementation in the Supermarket Retail. In IFIP International Conference on Advances in Production Management Systems, Proceedings of the Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World, Ajaccio, France, 20–24 September 2014; Volume 439, pp. 197–204. [Google Scholar]
  116. Oliveira Neto, G.C.D.; Cesar da Silva, P.; Tucci, H.N.P.; Amorim, M. Reuse of water and materials as a cleaner production practice in the textile industry contributing to blue economy. J. Clean. Prod. 2021, 305, 127075. [Google Scholar] [CrossRef]
  117. Gomes, M.G.; da Silva, V.H.C.; Pinto, L.F.R.; Centoamore, P.; Digiesi, S.; Facchini, F.; Neto, G.C.d.O. Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles. Sustainability 2020, 12, 3604. [Google Scholar] [CrossRef]
  118. Pinto, L.F.R.; Venturini, G.D.F.P.; Digiesi, S.; Facchini, F.; Oliveira Neto, G.C.D. Sustainability Assessment in Manufacturing under a Strong Sustainability Perspective—An Ecological Neutrality Initiative. Sustainability 2020, 12, 9232. [Google Scholar] [CrossRef]
  119. de Oliveira Neto, G.C.; da Conceição Silva, A.; Filho, M.G. How can Industry 4.0 technologies and circular economy help companies and researchers collaborate and accelerate the transition to strong sustainability? A bibliometric review and a systematic literature review. Int. J. Environ. Sci. Technol. 2022, 1–38. [Google Scholar] [CrossRef]
  120. UNEP—United Nations Environment Programme. Environmental Agreements and Cleaner Production: Questions and Answers; United Nations Environment Programme Division of Technology, Industry & Economics: Nairobi, Kenya; InWEnt: Bonn, Germany, 2006; pp. 1–28. [Google Scholar]
  121. Martinez-Marquez, D.; Florin, N.; Hall, W.; Majewski, P.; Wang, H.; Stewart, R.A. State-of-the-art review of product stewardship strategies for large composite wind turbine blades. Resour. Conserv. Recycl. Adv. 2022, 15, 200109. [Google Scholar] [CrossRef]
  122. Sangwan, K.S.; Mittal, V.K. A bibliometric analysis of green manufacturing and similar frameworks. Manag. Environ. Qual. 2015, 26, 566–587. [Google Scholar] [CrossRef]
  123. Satyro, W.C.; Sacomano, J.B.; Contador, J.C. Production Planning and Control: The Dissemination Tool of the Operation Strategy. In Advances in Production Management Systems. Initiatives for a Sustainable World, Proceedings of the APMS 2016. IFIP Advances in Information and Communication Technology, Iguassu Falls, Brazil, 3–7 September 2016; Springer: Cham, Switzerland, 2016; Volume 488. [Google Scholar] [CrossRef]
  124. Luthra, S.; Mangla, S.K.; Lopes de Sousa Jabbour, A.B.; Huisingh, D. Industry 4.0, Cleaner Production, and Circular Economy: An important agenda for improved Ethical Business Development. J. Clean. Prod. 2021, 326, 129370. [Google Scholar] [CrossRef]
  125. Yuksel, H. An empirical evaluation of cleaner production practices in Turkey. J. Clean. Prod. 2008, 16, S50–S57. [Google Scholar] [CrossRef]
  126. Leal Filho, W.; Salvia, A.L.; Paço, A.; Dias-Ferreira, C.; Neiva, S.; Rampasso, I.S.; Anholon, R.; de Vasconcelos, C.R.P.; Eustachio, J.H.P.P.; Jabbour, C.J.C. Assessing the Connections between COVID-19 and Waste Management in Brazil. Sustainability 2022, 14, 8083. [Google Scholar] [CrossRef]
  127. de Oliveira Neto, G.C.; Correia, J.M.F.; Tucci, H.N.P.; Librantz, A.F.H.; Giannetti, B.F.; de Almeida, C.M.V.B. Sustainable Resilience Degree assessment of the textile industrial by size: Incremental change in cleaner production practices considering circular economy. J. Clean. Prod. 2022, 380, 134633. [Google Scholar] [CrossRef]
  128. Neto, G.C.d.O.; Leite, R.R.; Lucato, W.C.; Vanalle, R.M.; Amorim, M.; Matias, J.C.O.; Kumar, V. Overcoming Barriers to the Implementation of Cleaner Production in Small Enterprises in the Mechanics Industry: Exploring Economic Gains and Contributions for Sustainable Development Goals. Sustainability 2022, 14, 2944. [Google Scholar] [CrossRef]
  129. Pinto, L.F.R.; Tucci, H.N.P.; Mummolo, G.; de Oliveira Neto, G.C.; Facchini, F. Circular Economy Approach on Energy Cogeneration in Petroleum Refining. Energies 2022, 15, 1713. [Google Scholar] [CrossRef]
  130. Oliveira Neto, G.C.D.; Tucci, H.N.P.; Godinho Filho, M.; Lucato, W.C.; da Silva, D. Moderating effect of OHS actions based on WHO recommendations to mitigate the effects of COVID-19 in multinational companies. Process Saf. Environ. Prot. 2022, 159, 652–661. [Google Scholar] [CrossRef]
  131. Lopes de Sousa Jabbour, A.B.; Chiappetta Jabbour, C.J.; Choi, T.-M.; Latan, H. ‘Better together’: Evidence on the joint adoption of circular economy and industry 4.0 technologies. Int. J. Prod. Econ. 2022, 252, 108581. [Google Scholar] [CrossRef]
  132. Zeng, S.X.; Meng, Z.H.; Yin, H.T.; Tam, C.M.; Sun, L. Impact of clean production on business performance. J. Clean. Prod. 2010, 18, 975–984. [Google Scholar] [CrossRef]
  133. Severo, E.A.; Guimaraes, C.F.; Dorion, E.C.; Nodari, C.H. Cleaner production, environmental sustainability and organizational performance: An empirical study in the Brazilian Metal-Mechanic industry. J. Clean. Prod. 2015, 96, 118–125. [Google Scholar] [CrossRef]
  134. Gupta, H.; Kumar, A.; Wasan, P. Industry 4.0, cleaner production and circular economy: An integrative framework for evaluating ethical and sustainable business performance of manufacturing organizations. J. Clean. Prod. 2021, 295, 126253. [Google Scholar] [CrossRef]
  135. Mubarik, M.S.; Naghavi, N.; Mubarik, M.; Kusi-Sarpong, S.; Khan, S.A.; Zaman, S.I.; Kazmi, S.H.A. Resilience and cleaner production in industry 4.0: Role of supply chain mapping and visibility. J. Clean. Prod. 2021, 292, 126058. [Google Scholar] [CrossRef]
  136. Rosa, P.; Sassanelli, C.; Urbinati, A.; Chiaroni, D.; Terzi, S. Assessing relations between Circular Economy and Industry 4.0: A systematic literature review. Int. J. Prod. Res. 2020, 58, 1662–1687. [Google Scholar] [CrossRef] [Green Version]
  137. Yusup, M.Z.; Mahmood, W.H.W.; Salleh, M.R.B.; Tukimin, R. A review on optimistic impact of cleaner production on manufacturing sustainability. Int. J. Adv. Manuf. Technol. 2013, 7, 79–99. [Google Scholar]
  138. Giannetti, B.; Bonilla, S.H.; Almeida, C.M.V.B. Cleaner production practices in a medium size gold-plated jewelry company in Brazil: When little changes make the difference. J. Clean. Prod. 2008, 16, 1106–1117. [Google Scholar] [CrossRef]
  139. Wen, H.; Lee, C.-C.; Song, Z. Digitalization and environment: How does ICT affect enterprise environmental performance? Environ. Sci. Pollut. Res. 2021, 28, 54826–54841. [Google Scholar] [CrossRef] [PubMed]
  140. Satyro, W.C.; Sacomano, J.B.; Contador, J.C.; Almeida, C.M.V.B.; Giannetti, B.F. Process of strategy formulation for sustainable environmental development: Basic model. J. Clean. Prod. 2017, 166, 1295–1304. [Google Scholar] [CrossRef]
  141. Demianchuk, M.; Bezpartochnyi, M.; Filipishyna, L.; Živitere, M. The model of achieving a balanced balance between economic efficiency and ecological-social responsibility of digitalized enterprise. J. Optim. Ind. Eng. 2021, 14, 63–70. [Google Scholar]
  142. Alsuwaidi, A.K.M.S.; Alshami, S.A.; Akmal, S. The Impact of Entrepreneurship Towards Innovation in Airport Industry: The Double Mediation Framework of Strategic Alignment and Learning Orientation. Acad. Strateg. Manag. J. 2021, 20, 1–19. [Google Scholar]
  143. Sidorov, A.A.; Kudinova, G.E.; Rozenberg, A.G. Assessment of Environmental Components in Municipal Development Strategies. In Innovative Economic Symposium; Lecture Notes in Networks and Systems; Springer: Berlin/Heidelberg, Germany, 2021; Volume 160 LNNS, pp. 327–332. [Google Scholar]
  144. van Rheede, A.; Lim, A. Understanding corporate responsibility in the hospitality industry: A view based on the strategy-as-practices. Adv. Ser. Manag. 2020, 24, 137–144. [Google Scholar]
  145. Satyro, W.C.; Sacomano, J.B.; Contador, J.C.; Raymundo, H. A framework of strategy formulation to improve competitive advantage in sustainable manufacturers and their supply chain. In Proceedings of the ILS 2016—6th International Conference on Information Systems, Logistics and Supply Chain, Bordeaux, France, 1–4 June 2016; pp. 1–7. [Google Scholar]
  146. Satyro, W.C.; Sacomano, J.B.; Contador, J.C. Strategic factors to obtain competitive advantage in industries that compete in environmental sustainability. In Advances in Production Management Systems. Initiatives for a Sustainable World, Proceedings of the APMS 2016. IFIP Advances in Information and Communication Technology, Iguassu Falls, Brazil, 3–7 September 2016; Springer: Cham, Switzerland, 2016; Volume 488. [Google Scholar] [CrossRef] [Green Version]
  147. David, L.O.; Nwulu, N.I.; Aigbavboa, C.O.; Adepoju, O.O. Integrating fourth industrial revolution (4IR) technologies into the water, energy & food nexus for sustainable security: A bibliometric analysis. J. Clean. Prod. 2022, 363, 132522. [Google Scholar]
  148. Pigola, A.; da Costa, P.R.; Carvalho, L.C.; Silva, L.F.d.; Kniess, C.T.; Maccari, E.A. Artificial intelligence-driven digital technologies to the implementation of the sustainable development goals: A perspective from Brazil and Portugal. Sustainability 2021, 13, 13669. [Google Scholar] [CrossRef]
  149. Maiurova, A.; Kurniawan, T.A.; Kustikova, M.; Bykovskaia, E.; Othman, M.H.D.; Singh, D.; Goh, H.H. Promoting digital transformation in waste collection service and waste recycling in Moscow (Russia): Applying a circular economy paradigm to mitigate climate change impacts on the environment. J. Clean. Prod. 2022, 354, 131604. [Google Scholar] [CrossRef]
  150. Stock, T.; Seliger, G. Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP 2016, 40, 536–541. [Google Scholar] [CrossRef]
  151. Lasi, H.; Fettke, P.; Kemper, H.-G.; Feld, T.; Hoffmann, M. Industry 4.0. Bus. Inf. Syst. Eng. 2014, 6, 239–242. [Google Scholar] [CrossRef]
  152. Rojko, A. Industry 4.0 Concept: Background and Overview. Int. J. Interact. Mob. Technol. 2017, 11, 77–90. [Google Scholar] [CrossRef] [Green Version]
  153. Cai, L.; Shi, X.; Zhu, J. Quality recovery or low-end recovery? Profitability and environmental impact of durable product recovery. Sustainability 2019, 11, 1726. [Google Scholar] [CrossRef] [Green Version]
  154. Giannetti, B.F.; Agostinho, F.; Almeida, C.M.V.B.; Yang, Z.; Liu, G.; Wang, Y.; Huisingh, D. Ten years working together for a sustainable world, dedicated to the 6th IWACP: Introductory article. J. Clean. Prod. 2019, 226, 866–873. [Google Scholar] [CrossRef]
  155. Yu, D.E.C.; Yu, K.D.S.; Tan, R.R. Implications of the pandemic-induced electronic equipment demand surge on essential technology metals. Clean. Resp. Consump. 2020, 1, 100005. [Google Scholar] [CrossRef]
  156. Sánchez-Carralero, A.; Armenta-Déu, C. Modelling and characterisation of the obsolescence process. Int. J. Prod. Lifecycle Manag. 2021, 13, 140–158. [Google Scholar] [CrossRef]
  157. Niklewicz-Pijaczyńska, M.; Stańczyk, E.; Gardocka-Jałowiec, A.; Gródek-Szostak, Z.; Niemczyk, A.; Szalonka, K.; Homa, M. A Strategy for Planned Product Aging in View of Sustainable Development Challenges. Energies 2021, 14, 7793. [Google Scholar] [CrossRef]
  158. Bisht, A. Sand futures: Post-growth alternatives for mineral aggregate consumption and distribution in the global south. Ecol. Econ. 2022, 191, 107233. [Google Scholar] [CrossRef]
  159. Bedford, L.; Mann, M.; Foth, M.; Walters, R. A Post-Capitalocentric Critique of Digital Technology and Environmental Harm: New Directions at the Intersection of Digital and Green Criminology. Int. J. Crime Justice Soc. Democr. 2022, 11, 167–181. [Google Scholar] [CrossRef]
  160. Li, Y.-M.; Wang, Y.; Chen, M.-J.; Huang, T.-Y.; Yang, F.-H.; Wang, Z.-J. Current status and technological progress in lead recovery from electronic waste. Int. J. Environ. Sci. Technol. 2023, 20, 1037–1052. [Google Scholar] [CrossRef]
  161. Chen, C.-W. Approaching sustainable development goals: Inspirations from the Arts and Crafts movement to reshape production and consumption patterns. Sustain. Dev. 2022, in press. [Google Scholar] [CrossRef]
  162. Kpossa, M.R.; Breka, J. L’économie de fonctionnalité comme solution à l’obsolescence programmée: Une étude exploratoire. Gestion 2000 2022, 39, 125–146. [Google Scholar] [CrossRef]
  163. Monserand, A. Buying into inequality: A macroeconomic analysis linking accelerated obsolescence, interpersonal inequality, and potential for degrowth. Eur. J. Econ. Econ. 2022, 19, 119–137. [Google Scholar]
  164. Levesque, S.; Robertson, M.; Klimas, C. A life cycle assessment of the environmental impact of children’s toys. Sustain. Prod. Consum. 2022, 31, 777–793. [Google Scholar] [CrossRef]
  165. Mesa, J.A.; Gonzalez-Quiroga, A.; Aguiar, M.F.; Jugend, D. Linking product design and durability: A review and research agenda. Heliyon 2022, 8, e10734. [Google Scholar] [CrossRef]
  166. Figge, F.; Dimitrov, S.; Schlosser, R.; Chenavaz, R. Does the circular economy fuel the throwaway society? The role of opportunity costs for products that lose value over time. J. Clean. Prod. 2022, 368, 133207. [Google Scholar] [CrossRef]
  167. Kumar, V.; Mishra, Y.; Meena, M.L. Planned Obsolescence: A Bibliometric Analysis. In Recent Trends in Product Design and Intelligent Manufacturing Systems; Lecture Notes in Mechanical Engineering; Deepak, B., Bahubalendruni, M.R., Parhi, D., Biswal, B.B., Eds.; Springer: Singapore, 2023. [Google Scholar] [CrossRef]
  168. Pei, Z.; Yu, T.; Yi, W.; Li, Y. Twenty-year retrospection on green manufacturing: A bibliometric perspective. IET Collab. Intell. Manuf. 2021, 3, 303–323. [Google Scholar] [CrossRef]
  169. Ma, S.; Zhang, Y.; Lv, J.; Ren, S.; Yang, H.; Wang, C. Data-driven cleaner production strategy for energy-intensive manufacturing industries: Case studies from Southern and Northern China. Adv. Eng. Inform. 2022, 53, 101684. [Google Scholar] [CrossRef]
  170. Leng, J.; Ruan, G.; Song, Y.; Liu, Q.; Fu, Y.; Ding, K.; Chen, X. A loosely-coupled deep reinforcement learning approach for order acceptance decision of mass-individualized printed circuit board manufacturing in industry 4.0. J. Clean. Prod. 2021, 280, 124405. [Google Scholar] [CrossRef]
  171. Cater, T.; Cater, B.; Cerne, M.; Koman, M.; Redek, T. Industry 4.0 technologies usage: Motives and enablers. J. Manuf. Technol. Manag. 2021, 32, 323–345. [Google Scholar] [CrossRef]
  172. El Baz, J.; Tiwari, S.; Akenroye, T.; Cherrafi, A.; Derrouiche, R. A framework of sustainability drivers and externalities for Industry 4.0 technologies using the Best-Worst Method. J. Clean. Prod. 2022, 344, 130909. [Google Scholar] [CrossRef]
  173. Munsamy, M.; Telukdarie, A. Business Process (4IR) Centric Optimization Modelling. Procedia. Comput. Sci. 2021, 180, 581–590. [Google Scholar] [CrossRef]
  174. Munodawafa, R.T.; Johl, S.K. Big data analytics capabilities and eco-innovation: A study of energy companies. Sustainability 2019, 11, 4254. [Google Scholar] [CrossRef] [Green Version]
  175. Latan, H.; Chiappetta Jabbour, C.J.; Lopes de Sousa Jabbour, A.B.; Ali, M.; Pereira, V. Career satisfaction in the public sector: Implications for a more sustainable and socially responsible human resource management. Hum. Resour. Manag. J. 2022, 32, 844–863. [Google Scholar] [CrossRef]
  176. Neto, G.C.O.; Leite, R.R.; Shibao, F.Y.; Lucato, W.C. Framework to over-come barriers in the implementation of cleaner production in small and medium-sized enterprises: Multiple case studies in Brazil. J. Clean. Prod. 2017, 142, 50–62. [Google Scholar] [CrossRef]
Figure 1. Holistic and sustainable model for implementing Industry 4.0 [3].
Figure 1. Holistic and sustainable model for implementing Industry 4.0 [3].
Sustainability 15 02161 g001
Table 1. Numbers of documents in Scopus and Web of Science database.
Table 1. Numbers of documents in Scopus and Web of Science database.
Search StringScopusWeb of Science
“cleaner production”476733,617
“Industry 4.0”23,86418,427
“cleaner production” AND “Industry 4.0”35103
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Satyro, W.C.; Contador, J.C.; Monken, S.F.d.P.; Lima, A.F.d.; Soares Junior, G.G.; Gomes, J.A.; Neves, J.V.S.; do Nascimento, J.R.; de Araújo, J.L.; Correa, E.d.S.; et al. Industry 4.0 Implementation Projects: The Cleaner Production Strategy—A Literature Review. Sustainability 2023, 15, 2161. https://doi.org/10.3390/su15032161

AMA Style

Satyro WC, Contador JC, Monken SFdP, Lima AFd, Soares Junior GG, Gomes JA, Neves JVS, do Nascimento JR, de Araújo JL, Correa EdS, et al. Industry 4.0 Implementation Projects: The Cleaner Production Strategy—A Literature Review. Sustainability. 2023; 15(3):2161. https://doi.org/10.3390/su15032161

Chicago/Turabian Style

Satyro, Walter Cardoso, Jose Celso Contador, Sonia Francisca de Paula Monken, Anderson Ferreira de Lima, Gilberto Gomes Soares Junior, Jansen Anderson Gomes, João Victor Silva Neves, José Roberto do Nascimento, Josiane Lima de Araújo, Eduardo de Siqueira Correa, and et al. 2023. "Industry 4.0 Implementation Projects: The Cleaner Production Strategy—A Literature Review" Sustainability 15, no. 3: 2161. https://doi.org/10.3390/su15032161

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop