The additive manufacturing (AM) field is rapidly expanding, attracting significant scientific attention. This family of processes will be widely used in the evolution of Industry 4.0, particularly in the production of customized components. However, as the complexity and variability of additive manufacturing processes increase, there is an increasing need for advanced techniques to ensure quality control, optimize performance, and reduce production costs. Multiple tests are required to optimize processing variables for specific equipment and processes, to achieve optimum processing conditions. The application of digital twins (DTs) has significantly enhanced the field of additive manufacturing. A digital twin, abbreviated as DT, refers to a computer-generated model that accurately depicts a real-world object, system, or process. A DT comprises the complete additive manufacturing process, from the initial conception phase to the final manufacturing phase. It enables the manufacturing pr... [more]

This article addresses the problem statement and objective by exploring the necessity, scope, and execution of digital transformation in the oil and gas industry from a psychological perspective. It highlights the cognitive barriers faced by non-ICT professionals, which are often overlooked in traditional approaches. The study integrates case studies and empirical evidence from a mixed-methods approach, including qualitative interviews with industry experts and quantitative surveys among employees, to provide a comprehensive understanding of the transformation process. The research emphasizes the integration of psychological theories with practical digital transformation strategies, illustrating key obstacles and solutions. By adopting a holistic approach that incorporates both technological advancements and psychological insights, the study aims to enhance the effectiveness and sustainability of digital transformation efforts. Major contributions include identifying cognitive barriers... [more]

The purpose of this article was to develop a method of analyzing the manufacturing process with variables indicating product competitiveness and technological capabilities in metric space as a cognitive source. The presented method will facilitate the identification of key development factors within the manufacturing processes that have the greatest impact on the adaptation of the manufacturing enterprise to Industry 4.0. The presented method of manufacturing process analysis integrates a number of tools (SMART method, brainstorming, BOST analysis, 3 × 3 metrics) that enable the implementation of statistical analysis. The model developed makes it possible to apply known mathematical methods in areas new to them (adaptation in the manufacturing area), which makes it possible to use scientific information in a new way. The versatility of the method allows it to be used in manufacturing companies to identify critical factors in manufacturing processes. A test of the developed method was c... [more]

Strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a lean learning factory was developed in the Pitesti University Center that allows students to learn about, experiment with, and research new lean manufacturing methods and techniques as well as Industry 4.0 in an environment similar to that of enterprises. The research presented in this study aimed to identify the minimum number of repetitions necessary to train operators to perform the same assembly operation while working at two differently organized workstations: one classic and the other including digital techniques. Several indicators were considered in our analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percent... [more]

In the wake of Industry 4.0, the ubiquitous internet of things provides big data to potentially quantify the environmental footprint of green products. Further, as the concept of Industry 5.0 emphasizes, the increasing mass customization production makes the product configurations full of individuation and diversification. Driven by these fundamental changes, the design for sustainability of a high-mix low-volume product−service system faces the increasingly deep coupling of technology-driven product solutions and value-driven human-centric goals. The multi-criteria decision making of sustainability issues is prone to fall into the complex, contradictory, fragmented, and opaque flood of information. To this end, this work presents a data-driven quantitative method for the sustainability assessment of product−service systems by integrating analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods to measure the sustainability of customized products and promote the Ind... [more]

In the era of rapid technological advancement and evolving industrial landscapes, embracing the concept of the factory of the future (FoF) is crucial for companies seeking to optimize efficiency, enhance productivity, and stay sustainable. This case study explores the concept of the FoF and its role in driving the energy transition and digital transformation within the automotive sector. By embracing advancements in technology and innovation, these factories aim to establish a smart, sustainable, inclusive, and resilient growth framework. The shift towards hybrid and electric vehicles necessitates significant adjustments in vehicle components and production processes. To achieve this, the adoption of lighter materials becomes imperative, and new technologies such as additive manufacturing (AM) and artificial intelligence (AI) are being adopted, facilitating enhanced efficiency and innovation within the factory environment. An important aspect of this paradigm involves the development a... [more]

In this work, issues of water separation and purification are addressed, where, in order to achieve the desired results, it is necessary to use several disciplines such as classical physics, biotechnology, automatic control, automation, and applications of industry 4.0. Further, the need for comprehensive and automated solutions for rainwater treatment in the agricultural sector is addressed. This research focuses on designing and implementing a system adapted to these needs using Siemens technologies. The methodology ranges from the design of the Piping and Instrumentation Diagram (P&ID) to the implementation of the interface, incorporating Siemens technologies for data acquisition, electrical connections, treatment programming, and PID controller design. The results show significant advances in the development of the system, highlighting the effectiveness of automation and the HMI-PLC human−machine interface in process monitoring and control. These findings support the viability of a... [more]

Companies actively seek innovative tools and methodologies to enhance operations and meet customer demands. Maintenance plays a crucial role in achieving such objectives. This study identifies existing models that combine Lean Philosophy and Industry 4.0 principles to enhance decision-making and activities related to maintenance management. A comprehensive literature review on key concepts of Lean Philosophy and Industry 4.0, as well as an in-depth analysis of existing models that integrate these principles, is performed. An innovative model based on the synergies between Lean Philosophy and Industry 4.0, named the Maintenance Management in Sustainable Operations (MMSO) model, is proposed. A pilot test of the application of the MMSO model on a conveyor belt led to an operational time increase from 82.3% to 87.7%, indicating a notable 6.6% improvement. The MMSO model significantly enhanced maintenance management, facilitating the collection, processing, and visualization of data via int... [more]

The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and the Metaverse can lead to sustainable productivity in industries. This paper presents a practical approach to implementing digital twins of a magnetic forging holder that was designed and manufactured in this project. Thus, this paper makes two important contributions: the first contribution is the manufacturing of the holder, and the second significant contribution is the creation of its digital twin. The holder benefits from a special design and implementation, making it a user-friendly and powerful tool in materials research. More specifically, it can be employed for the thermomechanical influencing of the structure and, hence, the final properties of the materials under deve... [more]

The expansion of end-to-end Industry 4.0 technologies in various industries has caused a technological shock in the mineral resource sector, wherein itsdigital maturity is lower than in the manufacturing sector. As a result of the shock, the productivity and profitability of raw materials extraction has begun to lag behind the industries of its deep processing, which, in the conditions of volatile raw materials markets, can provoke sectoral crises. The diffusion of Industry 4.0 technologies in the mining sector (Mining 4.0) can prevent a technological shock if they are implemented in all segments, including quarrying (Surface Mining 4.0). The Surface Mining 4.0 technological platform would connect the advanced achievements of the Fourth Industrial Revolution (end-to-end digital artificial intelligence technologies, cyber-physical systems and unmanned production with traditional geotechnology) without canceling them, but instead bringing them to a new level of productivity, resource con... [more]

With the arrival of Industry 4.0, interoperability has become a major subject for companies worldwide. It is a crucial asset that enables new technologies and possibilities (Industrial Internet of Things, predictive maintenance or traceability solutions). With the increasing importance of data in business use cases, companies are faced with a choice between two interoperability approaches to deal with the challenge of reconciling different domains: standardization and mediation. This paper presents an analysis of each approach and proposes a decision-making methodology based on the Analytic Hierarchy Process (AHP) that aims to help companies in choosing the most suitable solution to resolve interoperability challenges.

In enterprises, the management of detection methods usually refers to ensuring the identification of nonconformities. This management is incomplete and incompatible with the concept of sustainability (it ignores electricity consumption and costs). To date, no models have been developed to support the analysis of detection methods in terms of the relationship of efficiency−energy consumption. The purpose of the study was to develop proprietary software to analyse the level of efficiency of detection methods for casting products in the context of their energy intensity. The model supports effective management of the quality control process, optimising the relationship of product quality−energy intensity of the process. The model integrally combines detection methods, so it was possible to identify critical product nonconformities and analyse these methods to determine their effectiveness, time efficiency, cost efficiency, and energy intensity. As a result of the implications of the softw... [more]

Mining of minerals is an important part of the technical sciences, for which the certainty and unambiguity of terms and the correct application of definitions is an absolute requirement. At the same time, the expansion of Industry 4.0 technologies, both in practice and in scientific discussions, brings new terms to mining that are far from the original meaning. These terms include Data Mining and Mining 4.0, which, having a common digital core, refer to fundamentally different areas of human activity, and have the opposite meaning in relation to the use of resources (digital ones—endless, and the natural ones—finite). The indiscriminate use of the term “mining” is especially dangerous in the context of Mining 4.0, in which digital technologies allow the intensification of the exploitation of natural resources. This brief Perspective paper will show the role of terminology in Mining 4.0 and offer an interpretation of its relationship with Data Mining.

Human factor plays an important role in the implementation of the fourth industrial revolution (Industry 4.0). The concept of Industry 4.0 is poorly researched, particularly the social aspect. The authors have conducted a study to determine the level of preparation of employees for the introduction of technological changes. This study involved conducting a survey on a sample of 453 employees based in four organizations within the automotive industry. The respondents were thereafter divided into groups based on age and positions held. The employees’ knowledge of the Industry 4.0 technology was examined, and their openness to change and readiness to increase competence was determined. A causal relationship was found between knowledge and trust in technology. Employees’ fears associated with production automation were discussed. A group of production workers was found to be the least prepared to implement technology changes. Actions to improve the situation and potential consequences of i... [more]

I4.0 promotes a future in which highly individualized goods are mass produced at a competitive price through autonomous, responsive manufacturing. In order to attain market competitiveness, organizations require proper integration of I4.0 technologies and manufacturing strategy outputs (MSOs). Implementing such a comprehensive integration relies on carefully selecting I4.0 technologies to meet industrial requirements. There is little clarity on the impact of I4.0 technologies on MSOs, and the literature provides little attention to this topic. This research investigates the influence of I4.0 technologies on MSOs by combining reliable MCDM methods. This research uses a combination of fuzzy DEMATEL and fuzzy TOPSIS to evaluate the impact of I4.0 technologies on MSOs. The fuzzy theory is implemented in DEMATEL and TOPSIS to deal with the uncertainty and vagueness of human judgment. The FDEMATEL was utilized to identify interrelationships and determine criterion a’s weights, while the fuzz... [more]

Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. This study reviews the ML applications in the life cycle stages of biofuels, i.e., soil, feedstock, production, consumption, and emissions. ML applications in the soil stage were mostly used for satellite images of land to estimate the yield of biofuels or a suitability analysis of agricultural land. The existing literature have reported on the assessment of rheological properties of the feedstocks and their effect on the quality of biofuels. The ML applications in the production stage include estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage include analysis of engine performance and estimation of emissions temperature and composition. This study identifies the following trends: the most dominant ML method, the stage of life cycle getting the most usage of ML, the type of data used for the development of the ML-based models,... [more]

Leadership competencies are of crucial importance in every organisation as to a large extent they determine its success. This is especially evident in the time of Industry 4.0. Given this fact, the aim of our paper is to examine the relationship between leadership competencies and 4.0 leadership effectiveness. The heat and power plants industry was chosen as the subject of our research. The fuzzy-set qualitative comparative analysis (fs/QCA) was used as the research method. It enabled us not only to analyse particular variables, competences, and typical statistical relations between them, but we also revealed the patterns of causal relationships between particular variables. The key finding of our research was the juxtaposition of leadership competencies that are indispensable for 4.0 leaders in the CHP plants. We also found out that managerial competencies were not sufficient, and they should be supported by intellectual or socio-emotional ones.

The publication presents a picture of modern steelworks that is evolving from steelworks 3.0 to steelworks 4.0. The paper was created on the basis of secondary sources of information (desk research). The entire publication concerns the emerging opportunities for the development of the steel producers to Industry 4.0 and the changes already implemented in the steel plants. The collected information shows the support environment for changes in the steel sector (EU programs), the levels of evolution of steel mills, along with the areas of change in the steel industry and implemented investment projects. The work consists of a theoretical part based on a literature review and a practical part based on case studies. The work ends with a discussion in which the staged and segmented nature of the changes introduced in the analyzed sector is emphasized. Based on the three case studies described in the paper, a comparative analysis was conducted between them. When we tried to compare methods us... [more]

Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image re... [more]

Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to sustainability problems faced in the world. Thus, the proposed work aims to present an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the opera... [more]

Nowadays products are developed at a rapid pace, with shorter and shorter times between concept and go to market. With the advancement in technology, product designers and manufacturers can use new approaches to obtain information about their products and transform it into knowledge that they can use to improve the product. We developed the Poket Framework platform to facilitate the generation of product knowledge. In order to increase the reliability and safety in operation of electrical equipment, an evaluation is proposed, through tests and studies, using the original Poket Framework platform. Thus, several tests and studies were performed, which included testing and analyzing the correct integration in several use cases and remote data acquisition, and testing and analysis of the Poket Framework using literature established data sets of household appliances and electrical systems. Possible evolutions and Poket platform extensions are also considered.

Digital technologies enable companies to build cyber-physical systems (CPS) in Industry 4.0. In the increasingly popular concept of Industry 4.0, an important research topic is the application of digital technology in industry, and in particular in specific industry sectors. The aim of this paper is to present the tools used in the steel industry in Poland on its way to the full digitalisation that is needed for the development of Industry 4.0. The paper consists of two parts: a literature review and a practical analysis. The paper provides the background information about digitalisation using digital tools in the steel industry in Poland. The paper was prepared based on secondary information and statistical data. The object of the research is the Polish steel sector. This study assumes that digitalisation is the main area of innovation in the steel industry. The digitalisation determines the creation of new or modified products, processes, techniques and expansion of the company’s inf... [more]

The growth of the renewable energy industry is happening at a swift pace pushed, by the emergence of Industry 4.0. Smart technologies like artificial intelligence (AI), Big Data, the Internet of Things (IoT), Digital Twin (DT), etc. enable companies within the sector of renewable energies to drastically improve their operations. In this sectoral context, where upgraded sustainability standards also play a vital role, it is necessary to fulfil the human capital requirements of the imminent technological advances. This article aims to determine the current skills of the renewable energy industry workforce and to predict the upcoming skill requirements linked to a digital transition by creating a unified database that contains both types of skills. This will serve as a tool for renewable energy businesses, education centers, and policymakers to plan the training itinerary necessary to close the skills gap, as part of the sectoral strategy to achieve a competent future workforce.

The United Nations established 17 Sustainable Development Goals (SDGs), and the fulfillment of the 7th, defined as “Ensure access to affordable, reliable, sustainable, and modern energy for all”, requires energy industry transitions and digital transformations, which implies that diverse stakeholders need to move fast to allow the growth of more flexible power systems. This paper contains the case report that addresses the commercial digital transformation process developed at AES Colombia, through the implementation of a modern platform based on specialized applications that use Industry 4.0 tools. The Chivor hydropower project, a 1000-MW powerplant that covers 6% of Colombia’s demand, which is owned by AES Colombia and constitutes its primary asset, is first described. Then, a description of Colombia’s complex market (energy matrix, trading and dispatch mechanisms, and future projects) is presented. Then, the methodology followed for the digital transformation process using modern to... [more]

Operation and maintenance constitute a substantial share of the lifecycle expenditures of an offshore renewable energy farm. A noteworthy number of methods and techniques have been developed to provide decision-making support in strategic planning and asset management. Condition monitoring instrumentation is commonly used, especially in offshore wind farms, due to the benefits it provides in terms of fault identification and performance evaluation and improvement. Incorporating technology advancements, a shift towards automation and digitalisation is taking place in the offshore maintenance sector. This paper reviews the existing literature and novel approaches in the operation and maintenance planning and the condition monitoring of offshore renewable energy farms, with an emphasis on the offshore wind sector, discussing their benefits and limitations. The state-of-the-art in industrial condition-based maintenance is reviewed, together with deterioration models and fault diagnosis and... [more]