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This study provides an up-to-date review of additive manufacturing (AM) technologies and guidance for selecting the most appropriate ones for specific applications, taking into account the main features, strengths, and limitations of the existing options.

A literature review on AM technologies was conducted to assess the current state-of-the-art. This was followed by a closer examination of different AM machines to gain a deeper insight into their main features and operational characteristics. The conclusions and data gathered were used to formulate a classification and decision-support framework.

The findings indicate the building blocks of the selection process for AM technologies. Furthermore, this work shows the suitability of the existing AM technologies for specific cases and points to opportunities for technological and decision-support improvements. Lastly, more standardization in AM would be beneficial for future research.

The proposed framework offers valuable support for decision-makers to select the most suitable AM technologies, as demonstrated through practical examples of its utilization. In addition, it can help researchers identify the limitations of AM by pinpointing applications where existing technologies fail to meet the requirements.

The study offers a novel classification and decision-support framework for selecting AM technologies, incorporating machine characteristics, process features, physical properties of printed parts, and costs as key features to evaluate the potential of AM. Additionally, it provides a deeper understanding of these features as well as the potential opportunities for AM and its impact on various industries.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

The industrial application of continuous glass fabric-reinforced polymer composites (GFRPCs) is growing; however, the manufacturing boundedness of complex structures and the high cost of molds restrict their use. This research proposes a three-dimensional (3 D) printing process for GFRPCs that allows low-cost and rapid fabrication of complex composite parts.

The composite is manufactured using a digital light processing (DLP) based Vat-photopolymerization (VPP) process. For the composites, suitable resin material and glass fabrics are chosen based on their strength, stiffness, and printability. Jacob's working curve characterizes the curing parameters for adequate adhesion between the matrix and fabrics. The tensile and flexural properties were examined using UTM. The fabric distribution and compactness of the cured resin were analyzed in scanning electron microscopy.

The result showed that the object could print at a glass fabric content of 40 volume%. In DLP-based VPP printing technology, the adequate exposure time was found to be 30 seconds for making a GFRPC. The tensile strength and Young's modulus values were increased by 5.54 and 8.81 times, respectively than non-reinforced cured specimens. The flexural strength and modulus were also effectively increased to 2.8 and 3 times more than the neat specimens. In addition, the process is found to help fabricate the functional component.

The experimental procedure to fabricate GFRPC specimens through DLP-based AM is a spectacular experimental approach.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

This study aims to explore human–machine interactions in the process of adopting artificial intelligence (AI) based on the principles of Taylorism and digital Taylorism to validate these principles in postmodern management.

The topic has been investigated by means of a case study based on the current experience of Carrozzeria Basile, a body shop born in Turin in 1970.

The Carrozzeria Basile’s approach is rooted in scientific management concepts, and its digital evolution is aimed at centring humans, investigating human–machine interactions and how to take advantage of both of these.

The research contributes to both Taylorism management and the literature on human–machine interactions. A unique case study represents a first step in comprehending the phenomenon but could also represent a limit for the study.

Practical implications refer to the scientific path to facilitate the implementation and adoption of emerging technologies in the organisational process, including employee engagement and continuous employee training.

The research focuses on human–machine interactions in the process of adopting AI in the automation process. Its novelty also relies on the comprehension of the needed path to facilitate these interactions and stimulate a collaborative and positive approach. The study fills the literature gap investigating the interactions between humans and machines beginning with their historical roots, from Taylorism to digital Taylorism, in relation to an empirical scenario.

The purpose of this paper is to provide an integrative picture of the state of the art of the literature on digitalisation of small and medium-sized enterprises (SMEs) as an enabler for their internationalisation process and as a comprehensive view of the specific domains impacted by digital technologies as well as their repercussions on the international outreach.

A systematic review which leverages a descriptive analysis of extant literature and an axial coding technique has been conducted to shed light on the current knowledge and to identify primary research areas and future research lines.

The research indicates that digitalisation impacts the internationalisation of SMEs in three specific domains: (1) internationalisation through the adoption of information and communication technologies (ICT) technologies and e-commerce platforms; (2) international expansion through the digitalisation of value chain activities and (3) international outreach through knowledge acquisition on digital platforms.

The value of this study is threefold. First, the authors attempt to systematically review the literature on SMEs digitalisation and internationalisation and provide a holistic perspective on the intertwining of these two research streams. Second, the authors propose a novel conceptualisation on the dimensions of SMEs digitalisation as enablers to internationalisation. Third, the authors put forward promising future lines of research.

1. Digitalisation represents a pivotal strategy that allows companies to build new strategic capabilities and is a propeller for SMEs internationalisation.

2. Through e-commerce, SMEs could compete at the same level of multinational companies but enduring lower costs of expansion.

3. Digital platforms allow SMEs to enhance the learning processes about international markets through an immediate access to relevant information.

4. Digital entrepreneurship has enabled SMEs to develop new configurations of value chain activities, evolving their business model or reaching new markets.

5. SMEs are changing the “business as usual” paradigm offering digital tools to build modular architectures that are scalable and agile in their evolution ability.

Digitalisation represents a pivotal strategy that allows companies to build new strategic capabilities and is a propeller for SMEs internationalisation.

Through e-commerce, SMEs could compete at the same level of multinational companies but enduring lower costs of expansion.

Digital platforms allow SMEs to enhance the learning processes about international markets through an immediate access to relevant information.

Digital entrepreneurship has enabled SMEs to develop new configurations of value chain activities, evolving their business model or reaching new markets.

SMEs are changing the “business as usual” paradigm offering digital tools to build modular architectures that are scalable and agile in their evolution ability.

Continuous advances in digital technology and business models digitalization have decisively altered the entrepreneurial landscape redefining the aims and the requirements of entrepreneurial education to suit the new digital reality in entrepreneurship. The purpose of this study is to shed light in a neglected niche in the intersection between digital entrepreneurship (DE) and entrepreneurship education and outline DE education as field of research. Given that the interdisciplinary growth of DE research outpaces instructional designs in terms of required knowledge and skills, it is important to document how entrepreneurship education responds to the ongoing integration of emerging digital technologies with the entrepreneurial process. Moreover, the introduction of a DE education conceptual framework would facilitate the discussion on theoretical and practical implications and promote new conceptualizations in future research, new educational approaches and new curriculum designs.

A concept-driven, semi-structured developmental literature review methodology, based on grounded theory and reinforced with increased systemization, was used for the identification and analysis of peer-reviewed articles. Previous literature reviews were used to define the search keywords. The articles from three databases were carefully selected, based on protocol and strict eligibility criteria. The papers in the final set were classified in four primary dimensions, synthesized from several sub-streams of research. Each sub-stream highlighting a different view of DE education emerged through open, axial and selective coding of articles. The combined perspectives of these dimensions resulted in a new DE conceptual framework.

Thematic interrelation between the studies examined, revealed an ample view of the various schools of thought in the research field, offering also a better understanding on how entrepreneurial education addresses the practical requirements of digital entrepreneurship. A four dimensional conceptual framework produced highlights pedagogy and learning, success factors and barriers, behavioral approach and ecosystems as the current trends of research. Also, directions for future research are proposed.

The classification framework proposed can serve as a roadmap for entrepreneurship educators seeking efficient pedagogical practices focused on the transfer of knowledge and training on the new skills required by DE and motivate future researchers aiming to propose novel educational interventions.

Although digital entrepreneurship research has gained significant momentum in recent years, little attention is paid to its increased educational requirements. The body of knowledge develops in an uncontrolled and fragmented manner, and the systematic study of the field from an educational perspective was missing. This study offers a representative picture of the topic, highlights current trends of research, synthesizes literature from different disciplinary origins, provides linkages between unconnected streams of research and points out research gaps. Finally, it proposes a conceptual framework to circumscribe DE education as a field of study and serve as a basis to help future research move forward.

The purpose of this paper is to evaluate the causal relationship between Lean practices and team performance. Specifically, the authors tried to demonstrate which practices act as enablers of continuous improvement and waste elimination and what is their impact on team performance.

A survey was carried out in a Higher Education Institution (HEI) in Southern Brazil. The authors obtained a sample of 785 respondents. The data analysis procedures involved confirmatory factor analysis and structural equations modeling.

The results of the research provided support for the positive influence of continuous improvement on waste elimination and of these two practices on team performance. In addition, empirical support was obtained for the effect of leadership support, employee involvement and internal process customers on continuous improvement.

Data collection was carried out online, so we were not able to maintain full control of the research respondents. This research generates relevant insights for decision-makers in the HEI environment, especially concerning Lean practices and team performance. The effects analyzed are even more relevant given the pandemic context.

This study shows how some higher education Lean practices can positively affect continuous improvement and better team performance. The results raise important insights for decision-makers to offer better higher education public services, especially given the context and changes imposed by the pandemic situation.

This paper initiates the discussion about enablers of continuous improvement and waste elimination in HEI and demonstrates their impact on team performance.

Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures.

The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations.

The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16.

The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

Digitalization is affecting business management and pushing for new strategies, innovative products, new ways to communicate with stakeholders and new channels. This phenomenon is unavoidable, and companies have to face it in a holistic and integrated way. One holistic and interconnected approach, when studying enterprise challenges, is represented by the business process management method, a fitting mechanism when digitalization needs to be amalgamated in business practices, enhancing the intellectual capital (IC), therefore, this study researches digitalization under business process lens, in a sample of small and medium enterprises (SMEs), that constitute an under-explored set, as regard digitalization, process management and IC. The research aims to explore the digital tools and business processes link and the related impact on performance, benefits and IC.

In exploring digitalization, a sample of Italian SMEs was scrutinized. The data were elaborated using two types of tests: (1) the binomial tests for the categorical questions and (2) the zeta test was used for quantitative variables. Furthermore, the partial least square (PLS)-SEM model was applied.

Findings reveal that some digital tools are more adopted in the sample analysed, and also some particular digital tools are more inclined to support certain business processes. Furthermore, not only performance benefits emerge, but also benefits in terms of better communication and faster decisions, supporting the decision making process of managers, also considering that business processes approach is one way to manage IC.

Thanks to the conducted research it is possible to make aware managers and owners of SMEs to consciously choose the right type of digitalization investments, without neglecting training programme, to realize the company digital transformation, providing a map and bearing in mind the value added creation, protecting their IC.

The paper's originality is represented by the contribution in opening the black box about digitalization, business process management and IC in small and medium companies.