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This research paper examines the evolution of human-machine interfaces (HMIs) in the manufacturing and logistics sectors inthe context of Industry 5.0 (I5.0). I5.0 introduces a human-centered paradigm, and as digitalization transforms processes in thesedomains, human-machine interaction is undergoing a notable shift. Yet, there is a lack of I5.0 HM...
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... gain a better understanding of applying the abstract requirements in practice and of the challenges involved, a practical case study approach was used. Two use cases were identified within in-house industry projects and are presented in Table 2. Design of a digital and ai-assisted flexible assembly line to increase product and process innovation [31,32] Assembly planning Touchscreen (GUI/NUI) Intuition, knowledge management, communication, quality assurance Three experienced HMI designers conducted a workshop session to collaboratively brainstorm and explore implementation strategies for each requirement. ...Similar publications
Growing awareness of environmental issues and the constant pressure to reduce greenhouse gas emissions have prompted the automotive industry to research and develop sustainable solutions. Battery electric vehicles (BEVs) are considered as a key element in reducing dependence on fossil fuels and minimizing driving-related emissions from road transpo...
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... human-related risks, including safety, ethics, and privacy [8,9] or challenges in innovation processes, such as lack of human-centered design in manufacturing and logistics or lack of user-centered innovation in real estate [10,11]. In the current business context, these and other challenges, like the need for a new-skilled workforce, represent new opportunities for higher education institutions (HEIs). ...
... There also seems to be a need for research and knowledge on how co-teaching initiatives can respond to the challenges related to digitalization [25] (p. 10). ...
Education for sustainability is one of the big challenges that higher education institutions (HEIs) face in the context of Society 5.0, which promotes human-centered design solutions. Therefore, solutions for collaboration between humans and technology in organizations are needed, as Industry 5.0 suggests. However, the concept of Engineering Education 5.0 promotes engineers who are able to solve global changes and are endowed with knowledge, skills, and a mindset for sustainability. This paper aims to highlight the transformative potential of international multidisciplinary consortia in HEIs, both for teaching and learning practices. Using a methodology that combines autoethnography and narrative analysis based on qualitative feedback received from participants, the paper presents lessons learned, good practices, and pilot co-teaching experiences within two Erasmus+ cooperation partnerships. This paper describes the educational process during joint learning sessions based on co-teaching and art-based training, showing educational practices for curricula development in engineering education. The findings show that cultivating teachers’ mindsets, skills, and pedagogical approaches can empower students to become active agents in fostering a more sustainable society and suggest that both ergonomics competencies and soft skills (e.g., self-awareness, creativity, collaboration) are crucial sustainability-oriented competencies, developed within international collaborative and enjoyable learning environments based on transformative learning experiences.
... Although natural language querying has been previously explored, existing implementations rely on predefined queries rather than leveraging the advanced capabilities of LLMs [21]. This capability would not only enhance access to real-time monitoring and data analysis but also reduce dependency on domain specialists, fostering more efficient decision-making and improved productivity in complex industrial environments [22]. In the context of self-service or citizen analytics, this shift also empowers users to autonomously explore data and generate insights, reducing dependency on data scientists or IT specialists. ...
... All applications mentioned above illustrate how LLMs enhance HMI by streamlining workflows and reducing the need for domain-specific expertise. Furthermore, such capabilities reduce cognitive load and improve decision-making efficiency [22]. Despite their potential, deploying LLMs in manufacturing requires addressing challenges such as domain-specific data training, real-time processing, and ensuring interpretability and trust to meet industrial reliability standards [18]. ...
Modern production systems generate vast amounts of process data that hold valuable insights for optimizing manufacturing processes. However, production personnel often face the challenge of interpreting this information, especially when dealing with unexpected anomalies or when insights beyond standard reports are required. This challenge arises both from the complex data structures in which the data is provided, and the lack of analytical expertise. This research introduces an approach that leverages Large Language Models (LLMs) to facilitate natural language queries and flexible data visualization, allowing production personnel to interact effortlessly with complex datasets. Tested on process data from an industrial extrusion process that have been enhanced using data augmentation techniques, the proposed concept demonstrates the capability to retrieve relevant data and present tailored visualizations based on simple user prompts. The results demonstrate that LLM-driven data exploration can support production personnel and help overcome the challenges described, which arise from the complex nature of manufacturing data and the specialized domain knowledge required. Future work will concentrate on improving accuracy, robustness, and further integration of domain-specific knowledge, aiming to provide a more reliable and accessible tool for various industrial environments.
... Industry 4.0 focused on employing enabling technologies to ramp up productivity, optimise processes and foster flexibility. Its novel counterpart, Industry 5.0, endeavours to augment human skills through the same technologies whilst prompting sustainability and human-centricity [1]. Cobots, a key enabling technology, have revolutionised operators' interaction with robots which were previously physically segregated on the shopfloor [2]. ...
Human-centricity is at the frontier of the novel Industry 5.0 paradigm, in which the well-being of the operator is not solely acknowledged but is actively heeded to. One application of this is in human-robot collaboration (HRC). Working in proximity to a collaborative robot has stemmed productivity, flexibility and assistance, but has also amassed concerns for safety. Designing physically safe HRC workstations is well established in scholarly work and international standards. However, attention must also be directed towards the cognitive facet of safety. Unlike physical safety requirements such as speed or distance, which are reasonably quantifiable; quantification of cognitive requirements may not be as straightforward, owing to the subjectivity of user emotions. Consequently, this work contributes a Kansei Engineering approach geared towards identification and quantification of requirements related to cognitive safety requirements in HRC workstations. The outcomes of this study shall then be implemented within a broader Axiomatic Design (AD) of a physically and cognitively safe HRC workstation, underlining the suitability of using Kansei Engineering to quantify cognitive requirements in preparation of Axiom 1 and Axiom 2 of the Axiomatic Design process.
... This process is not only reshaping employees' work practices and the broader organization of work but also underscores the critical importance of integrating human-cantered approaches alongside technological advancements [2]. In particular, access to new technologies has in some cases fundamentally changed the conditions for how employees work, learn and interact [3] and how work must be organized as a result, resulting in numerous changes in the areas of working life and health, the use of information and communication technology or organizational hierarchies, all of which are of a work-organizational nature (cf. [4]). ...
... According to several studies [12], [23], [15], the introduction of intelligent logistics solutions will create and revolutionize a profitable, sustainable and environmentally conscious logistics industry. Bhargava et al [22] focused on digital transformation in logistics. ...
... Human-Machine Interfaces (HMIs): facilitate human interaction with machines with ease (Adel, 2023;Panter et al., 2024). Intend interfaces use natural language processing (NLP), gesture recognition, and brain-computer interfaces (BCIs) in order to establish simple and effective communication pathways. ...
Industry 4.0 brought with it by the next-gen Industry 5.0 and Society 5.0 paradigms, catalysed by Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies. These advances have the benefit of encouraging sustainability, improving output, and updating manufacturing. By enabling self-decision, continuous monitoring, and predictive maintenance with the processing of large data, AI is dramatically reducing downtime and associated costs of system downtime. As a result, ML algorithms, in light of their applicability for continuous learning and adaptation, have contributed to enriching product quality, streamlining supply networks and okaying personalized customer experiences. Neural networks are also being leveraged to improve computer vision and speech capabilities, for applications such as smart automation and human-robot cooperation in challenging industrial contexts. Industry 5.0 truly puts humans back at the centre of innovation. It is aimed to create an evolved society in which AI, ML, and DL are fused with the digital and physical world Society 5.0. The integration aims to address a plethora of societal challenges: environmental sustainability, health and ageing population, among others. It is a convergence of these said technologies that lead to a paradigm shift towards more resilient, adaptive, and sustainable industrial ecosystems. This paper aims to address these questions in a systematic way to offer a comprehensive view of what the future industrial landscape could look like leveraging the promise of Industry 4.0 and Industry 5.0 thus, and more opportunities to embrace intelligent and sustainable industries of tomorrow.
... An option to overcome the relevant difficulties can be the use of less powerful HMI devices, which do not add excess power to the project and thereby reduce the cost of project implementation. This is the approach used in work [4], in which the authors, scientists and engineers, determined that optimizing the number of tags affects the clarity and convenience of the interface and allows the use of simpler HMI devices. Also, in work [5] it was determined that it is necessary to comply with certain requirements regarding the design principles of modern HMIs. ...
The object of this study is modern Human-Machine Interfaces (HMI) and SCADA systems in the industry. The subject of research is techniques for optimizing the number of tags (variables) in the SCADA/HMI environment to enhance resource utilization efficiency. One of the challenges in creating SCADA/HMI-based solutions can be the number of tags (variables) in the runtime environment. A large number of tags can lead to a problem of limited available resources. The technique presented here allow for the optimization of the number of tags used in Human-Machine Interface systems built with SCADA software and operator panels in combination with Programmable Logic Controllers (PLCs). An evaluation of the efficiency of techniques for reducing the number of HMI tags was conducted on an experimental configuration consisting of objects such as discrete input/output, analog input/output, actuators such as valves with discrete/analog control, and drives with frequency converters. The optimization coefficient, defined as the ratio of the number of input/output tags used directly to the number of tags after applying the optimization principle, was used as the efficiency criterion. Depending on the techniques and their combinations, the criterion values reached orders of 4, 10, and in one case even more than 100. These values are explained by the application of multiplexing approaches and various packing techniques. The advantages and disadvantages of the reported techniques, as well as their application limitations, have been identified. Some techniques are suitable only for specific tasks. These techniques could be applied in practical implementation when designing modern high-efficiency Human-Machine Interfaces under conditions of limited resources.
... ology. The digital twin of the human being is the counterpart of the human being that reflects multidimensional information to realise bilateral interaction between the physical and virtual world (Wang et. al., 2024). It seems quite possible when elements such as ethical principles, integration, empowerment, design and ergonomics are taken care of (Panter et. al., 2024). ...
The research deals with the social evolution of mankind in the historical process and the concept of "Society 5.0", which has recently come to the fore in this evolution. Starting from hunter-gatherer society in the history of mankind, it has passed through the stages of agriculture, industry and information society, and today, with technological advances, a new phase called "Society 5.0" has been transitioned. Society 5.0 is a model of society, especially developed under the leadership of Japan, in which technologies such as artificial intelligence, big data and the Internet of Things are integrated to improve human life. The research examines in detail the reasons, elements, concerns and achievements of this new society model, while emphasising the sustainable development goals.
... Industry 4.0's influence stems from its drive to integrate digital and industrial advanced technologies in manufacturing, resulting in higher efficiency and flexibility [1]. The manufacturing industry is now undergoing another paradigm shift called Industry 5.0, which seeks to have digital technologies complement human capabilities to enhance sustainability and social inclusion [2]. Collaborative robots (cobots), one of the key emerging industrial technologies of Industry 4.0, allow for collaboration with operators in close proximity without any physical barrier for safety separation [3]. ...
