Abstract
Industry 4.0 primarily centers around widespread digitalization, whereas Industry 5.0 aims to combine modern technologies with human actors, emphasizing a value-driven strategy rather than a technology-centric one. The primary goals of the Industry 5.0 paradigm, which were not emphasized in Industry 4.0, highlight the importance of not only digitizing production but also ensuring its resilience, sustainability, and human-centeredness. Industry 5.0 is a project focused on value rather than technology, aiming to promote technological transformation with a specific goal in mind. In industry 5.0, which focuses on real-world applications of AI-based technology such service robots, the usage of AI is clearly seen in several sectors like tourism, education, manufacturing, and retail. Recent research highlights the importance of interactions between humans and machines, and how they contribute to creating value by enhancing their own capacities. The primary objective of human-machine collaboration is to enhance the well-being of stakeholders, including consumers, employees, and society. This chapter focuses on human -machine collaboration, practical implementation of human-AI collaboration, review of literature on human-AEI frameworks, advantages and disadvantages of collaboration between human and AI, human- AI collaboration in education and finally comes the conclusion.
TopIntroduction
There is a need for a human-centric approach, which is referred to as Industry 5.0 (European Comission, 2023). Although there is a strong emphasis on digitization and automation, human operators and technicians will continue to be a crucial asset for manufacturers in order to maintain competitiveness, particularly for tasks that demand adaptability, customization, and originality (S. Nahavandi, 2019). In the future, when factories become fully automated and digitalized, humans will have less physical jobs. However, they will be responsible for more decision making and problem-solving activities inside the increasingly complex socio-cyber-physical manufacturing system.
Manufacturing industries must confront swift technological changes, the demand for customized production on a large scale, and the necessity for improved manufacturing techniques. In order to enhance productivity, it is imperative to integrate robots with the human mind and foster a strong sense of necessity (S. Nahavandi, 2019). To solve this issue, digitalization is employed to facilitate collaboration among individuals at the plant level, focusing on operations that revolve around human needs, such as establishing production units, ensuring work safety, conducting maintenance, and performing repairs. The prevailing requirement in this field can be succinctly described as follows: (a) The cooperative endeavors are organized or documented in unorganized formats. While there are basic data entry applications available, the level of acceptance within the industry could be improved for various reasons. These reasons include unique working conditions that may require the use of smart glasses or the ability to adapt to changes in the process. Additionally, these applications are primarily limited to one-on-one interactions between humans and machines. However, the main issue lies in the requirement for additional methods and solutions to effectively coordinate and digitize collaborative activities involving multiple participants in real-time. In the future, humans, IoT machines, and AI services will collaborate in many processes, such as major repairs in production lines. (b) The lack of easily accessible methods for organizing and reusing gathered process data by other parties (such as plant technologists) and AI services. Moreover, there is a distinct professional inclination for users to not only function as operators, but also as active participants in the creation of information inside digital service frameworks. They should have the capability to directly access and contribute to the company's knowledge base from their place of work.
Key Terms in this Chapter
The Resource Description Framework (RDF): A general framework for representing interconnected data on the web.
Human-Computer Interaction (HCI): A multidisciplinary field of study focusing on the design of computer technology and, in particular, the interaction between humans (the users) and computers.
General Data Protection Regulation (GDPR): This establishes the general obligations of data controllers and of those processing personal data on their behalf (processors).
Human-Machine Interaction (HMI): This refers to the communication and interaction between a human and a machine via a user interface.
Extensible Markup Language (XML): This lets you define and store data in a shareable manner. XML supports information exchange between computer systems such as websites, databases, and third-party applications.
The W3C Web Ontology Language (OWL): A computational logic-based language such that knowledge expressed in OWL can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit.
Manufacturing Execution Systems (MES): A comprehensive, dynamic software system that monitors, tracks, documents, and controls the process of manufacturing goods from raw materials to finished products.