Healthcare 4.0: Trends, Challenges and Benefits

The Fourth Industry Revolution, known as Industry 4.0, refers to the forces that are transforming industry, including the healthcare industry, where it has been termed Healthcare 4.0. Though lagging other industries in the adoption of new innovative technologies, the healthcare industry is embracing the potential benefits that arise from new innovative technologies. New trends revealed both in the academic literature and by industry practice show that researchers and practitioners are becoming more aware of the benefits technology can bring to an industry as complex as the healthcare industry. The object of the study is to identify the challenges, trends and gaps in the existing body of research with regard to Healthcare 4.0. In this study, a systematic literature review on Healthcare 4.0 research papers was conducted to identify trends, challenges and the perceived benefits that may arise from it. This paper found that there is a need to conduct more empirical studies in this area. It, further, identified the need to implement practical procedures in the industry to get feedback from patients and healthcare participants in order to promote the adoption of new Healthcare 4.0 technologie

Industry 4.0:use of digitalization in healthcare

The primary objective of this chapter is to examine the AI applications for healthcare 4.0. Using a wide range of contemporary technologies, such as digitization, artificial intelligence, user response data (ergonomics), human psychology, the internet of things, machine learning, big data mining, and augmented reality, one of the great success stories of our day is healthcare. Worldwide life expectancy has increased due to the tremendous advancements in medical research. But when people live longer, healthcare systems must deal with more people needing their services, more money spent on them, and a staff that finds it more challenging to care for patients. A healthy, productive society depends heavily on the healthcare industry, making it one of the most critical industries in the larger big data environment. Artificial intelligence (AI), which builds on automation, has the potential to transform healthcare and assist in addressing some of the issues mentioned above. AI can support healthcare professionals, including physicians and nurses, in their day-to-day jobs. Artificial intelligence (AI) can improve patient outcomes by enhancing the quality of life and preventive care and producing more accurate diagnoses and treatment regimens. This book provides an overview of the most recent advancements in artificial intelligence (AI) applications in biomedicine, encompassing pharmaceutical processing, disease diagnosis, patient monitoring, biomedical information, and biomedical research. A summary of the most recent developments in the use of AI in healthcare is also provided, along with a road map for creating safe, dependable, and efficient AI systems and a discussion of potential future directions for AI-assisted healthcare systems. Numerous uses of AI exist in the medical field. Healthcare 4.0 has brought about a paradigm shift in the healthcare industry, drawing inspiration from Industry 4.0. Therefore, how the digital revolution in healthcare will affect the quality of medical care is still being determined. This study results will help the new researchers and healthcare institutions

Time to be responsive in the process industry: a literature-based analysis of trends of change, solutions and challenges

The current uncertain and volatile business context is challenging firms worldwide, leading to the need to be responsive at a competitive cost. This trend is so substantial that it even affects industries traditionally competing in rather stable contexts, such as the process industry. Although the process industry includes multiple sectors with different technologies and processes, these share several aspects that make the industry as a whole distinctive to the discrete manufacturing industry. Based on a literature review, this study identifies and describes trends leading the process industry to the need for responsiveness, corresponding solutions to accommodate the need, and related challenges hindering the industrialization and diffusion of solutions in this industry. This study shows that trends, such as the uncertainty and volatility of market requirements, are challenging the process industry to develop reconfigurability solutions across multiple production levels. The development of reconfigurability solutions is hindered by modularity, integrability, co-ordination and collaboration challenges

Ontologies for Industry 4.0

The current fourth industrial revolution, or ‘Industry 4.0’ (I4.0), is driven by digital data, connectivity, and cyber systems, and it has the potential to create impressive/new business opportunities. With the arrival of I4.0, the scenario of various intelligent systems interacting reliably and securely with each other becomes a reality which technical systems need to address. One major aspect of I4.0 is to adopt a coherent approach for the semantic communication in between multiple intelligent systems, which include human and artificial (software or hardware) agents. For this purpose, ontologies can provide the solution by formalizing the smart manufacturing knowledge in an interoperable way. Hence, this paper presents the few existing ontologies for I4.0, along with the current state of the standardization effort in the factory 4.0 domain and examples of real-world scenarios for I4.0.Peer ReviewedPostprint (published version

Scheduling in the industry 4.0: a systematic literature review

Industry 4.0 is characterised for being a new way of organising the supply chains, coordinating smart factories that should be capable of a higher adaptivity, making them more responsive to a continuously changing demand. This paper presents a Systematic Literature Review (SLR) with three main objectives. First, to identify in the literature on Industry 4.0, the need for new job scheduling methods for the factories of the digital era. Second, to identify in the literature of scheduling, which of these issues have been accomplished and what are the most critical gaps. Third, to propose a new research agenda on scheduling methodology, that fulfils the needs of scheduling in the field of Industry 4.0. The results show that literature related to the subject of study is rapidly growing and the needs of new methods for job scheduling in the digital factories concern two main ideas. First, the need to create and implement a digital architecture where data can be appropriately processed and second, the need of giving a decentralised machine scheduling solution inside such a framework. Although we can find some studies on small production lines, research with practical results remains scarce in the literature to date

Revolutionizing Healthcare Organizations with Operational Excellence and Healthcare 4.0: A Systematic Review of the State-of-the-Art Literature

Purpose- This study examines current research on the relationship between Operational Excellence and Healthcare 4.0 for healthcare organizations. Design/Methodology/Approach- We have performed a systematic literature review of 102 documents published between 2011 to 2022 from the Scopus database to identify the research trends on Operational Excellence and Healthcare 4.0. Through a descriptive bibliometric analysis, we have highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities, and subject area analysis. Further, through content analysis, we have identified four clusters and proposed directions for future research of each identified cluster. Findings- Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and Healthcare 4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and Healthcare 4.0 technologies in dealing with various healthcare delivery aspects. We concluded our analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study. Originality- The article is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and Healthcare 4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study

An XML-based Factory Description Language for Smart Manufacturing Plants in Industry 4.0 : Factory Description Language

Industry 4.0 revolution concerns the digital transformation of manufacturing and promises to answer the ever-increasing demand of product customisation and manufacturing flexibility while incurring low costs. To perform the required factory reconfiguration, a computationally demanding optimisation process has to be executed to find favourable solutions in a relatively short time. While previous research focused on planning and scheduling of smart factories based on cloud-based optimisation, little attention has been paid to effective approaches to describe the targeted factory, the required products and the production processes. However, these matters are fundamental for the optimisation engine to be correctly and efficiently performed. This paper presents an XML-based factory modelling language to effectively describe the above data for a given factory and commodity order and to provide a convenient interface for altering the input information. Finally, two real-world manufacturing plants are provided to illustrate the feasibility of the proposed description language