Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas

Adel, Amr

doi:10.1186/s13677-022-00314-5

Cited by 274 publications

(142 citation statements)

References 145 publications

(169 reference statements)

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“…However, the next phase of industrial development, known as industry 5.0, is expected to bring about even more significant changes by integrating artificial intelligence (AI) and machine learning. These will enable factories not only to coordinate and communicate with each other but also to adapt and learn from their experiences, leading to more flexible and efficient production processes [ 1 , 2 , 3 , 4 , 5 ]. One key aspect of industry 5.0 is using prognostics and health management (PHM) systems.…”

Section: Introductionmentioning

confidence: 99%

LSTM-Autoencoder for Vibration Anomaly Detection in Vertical Carousel Storage and Retrieval System (VCSRS)

Seok

Kareem

Hur

2023

Sensors

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Industry 5.0, also known as the “smart factory,” is an evolution of manufacturing technology that utilizes advanced data analytics and machine learning techniques to optimize production processes. One key aspect of Industry 5.0 is using vibration data to monitor and detect anomalies in machinery and equipment. In the case of a vertical carousel storage and retrieval system (VCSRS), vibration data can be collected and analyzed to identify potential issues with the system’s operation. A correlation coefficient model was used to detect anomalies accurately in the vertical carousel system to ascertain the optimal sensor placement position. This model utilized the Fisher information matrix (FIM) and effective independence (EFI) methods to optimize the sensor placement for maximum accuracy and reliability. An LSTM-autoencoder (long short-term memory) model was used for training and testing further to enhance the accuracy of the anomaly detection process. This machine-learning technique allowed for detecting patterns and trends in the vibration data that may not have been evident using traditional methods. The combination of the correlation coefficient model and the LSTM-autoencoder resulted in an accuracy rate of 97.70% for detecting anomalies in the vertical carousel system.

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Section: Introductionmentioning

confidence: 99%

LSTM-Autoencoder for Vibration Anomaly Detection in Vertical Carousel Storage and Retrieval System (VCSRS)

Seok

Kareem

Hur

2023

Sensors

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“…Human‐robot co‐working is one of the emerging themes (Demir et al, 2019) and bioeconomy is the second one (Müller, 2020). In I5.0, humans are expected to come back into industrial production with collaborative robots to provide value‐added tasks in production, leading to mass customization and personalization (Adel, 2022). The purpose is to leverage the creativity of humans in conjunction with effective and intelligent systems, machines, and robots to design manufacturing solutions for mass customization (Nahavandi, 2019).…”

Section: Introductionmentioning

confidence: 99%

Industry 5.0 and the future of sustainable manufacturing: A systematic literature review

et al. 2023

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Industry 5.0 (I5.0) is all set to come into the limelight when Industry 4.0 (I4.0) has not yet fully matured and still gaining ground in growing economies. The general notion of I5.0 is discussed in the existing literature on the subject domain, but there are no adequate studies in the literature that examine its implications. Therefore, systematic literature review method is adopted to: explore the understanding of I5.0; identify the opportunities for I5.0; highlight the challenges in I5.0 implementation; investigate the effects of I5.0 on economic, environmental, and social pillars of sustainability; and propose a framework for effective implementation of I5.0 concept in manufacturing enterprises. This article aims to stand on an unbiased assessment to ascertain the landscape occupied by I5.0 and the results of the comprehensive review offer insightful conclusions. I5.0 represents a paradigm shift that emphasizes the integration of advanced technologies with human‐centric approaches. This paper critically analyzes the key pillars and highlights the potential to enhance sustainability in manufacturing. Furthermore, the implications of I5.0 for sustainable manufacturing practices are explored. The paper also investigates its potential to address environmental concerns and promote eco‐friendly manufacturing practices. The findings provide valuable insights for policymakers, industry leaders, and technology providers in implementing sustainable manufacturing practices on their I5.0 journey. In addition, the proposed I5.0 framework will serve as a basis for further investigations on how to apply the concept of I5.0 in other sectors.

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“…Although the concepts and the thrust focus areas are discussed at a wider level, the major challenges in implementation need critical attention. Further, several developing economies may face serious challenges in the successful adoption of the digital technologies, and in the procurement of skilled labor to achieve the human-centric focus (Adel, 2022;Gagnidze, 2022). The typical challenges to Industry 5.0 and the causal relations binding them were not explored in the current literature and this emanates as the primary objective of the study.…”

Section: Introductionmentioning

confidence: 99%

Industry 5.0: analyzing the challenges in implementation using grey influence analysis

Rajesh

2023

JEIM

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PurposeThe author explores the challenges to implementation of Industry 5.0 in the manufacturing sector, considering the developing economy context and studying the causal relationships among factors using an advanced causal modelling technique, the Grey Influence Analysis (GINA). The challenges were further classified based on importance and their influencing power.Design/methodology/approachThe author uses the novel causal modelling technique of GINA to study and understand the influence relations among the challenges to implementation of Industry 5.0.FindingsBased on the results from the expert response-based study in the Indian manufacturing industry, it is seen that the Regulatory challenges (RGC) appear to be the most important challenge that needs to be tackled first, while implementing Industry 5.0. Integration with existing systems and Ethical challenges (ETC) emerge as the second and third most important in the category of challenges, as per the results from the GINA analysis.Research limitations/implicationsThe RGC and the ETC need to be addressed prior to implementation and it is necessary to check whether the technologies comply with regulations and whether it creates serious job displacements. While implementation, the challenges with integration to existing systems can be appropriately tackled.Practical implicationsAs a practical implication of the study, the author suggests that a proactive and reactive approach can be adopted to implement the Industry 5.0 concepts to reality. The RGC can be viewed for the adoption of technology, integration challenges can be viewed by understanding the existing systems, and ETC can be addressed by understanding the workforce in combination with technologies.Originality/valueThe shift in focus on sustainability and resilience has transformed the conventional industries to think beyond efficiency and productivity, toward being more responsible to society. The study analyzes the challenges to implementation of Industry 5.0 and the causal relations among them considering an expert response-based study.

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Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas

Cited by 274 publications

References 145 publications

LSTM-Autoencoder for Vibration Anomaly Detection in Vertical Carousel Storage and Retrieval System (VCSRS)

LSTM-Autoencoder for Vibration Anomaly Detection in Vertical Carousel Storage and Retrieval System (VCSRS)

Industry 5.0 and the future of sustainable manufacturing: A systematic literature review

Industry 5.0: analyzing the challenges in implementation using grey influence analysis

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