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Efficient and Accountable Industry 5.0 Production Scheduling Mechanism for Mass Customization Scenarios

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Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023) (UCAmI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 842))

Abstract

Industry 5.0 refers to a new industrial revolution characterized by the humanization of industrial systems, applications, and services: from cognitive robots to customizable products. But at the same time, Industry 5.0 must preserve the efficiency and profitability of Industry 4.0 mass production scenarios. Although, personalization and product adaptation to the individuals are traditionally understood as obstacles to take the maximum advantage of exponential business models, economies of scale and mass markets; some authors envision technologies such as cognitive Cyber-Physical Systems or swarm intelligence to overcome this challenge and enable new profitable markets for mass customizable products and services. However, Industry 5.0 is one of the most recent technological paradigms, even Industry 4.0 paradigm is not fully developed yet, and no tangible or specific proposal is still reported to achieve this efficient mass customization. This paper addresses this challenge. We propose an efficient and accountable Industry 5.0 production scheduling mechanism based on a transparent Blockchain-enabled marketplace and particle swarm optimization algorithms. Customers can request a customized product using a prosumer environment and Smart Contracts. Later, Industry 5.0 producers will combine three functions to define an optimization problem and find the most efficient production schedule. Particle Swarm Optimization algorithms are employed to calculate the most profitable production schedule. The proposed mechanism is experimentally validated using simulation tools. Results show the economy of scale is preserved, contrary to traditional customized product markets, and efficiency is just 8% lower than common mass Industry 4.0 production systems.

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Acknowledgments

This work is supported by the Ministry of Science, Innovation and Universities through the COGNOS project (PID2019-105484RB-I00); and by Comunidad de Madrid within the framework of the Multiannual Agreement with Universidad Politécnica de Madrid to encourage research by young doctors (PRINCE project).

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Authors and Affiliations

  1. Universidad Politécnica de Madrid, Madrid, Spain

    Borja Bordel, Ramón Alcarria, Guillermo de la Cal Hacar & Tomás Robles Valladares

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  1. Borja Bordel
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  2. Ramón Alcarria
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  3. Guillermo de la Cal Hacar
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  4. Tomás Robles Valladares
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Corresponding author

Correspondence to Borja Bordel .

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Editors and Affiliations

  1. Ciudad Real, Spain

    José Bravo

  2. Mérida, Yucatán, Mexico

    Gabriel Urzáiz

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Bordel, B., Alcarria, R., de la Cal Hacar, G., Valladares, T.R. (2023). Efficient and Accountable Industry 5.0 Production Scheduling Mechanism for Mass Customization Scenarios. In: Bravo, J., Urzáiz, G. (eds) Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). UCAmI 2023. Lecture Notes in Networks and Systems, vol 842. Springer, Cham. https://doi.org/10.1007/978-3-031-48642-5_5

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