Intelligent, Sustainable and Resilient Personalized Product-Service Systems towards Industry 5.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 4852

Special Issue Editors

Department of Mechanical Engineering and Aeronautics, University of Patras, Rio Patras 26504, Greece
Interests: robotic systems; automation; augmented, mixed, and virtual reality in manufacturing; manufacturing process modeling; cloud technologies; Internet of Things (IoT); digital twin; 5G; artificial intelligence; product–service systems (PSS); Industry 4.0; Industry 5.0
Special Issues, Collections and Topics in MDPI journals
Fraunhofer Institute for Industrial Engineering—FhG IAO, Stuttgart, Germany
Interests: digital/virtual/smart factory; Manufacturing 4.0; modeling; simulation; wearable robotics; exoskeletons
Special Issues, Collections and Topics in MDPI journals
Laboratory for Advanced Manufacturing Simulation and Robotics (LAMS), School of Mechanical and Materials Engineering, University College Dublin, Dublin D04 V1W8, Ireland
Interests: digital manufacturing; manufacturing simulation; robotics; assembly processes; production planning and control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The mass production paradigm, which has characterized manufacturing in recent decades, aims to achieve sustainable and competitive advantages. The increased and highly volatile consumer/customer demand for user-centered customization and the personalization of products and services present new challenges in manufacturing. The innovative mass personalization paradigm, not fully investigated under Industry 4.0, represents a high-tech manufacturing automation strategy, enabling the better integration and smoother cooperation of hardware devices and machinery (Internet of Things—IoT), software systems and humans in the extended manufacturing value chain. Smart factories, core of this new paradigm, are characterized by a high degree of digitalization and data-centricity. Jointly cooperative working teams of humans and robots autonomously guided by lights collaboratively operate in so-called Lights-out Factories. Extreme automation, developing until "everything is connected to everything else" creates vulnerabilities that have not yet been investigated extensively. The next industrial revolution, Industry 5.0, is expected to cope with these new challenges by bringing the efficiency of manufacturing systems and supply chains beyond limits. Industry 5.0 aims to democratize the co-production of knowledge by employing cutting-edge digital technologies, e.g., Big Data and IoT, supported by three main pillars: (a) human-centricity; (b) resilience; and (c) sustainability. One of the main focuses relies on the development of product platforms aiming to improve the production efficiency and create high added value for the customer/end-user.

This Special Issue explores cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), computer vision, edge computing, advanced sensors, collaborative, mobile and wearable robotics, real-time control and optimization and cognitive systems as promising technologies for the realization of mass personalization/customization under resilient, human-centric manufacturing.

Prof. Dr. Dimitris Mourtzis
Prof. Dr. Carmen Constantinescu
Prof. Dr. Nikolaos Papakostas
Guest Editors

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Published Papers (2 papers)

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Research

18 pages, 3807 KiB  
Article
Designing a User-Centered Inspection Device’s Handle for the Aircraft Manufacturing Industry
by Ana Colim, Débora Pereira, Pedro Lima, André Cardoso, Rui Almeida, Duarte Fernandes, Sacha Mould and Pedro Arezes
Appl. Sci. 2023, 13(20), 11584; https://0-doi-org.brum.beds.ac.uk/10.3390/app132011584 - 23 Oct 2023
Cited by 1 | Viewed by 629
Abstract
In aircraft manufacturing settings, workers are frequently exposed to biomechanical risk factors, mainly in the later stages of the production processes, including inspection tasks. To support the development of a novel inspection device appropriate for the end-users and their tasks, this study presents [...] Read more.
In aircraft manufacturing settings, workers are frequently exposed to biomechanical risk factors, mainly in the later stages of the production processes, including inspection tasks. To support the development of a novel inspection device appropriate for the end-users and their tasks, this study presents a user-centered approach for the device’s handle. Three different handles were proposed, and the current study aims to find out which handle can offer (1) the best ergonomic conditions and (2) the best stability in holding the device in hand during an inspection task. To this end, 23 volunteers participated in the experimental assessment, which comprised qualitative and quantitative data. A questionnaire was used for subjective comfort assessment. Partial times to execute the task studied, stability metrics of the device during its handling, and kinematic and electromyographic data of the upper limb recruited were measured and analyzed to compare the three handles. Outstanding results include the higher comfort perceived by the participants working with the selected handle for the final design, as well as the reduction in muscle effort. Globally, the results obtained demonstrated that the handle user-centered design potentiates good efficiency and usability of the novel device. Full article
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21 pages, 3916 KiB  
Article
An Intelligent Product Service System for Adaptive Maintenance of Engineered-to-Order Manufacturing Equipment Assisted by Augmented Reality
by John Angelopoulos and Dimitris Mourtzis
Appl. Sci. 2022, 12(11), 5349; https://0-doi-org.brum.beds.ac.uk/10.3390/app12115349 - 25 May 2022
Cited by 17 | Viewed by 2698
Abstract
Under the framework of Industry 4.0, machines and machine tools have evolved to smart and connected things, comprising the Internet of Things (IoT) and leading to the Mass Personalization (MP) paradigm, which enables the production of uniquely made products at scale. MP, fueled [...] Read more.
Under the framework of Industry 4.0, machines and machine tools have evolved to smart and connected things, comprising the Internet of Things (IoT) and leading to the Mass Personalization (MP) paradigm, which enables the production of uniquely made products at scale. MP, fueled by individualization trends and enabled by increasing digitalization, has the potential to go beyond current mass customization. Although this evolution has enabled engineers to gain useful insight for the production, the machine status, the quality of products, etc., machines have become more complex. Thus, Maintenance Repair and Overhaul (MRO) operations should be undertaken by specialized personnel. Additionally, Augmented Reality (AR) can support remote maintenance assistance to handle unexpected malfunctions. Moreover, due to advances regarding Product Service Systems (PSS), manufacturing companies are offering many services to improve user experience. Consequently, in this manuscript the design and development of a method based on the principles of servitization for the provision of an intelligent and adaptable maintenance service assisted by AR are presented. The contribution of the manuscript extends to the provision of an optimization algorithm for adapting the schedules of the stakeholders based on the energy supplier predictions. The developed method was tested and validated on an industrial case study of injection mold maintenance, achieving 11% energy reduction, 50% less time for mold inspection, and a 20% rise in on-time mold deliveries. Full article
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