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

Deadline for manuscript submissions: closed (10 November 2021) | Viewed by 45416

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Special Issue Editors

Prof. Dr. Stanislao Patalano

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Department of Industrial Engineering, University of Naples Federico II, 80125 Napoli, Italy
Interests: knowledge-based 3D CAD modeling; GD&T and variation analysis; modeling and simulation of mechatronic systems

Prof. Dr. Antonio Lanzotti

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Guest Editor

Department of Industrial Engineering, University of Naples Federico II, 80125 Napoli, Italy
Interests: design methods; robust design; human-centered design; virtual prototyping; VR-AR technologies

Prof. Dr. Bruno Siciliano

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Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Napoli, Italy
Interests: manipulation and control; human–robot cooperation; service robotics

Prof. Dr. Luigi Villani

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Guest Editor

Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Napoli, Italy
Interests: robot control; human–robot interaction; human–robot collaboration

Special Issue Information

Dear Colleagues,

The Issue aims to disseminate challenging research dealing with design methods, technologies, and systems for a collaborative factory enhanced by Industry 4.0 and Industry 5.0 principles. Interconnected technologies aiming to improve factory efficiency and productivity—supported by Industry 4.0 pillars—have to be enriched by a deeper system humanization and a renewed usage of resources. In such a vision, humans and machine must be highly interconnected to accomplish the future enlarging customization of manufacturing processes and the wider use of optimized robotized processes. Mobile and fixed robotic collaborative systems, quality and machinery monitoring systems for operator assistance, and autonomous guided vehicles interacting with operators are essential tools to conceive, prototype, and implement integrated collaborative workplaces for a smart factory. New methodologies can support the design and development of collaborative workplaces by adopting mathematical modeling and virtual simulation to boost and optimize verification and validation steps of designing processes.

Design methods and models for a new collaborative factory
Methodologies for the design and development of collaborative workplaces
Enhanced efficient integration of robotic collaboration
Active and smart logistics with autonomous guided vehicles for collaborative operations
Collaborative quality control for product/process optimization and predictive maintenance
Planning and control paradigms for collaborative robots
Mechatronic design of collaborative robots
Human–machine interfaces for the collaborative factory

Prof. Dr. Stanislao Patalano
Prof. Dr. Antonio Lanzotti
Prof. Dr. Bruno Siciliano
Prof. Dr. Luigi Villani
Guest Editors

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Published Papers (10 papers)

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Research

21 pages, 2548 KiB

Open AccessArticle

Heterogeneous Models Integration for Safety Critical Mechatronic Systems and Related Digital Twin Definition: Application to a Collaborative Workplace for Aircraft Assembly

by Faïda Mhenni, Ferdinando Vitolo, Andrea Rega, Régis Plateaux, Peter Hehenberger, Stanislao Patalano and Jean-Yves Choley

Appl. Sci. 2022, 12(6), 2787; https://doi.org/10.3390/app12062787 - 9 Mar 2022

Cited by 15 | Viewed by 3101

Abstract

Nowadays, several manufacturing systems are evolving towards a greater collaboration between human and robots. The development of such systems requires integrated design tasks involving many disciplines and domains such as systems engineering, safety analyses and multi-physics. Furthermore, the increasing presence of multiple and structured requirements makes the use of models inevitable during the designing phases and also strongly helpful during other phases of the system life-cycle. Besides, for a better efficiency, there is an increasing demand to have a Digital Twin of the system to be used for different purposes such as design improvements by playing different scenarios, virtual commissioning and controlling maintenance activities. In this paper, we first summarize the research context, the reference methodologies, and the emerging needs for Digital Twin creation. Then, we apply a design approach including Model-Based Systems Engineering (MBSE), Model-Based Safety Assessment (MBSA) and multi-physics modeling for the design of a collaborative workplace for the assembly of Electro-Mechanical Actuators on an aircraft wing. An operational flow to integrate MBSE, MBSA and multi-physics modelling activities is provided. Then, after having identified some relevant scientific barriers, we provide a meta-model for system models integration within a digital twin framework. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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13 pages, 2608 KiB

Open AccessArticle

Towards an Assembly Support System with Dynamic Bayesian Network

by Stefan-Alexandru Precup, Arpad Gellert, Alexandru Matei, Maria Gita and Constantin-Bala Zamfirescu

Appl. Sci. 2022, 12(3), 985; https://doi.org/10.3390/app12030985 - 19 Jan 2022

Cited by 7 | Viewed by 2194

Abstract

Due to the new technological advancements and the adoption of Industry 4.0 concepts, the manufacturing industry is now, more than ever, in a continuous transformation. This work analyzes the possibility of using dynamic Bayesian networks to predict the next assembly steps within an assembly assistance training system. The goal is to develop a support system to assist the human workers in their manufacturing activities. The evaluations were performed on a dataset collected from an experiment involving students. The experimental results show that dynamic Bayesian networks are appropriate for such a purpose, since their prediction accuracy was among the highest on new patterns. Our dynamic Bayesian network implementation can accurately recommend the next assembly step in 50% of the cases, but to the detriment of the prediction rate. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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25 pages, 5631 KiB

Open AccessArticle

Mobile Robots and Cobots Integration: A Preliminary Design of a Mechatronic Interface by Using MBSE Approach

by Ferdinando Vitolo, Andrea Rega, Castrese Di Marino, Agnese Pasquariello, Alessandro Zanella and Stanislao Patalano

Appl. Sci. 2022, 12(1), 419; https://doi.org/10.3390/app12010419 - 2 Jan 2022

Cited by 22 | Viewed by 5268

Abstract

Enabling technologies that drive Industry 4.0 and smart factories are pushing in new equipment and system development also to prevent human workers from repetitive and non-ergonomic tasks inside manufacturing plants. One of these tasks is the order-picking which consists in collecting parts from the warehouse and distributing them among the workstations and vice-versa. That task can be completely performed by a Mobile Manipulator that is composed by an industrial manipulator assembled on a Mobile Robot. Although the Mobile Manipulators implementation brings advantages to industrial applications, they are still not widely used due to the lack of dedicated standards on control and safety. Furthermore, there are few integrated solutions and no specific or reference point allowing the safe integration of mobile robots and cobots (already owned by company). This work faces the integration of a generic mobile robot and collaborative robot selected from an identified set of both systems. The paper presents a safe and flexible mechatronic interface developed by using MBSE principles, multi-domain modeling, and adopting preliminary assumptions on the hardware and software synchronization level of both involved systems. The interface enables the re-using of owned robot systems differently from their native tasks. Furthermore, it provides an additional and redundant safety level by enabling power and force limiting both during cobot positioning and control system faulting. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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29 pages, 4747 KiB

Open AccessArticle

Collaborative Workplace Design: A Knowledge-Based Approach to Promote Human–Robot Collaboration and Multi-Objective Layout Optimization

by Andrea Rega, Castrese Di Marino, Agnese Pasquariello, Ferdinando Vitolo, Stanislao Patalano, Alessandro Zanella and Antonio Lanzotti

Appl. Sci. 2021, 11(24), 12147; https://doi.org/10.3390/app112412147 - 20 Dec 2021

Cited by 29 | Viewed by 5043

Abstract

The innovation-driven Industry 5.0 leads us to consider humanity in a prominent position as the center of the manufacturing field even more than Industry 4.0. This pushes us towards the hybridization of manufacturing plants promoting a full collaboration between humans and robots. However, there are currently very few workplaces where effective Human–Robot Collaboration takes place. Layout designing plays a key role in assuring safe and efficient Human–Robot Collaboration. The layout design, especially in the context of collaborative robotics, is a complex problem to face, since it is related to safety, ergonomics, and productivity aspects. In the current work, a Knowledge-Based Approach (KBA) is adopted to face the complexity of the layout design problem. The framework resulting from the KBA allows for developing a modeling paradigm that enables us to define a streamlined approach for the layout design. The proposed approach allows for placing resource within the workplace according to a defined optimization criterion, and also ensures compliance with various standards. This approach is applied to an industrial case study in order to prove its feasibility. A what-if analysis is performed by applying the proposed approach. Changing three control factors (i.e., minimum distance, robot speed, logistic space configuration) on three levels, in a Design of Experiments, 27 layout configurations of the same workplace are generated. Consequently, the inputs that most affect the layout design are identified by means of an Analysis of Variance (ANOVA). The results show that only one layout is eligible to be the best configuration, and only two out of three control factors are very significant for the designing of the HRC workplace layout. Hence, the proposed approach enables the designing of standard compliant and optimized HRC workplace layouts. Therefore, several alternatives of the layout for the same workplace can be easily generated and investigated in a systematic manner. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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23 pages, 11327 KiB

Open AccessArticle

An Approach Based on VR to Design Industrial Human-Robot Collaborative Workstations

by Elisa Prati, Valeria Villani, Margherita Peruzzini and Lorenzo Sabattini

Appl. Sci. 2021, 11(24), 11773; https://doi.org/10.3390/app112411773 - 11 Dec 2021

Cited by 18 | Viewed by 4319

Abstract

This paper presents an integrated approach for the design of human-robot collaborative workstations in industrial shop floors. In particular, the paper presents how to use virtual reality (VR) technologies to support designers in the creation of interactive workstation prototypes and in early validation of design outcomes. VR allows designers to consider and evaluate in advance the overall user experience, adopting a user-centered perspective. The proposed approach relies on two levels: the first allows designers to have an automatic generation and organization of the workstation physical layout in VR, starting from a conceptual description of its functionalities and required tools; the second aims at supporting designers during the design of Human-Machine Interfaces (HMIs) by interaction mapping, HMI prototyping and testing in VR. The proposed approach has been applied on two realistic industrial case studies related to the design of an intensive warehouse and a collaborative assembly workstation for automotive industry, respectively. The two case studies demonstrate how the approach is suited for early prototyping of complex environments and human-machine interactions by taking into account the user experience from the early phases of design. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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20 pages, 2046 KiB

Open AccessArticle

IoT Helper: A Lightweight and Extensible Framework for Fast-Prototyping IoT Architectures

by Giansalvatore Mecca, Michele Santomauro, Donatello Santoro and Enzo Veltri

Appl. Sci. 2021, 11(20), 9670; https://doi.org/10.3390/app11209670 - 17 Oct 2021

Cited by 4 | Viewed by 2973

Abstract

Industry 4.0 is focused on the task of creating Smart Factories, which require the automation of traditional industrial processes and the fully connection and integration of different systems and devices. However, despite the wide availability of tools and technology, developing intelligent applications in the industry framework remains a complex and expensive task. This paper proposes a lightweight, extensible and scalable framework called IoT Helper to facilitate the adoption of IoT and IIoT solutions both in industry and domotics. The framework is designed to be highly flexible and declarative in nature, thus allowing for a wide range of configurations with minimal user efforts. To emphasize the practical applicability or our proposal, we present two real-life use cases where the framework was successfully adopted. We also investigate a crucial aspect of these applications, i.e., what level of scalability can be achieved with a lean generic framework based on inexpensive components such as ours. Comprehensive experimental results show the excellent cost-to-performance ratio of our solution. We consider this to be an important contribution because it paves the way for a more widespread adoption of IIoT-enabling technologies in industry. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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21 pages, 5245 KiB

Open AccessArticle

QHAR: Q-Holonic-Based ARchitecture for Self-Configuration of Cyber–Physical Production Systems

by Douha Macherki, Thierno M. L. Diallo, Jean-Yves Choley, Amir Guizani, Maher Barkallah and Mohamed Haddar

Appl. Sci. 2021, 11(19), 9013; https://doi.org/10.3390/app11199013 - 28 Sep 2021

Cited by 4 | Viewed by 3257

Abstract

Production systems must be able to adapt to increasingly frequent internal and external changes. Cyber-Physical Production Systems (CPPS), thanks to their potential capacity for self-reconfiguration, can cope with this need for adaptation. To implement the self-reconfiguration functionality in economical and safe conditions, CPPS must have appropriate tools and contextualized information. This information can be organized in the form of an architecture. In this paper, after the analysis of several holonic and nonholonic architectures, we propose a holonic architecture that allows for reliable and efficient reconfiguration. We call this architecture QHAR (Q-Holonic-based ARchitecture). QHAR is constructed based on the idea of a Q-holon, which has four dimensions (physical, cyber, human, and energy) and can exchange three flows (energy, data, and materials). It is a generic Holon that can represent any entity or actor of the supply chain. The QHAR is structured in three levels: centralized control level, decentralized control level, and execution level. QHAR implements the principle of an oligarchical control architecture by deploying both hierarchical and heterarchical control approaches. This ensures the overall system performance and reactivity to hazards. The proposed architecture is tested and validated on a case study. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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24 pages, 5451 KiB

Open AccessArticle

Increasing Resilience of Production Systems by Integrated Design

by Steffen Ihlenfeldt, Tim Wunderlich, Marian Süße, Arvid Hellmich, Christer-Clifford Schenke, Ken Wenzel and Sarah Mater

Appl. Sci. 2021, 11(18), 8457; https://doi.org/10.3390/app11188457 - 12 Sep 2021

Cited by 13 | Viewed by 4292

Abstract

The paper presents a framework for considering resilience as an integrated aspect in the design of manufacturing systems. The framework comprises methods for the assessment of resilience, supply chain and production planning, flexible execution and control as well as modular and skill-based methods for automation systems. A basic classification of risk categories and their impacts on manufacturing environments is given so that a concept of reconfigurable and robust production systems can be derived. Based on this, main characteristics and concepts of resilience are applied to manufacturing systems. As a lever of increased resilience on business and supply chain level, options for synchronized production planning are presented in a discrete event simulation. Furthermore, a concept to increase resilience on the level of business process execution is investigated, allowing manufacturing tasks to be rescheduled during runtime using a declarative approach to amend conventional business process models. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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21 pages, 8271 KiB

Open AccessArticle

Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics

by Khalil Aloui, Amir Guizani, Moncef Hammadi, Thierry Soriano and Mohamed Haddar

Appl. Sci. 2021, 11(13), 6187; https://doi.org/10.3390/app11136187 - 3 Jul 2021

Cited by 15 | Viewed by 6593

Abstract

In recent years, collaborative robots have become one of the main drivers of Industry 4.0. Compared to industrial robots, automated guided vehicles (AGVs) are more productive, flexible, versatile, and safer. They are used in the smart factory to transport goods. Today, many producers and developers of industrial robots have entered the AGV sector. However, they face several challenges in designing AGV systems, such as the complexity and discontinuity of the design process, as well as the difficulty of defining a decentralized system decision. In this paper, we propose a new integrated design methodology based on swarm robotics to address the challenges of functional, physical, and software integration. This methodology includes two phases: a top-down phase from requirements specification to functional and structural modeling using the systems modeling language (SysML); with a bottom-up phase for model integration and implementation in the robot operating system (ROS). A case study of an automated guided vehicle (AGV) system was chosen to validate our design methodology and illustrate its contributions to the efficient design of AGVs. The novelty of this proposed methodology is the combination of SysML and ROS to address traceability management between the different design levels of AGV systems, in order to achieve functional, physical and software integration. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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19 pages, 3431 KiB

Open AccessFeature PaperArticle

Toward Future Automatic Warehouses: An Autonomous Depalletizing System Based on Mobile Manipulation and 3D Perception

by Jacopo Aleotti, Alberto Baldassarri, Marcello Bonfè, Marco Carricato, Davide Chiaravalli, Roberto Di Leva, Cesare Fantuzzi, Saverio Farsoni, Gino Innero, Dario Lodi Rizzini, Claudio Melchiorri, Riccardo Monica, Gianluca Palli, Jacopo Rizzi, Lorenzo Sabattini, Gianluca Sampietro and Federico Zaccaria

Appl. Sci. 2021, 11(13), 5959; https://doi.org/10.3390/app11135959 - 26 Jun 2021

Cited by 24 | Viewed by 5740

Abstract

This paper presents a mobile manipulation platform designed for autonomous depalletizing tasks. The proposed solution integrates machine vision, control and mechanical components to increase flexibility and ease of deployment in industrial environments such as warehouses. A collaborative robot mounted on a mobile base is proposed, equipped with a simple manipulation tool and a 3D in-hand vision system that detects parcel boxes on a pallet, and that pulls them one by one on the mobile base for transportation. The robot setup allows to avoid the cumbersome implementation of pick-and-place operations, since it does not require lifting the boxes. The 3D vision system is used to provide an initial estimation of the pose of the boxes on the top layer of the pallet, and to accurately detect the separation between the boxes for manipulation. Force measurement provided by the robot together with admittance control are exploited to verify the correct execution of the manipulation task. The proposed system was implemented and tested in a simplified laboratory scenario and the results of experimental trials are reported. Full article

(This article belongs to the Special Issue Focus on Integrated Collaborative Systems for Smart Factory)

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