Article
Automation & Control Systems
Emre Yildiz, Charles Moller, Arne Bilberg
Summary: Smart manufacturing, driven by the 4th industrial revolution and forces like innovation, competition, and changing demands, requires manufacturing companies to reform and regenerate their product, process, and system models to stay competitive. The digital twin-based virtual factory concept shows potential in supporting manufacturing organizations to adapt to dynamic and complex environments through virtual collaboration and prototyping.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Victor Alejandro Huerta-Torruco, Oscar Hernandez-Uribe, Leonor Adriana Cardenas-Robledo, Noe Amir Rodriguez-Olivares
Summary: This study develops an integrated approach to determine the effectiveness of virtual reality (VR) and presents the results based on data collection and analysis of 72 volunteers. The findings indicate that the VR interface significantly reduces experimentation time and improves the percentage of correct answers. Users also preferred the VR system according to self-reported feedback, with higher values in terms of usability compared to the laptop computer.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Automation & Control Systems
Emre Yildiz, Charles Moller, Arne Bilberg
Summary: Manufacturing organisations need to adapt and compete by strengthening their chains of competencies, which can be achieved through technological advancements and integrated solutions. Studies focusing on conceptual and practical aspects of comprehensive and integrated solutions in the manufacturing domain are limited. This paper aims to fill this gap by discussing the theoretical foundations of DT-based VF, extending it to virtual enterprise, and providing managerial guidelines based on framed concepts and theories.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Iman Morshedzadeh, Amos H. C. Ng, Manfred Jeusfeld, Jan Oscarsson
Summary: Virtual engineering requires maintenance in a PLM system to manage the increasing rate and diversity of models being created. This research proposes an extension to PLM systems by designing a new information model to effectively manage historical information related to virtual models and engineering activities.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Giovanni Lugaresi, Sofia Gangemi, Giulia Gazzoni, Andrea Matta
Summary: Digital twins are crucial in optimizing production systems and aiding decision making. Ensuring alignment between the physical system and the digital model, as well as validating the model in real-time with limited data, is essential. This study proposes a methodology for validating digital twins in production planning and control, measuring alignment using sequence data comparison techniques.
COMPUTERS IN INDUSTRY
(2023)
Article
Management
Rafael da Costa Jahara, Marcos Pereira Estellita Lins
Summary: This paper presents a multimethodology approach that combines qualitative and quantitative modeling to improve the performance of production processes in the prosthetics and orthotics industry. By using knowledge mapping and discrete-event simulation model, an alternative improvement scenario for orthotics manufacturing was developed and validated through effective intervention, resulting in increased production capacity and reduced manufacturing lead time.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Matevz Resman, Jernej Protner, Marko Simic, Niko Herakovic
Summary: This study proposes a five-step approach to planning data-driven digital twins of manufacturing systems and processes, guiding users through breaking down the system and processes into fundamental building blocks. The development of digital models includes predefined necessary parameters to connect with a real manufacturing system, enabling control and the creation of a digital twin, with presentation and visualization of system functioning based on the digital twin for different participants in the last step.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Seungnam Yu, Jonghui Han
Summary: This study developed a design method combining layout optimization, discrete event simulation, and virtual reality platform for the hot cell facility design, proving its practicality in remote handling operations.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Review
Engineering, Industrial
Carlos Henrique dos Santos, Jose Arnaldo Barra Montevechi, Jose Antonio de Queiroz, Rafael de Carvalho Miranda, Fabiano Leal
Summary: The use of simulation as Digital Twin to support decision-making is a well-established research field, with integration of simulation with physical systems allowing virtual models to be aligned with the current state of processes. Even though the Digital Twin concept is relatively new, its principles have been used for decades in decision-making through simulation, with ongoing discussions and uncertainties regarding simulation models in this research field.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Automation & Control Systems
Mohamed Afy-Shararah, Konstantinos Salonitis
Summary: This paper presents a novel holistic modeling approach to investigate the relationship between qualitative variables and quantifiable shopfloor key performance indicators. The study found that increasing absenteeism reduces production rate and motivation, while effective training can increase motivation. Causal loop diagram and system dynamics simulation model were used to depict these relationships.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Giovanni Lugaresi, Andrea Matta
Summary: Industry 4.0 has brought forth technologies that enable data-driven production planning and control. Digital twins, utilized for decision making based on the current state of manufacturing systems, depend on accurately representing the physical counterpart. Automating model generation through process mining can speed up the development of digital twins, but traditional techniques struggle with complex production environments. This paper proposes object-centric process mining and an algorithm for generating accurate digital models of manufacturing systems with complex material flows, and it has been successfully tested on real systems.
COMPUTERS IN INDUSTRY
(2023)
Article
Engineering, Industrial
Haifan Jiang, Shengfeng Qin, Jianlin Fu, Jian Zhang, Guofu Ding
Summary: Digital twin is a virtual mirror of a physical world or system, serving as a key building block for smart factory and manufacturing under the Industry 4.0 paradigm. The key research question is how to effectively create a DT model during the design stage of a complex manufacturing system and make it usable throughout the system’s lifecycle. Modeling methods for rapidly creating a virtual model and the connection implementation mechanism between physical and virtual systems are crucial for achieving these goals.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Nuclear Science & Technology
Cade M. Bourque, Kevin T. Clarno, Benjamin D. Leibowicz
Summary: This paper explores how hiring requirements in the context of nuclear fuel manufacturing can be determined using the coupling of physics-based and discrete-event simulation technologies, aiming to meet production goals, comply with safety regulations, and reduce project costs.
ANNALS OF NUCLEAR ENERGY
(2022)
Article
Computer Science, Artificial Intelligence
Prieto-Gonzalez David, Castilla-Rodriguez Ivan, Gonzalez-Gonzalez Evelio Jose, Couce-Pico Maria de la Luz
Summary: This study presents a method to extract knowledge from a domain ontology and generate discrete event simulation (DES) models. By improving a rare disease ontology and developing a transformation tool, DES models can be automatically generated. The effectiveness of this method is validated by comparing the automatically generated models with manually created ones.
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
(2023)
Article
Computer Science, Artificial Intelligence
Konstantinos Mykoniatis, Gregory A. Harris
Summary: Virtual commissioning is a key technology in Industry 4.0 that utilizes a digital twin model to test and verify control systems in a simulated environment before physical commissioning. It can also integrate and test modular production control systems during or prior to the construction of the physical system. The development and deployment of a digital twin emulator involves a hybrid simulation- and data-driven modeling approach to support design decisions and validate system behavior.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Mathematics
Alessio Angius, Andras Horvath, Marcello Urgo
Summary: This paper presents a method using phase-type distributions and a Markov chain model to schedule activity networks in the face of uncertain events and incomplete information. It introduces a general formulation for efficient computation by utilizing Kronecker algebra to calculate the infinitesimal generator of the Markov chain.
Article
Computer Science, Interdisciplinary Applications
Massimo Manzini, Erik Demeulemeester, Marcello Urgo
Summary: The paper discusses the technological evolution and customization needs in the automotive industry, and proposes a scheduling method for multi-product assembly lines to minimize batch completion time.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Engineering, Manufacturing
Marcello Urgo, Walter Terkaj, Marta Mondellini, Giorgio Colombo
Summary: This article presents a framework for serious game design in engineering education and tests it through a serious game application for the design and analysis of manufacturing systems.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Industrial
Francesco Berardinucci, Giorgio Colombo, Marcello Lorusso, Massimo Manzini, Walter Terkaj, Marcello Urgo
Summary: This paper proposes a structured learning workflow based on an open toolkit that smoothly integrates digital tools for manufacturing system modelling, performance evaluation, and virtual reality representation, aiming to enhance the learning experience for non-specialists in the field.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Lei Liu, Marcello Urgo
Summary: This paper investigates the scheduling problem of re-manufacturing activities for turbine blades. Due to the uncertainty in the wear states and defects of parts, a robust scheduling framework is proposed.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Maria Chiara Magnanini, Walter Terkaj, Tullio A. M. Tolio
Summary: This study proposes a new algorithm for the buffer allocation problem, which integrates performance evaluation and optimization based on linear approximation. The numerical results show the effectiveness of the proposed method compared to traditional methods. Additionally, an industrial case study incorporating the proposed method into a decision-support system for buffer allocation and reallocation is analyzed.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Q. Qi, W. Terkaj, M. Urgo, X. Jiang, P. J. Scott
Summary: As manufacturing undergoes the Industry 4.0 revolution, the complexity of digitized manufacturing systems increases due to a large amount of data and information exchange. To address this complexity, one solution is to design and operate digital twin models at different levels of abstraction and detail. To enable efficient information flow between models with different levels of detail, a mathematical structure known as a delta lens has been developed. A hybrid delta lens has also been proposed to support different types of abstractions in manufacturing.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Article
Engineering, Industrial
Lei Liu, Marcello Urgo
Summary: This work proposes a new robust scheduling framework for handling uncertain processing times and rework requirements in the remanufacturing processes of turbine blades. The framework integrates branch-and-bound and heuristic steps, using a Markovian model and phase-type distributions to execute activities and pursue robustness through the minimisation of the value-at-risk of the makespan. An industrial case study is also presented to demonstrate the feasibility of the approach.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Industrial
Lei Liu, Marcello Urgo
Summary: This paper proposes a branch-and-bound approach to solve the two-machine permutation flow shop scheduling problem with stochastic processing times. The objective is to minimize the value-at-risk of the makespan, balancing the expected performance and the mitigation of extreme scenarios. Computational experiments demonstrate the effectiveness and performance of the proposed approach.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Lei Liu, Marcello Urgo
Summary: This paper addresses a two-machine re-entrant flow shop scheduling problem with stochastic processing times and proposes a branch-and-bound algorithm and heuristic algorithms to solve the problem. The goal is to balance expected performance and the impact of extreme scenarios by minimizing the value-at-risk.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Kashif Mahmood, Tauno Otto, Vladimir Kuts, Walter Terkaj, Gianfranco Modoni, Marcello Urgo, Giorgio Colombo, Geza Haidegger, Peter Kovacs, Johan Stahre
Summary: This paper presents the conceptual development and testing of a Virtual Learning Factory Toolkit (VLFT), which integrates digital tools used in production management with engineering education to enhance students' ICT skills for future industrial engineering. The digital tools within the VLFT were tested through structured workflows and joint learning labs to collect and analyze students' feedback.
PROCEEDINGS OF THE ESTONIAN ACADEMY OF SCIENCES
(2021)
Article
Engineering, Industrial
Walter Terkaj, Qunfen Qi, Marcello Urgo, Paul J. Scott, Xiangqian Jiang
Summary: By leveraging ontologies and delta-lenses, this study enables multiscale models of manufacturing systems to map digital models and flow data while assessing the capability of lower-detail models to approximate system behavior, ultimately deciding the positions of sensors on an assembly line.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2021)
