Review
Engineering, Industrial
Ardeshir Shojaeinasab, Todd Charter, Masoud Jalayer, Maziyar Khadivi, Oluwaseyi Ogunfowora, Nirav Raiyani, Marjan Yaghoubi, Homayoun Najjaran
Summary: This paper systematically reviews the research and implementations in Manufacturing Execution Systems (MES) to identify promising research topics and proposes a conceptual framework for Intelligent MES (IMES).
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Information Science & Library Science
Maria del Mar Roldan-Garcia, Jose Garcia-Nieto, Alejandro Mate, Juan Trujillo, Jose F. Aldana-Montes
Summary: A key challenge in current Business Analytics is selecting suitable indicators for business objectives by exploring business data through data-driven approaches and modeling business strategies with domain experts. The semantic web technology emerges as a powerful tool for knowledge representation and data modeling to enrich strategic models and enable semantic validation of indicators.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Akshay Avhad, Casper Schou, Ole Madsen
Summary: Swarm Production Systems utilize mobile robot platforms for workstations and material transport, allowing for a flexible production philosophy and continuous restructuring of the factory floor. The systems also require an interoperable management system called the Swarm Manager, which handles task planning, allocation, and scheduling for process and product transport robots. This research provides a conceptualization framework and architecture for the Swarm Manager, addressing functional needs and proposing a system-level architecture.
COMPUTERS IN INDUSTRY
(2023)
Article
Engineering, Industrial
Xingjian Lai, Huanyi Shui, Daoxia Ding, Jun Ni
Summary: A systematic approach for bottleneck detection in complex manufacturing systems is proposed, extending a well-recognized algorithm and evaluating several common industrial scenarios including closed loop structures, parallel line structures, and rework loop structures. The methodology is demonstrated with a successful pilot study at an automotive powertrain assembly line, resulting in over 30% gain in Overall Equipment Effectiveness (OEE).
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Chen Zheng, Jiajian Xing, Zhanxi Wang, Xiansheng Qin, Benoit Eynard, Jing Li, Jing Bai, Yicha Zhang
Summary: This study proposes a knowledge-based program-generation approach for robotic manufacturing systems to improve programming efficiency and enhance manufacturing stability and production quality by standardizing manufacturing program rules and knowledge.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Chemistry, Multidisciplinary
Richard Beregi, Gianfranco Pedone, Borbala Hay, Jozsef Vancza
Summary: Digital transformation and artificial intelligence are driving innovation in industry, integrating IT into manufacturing processes and transforming work practices. The proposed methodology in the study aims to integrate services from isolated workcells into a reliable, reconfigurable, and interoperable manufacturing architecture, enhancing service interoperability levels.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Wei Hua Chen, Gwendolyn Foo, Sami Kara, Maurice Pagnucco
Summary: The study introduces a robotic disassembly system aimed at addressing product variation and end-of-life product and condition information uncertainties, capable of dismantling LCD screens with user intervention and flexible planning. By combining specific product information with background knowledge, the system is able to assess and select desirable disassembly actions effectively.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Review
Chemistry, Multidisciplinary
Jinyu Sheng, Daisy R. S. Pooler, Ben L. L. Feringa
Summary: Chirality is a fundamental property with wide applications in various fields. Chiroptical artificial molecular motors (AMMs) are a class of molecules that can convert light energy into mechanical work, holding great potential in the development of dynamic systems and responsive materials. By taking advantage of their intrinsic chirality and the ability to modulate chirality, chiral AMMs have been designed for light-responsive processes such as catalysis, self-assembly, recognition, transmission of chirality, spin selectivity control, and integration with mechanical functions. This review focuses on the strategies for chirality-led applications using intrinsically chiral AMMs and discusses current limitations and future prospects.
CHEMICAL SOCIETY REVIEWS
(2023)
Article
Chemistry, Multidisciplinary
Minjae Ko, Changho Lee, Yongju Cho
Summary: This article presents a framework, development, and application process of a cloud-based collaborative Manufacturing Execution System (MES) and analyzes its application and effects in the value chain of personalized sportswear products in the fashion industry in Korea.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Filip Ilievski, Alessandro Oltramari, Kaixin Ma, Bin Zhang, Deborah L. McGuinness, Pedro Szekely
Summary: Commonsense knowledge is crucial for various AI applications, with recent focus on large text-based sources. Efforts to consolidate this knowledge into a comprehensive solution have had partial success. Researchers aim to unify different sources by organizing them around common dimensions and analyzing their impact on reasoning tasks.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Tao Zhang, Weixi Ji, Yongtao Qiu
Summary: This paper introduces a data-driven energy consumption data analysis framework for promoting energy efficiency in discrete manufacturing systems. The focus of the research is on proposing energy efficiency evaluation standards, energy consumption data preprocessing, big data mining methods, energy consumption parameter design, and prediction algorithms.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Computer Science, Artificial Intelligence
Lingguo Bu, Yanjie Zhang, Heshan Liu, Xin Yuan, Jia Guo, Su Han
Summary: Smart manufacturing has great potential in personalized customization, network collaboration, and improving production efficiency. However, integrating AI and IIoT technologies based on platform is a challenge for the manufacturing industry.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Lei Yang, Yi-Song Wang, Hong-Bo Hu, Ren-Yan Feng, Jun Liu
Summary: Multicontext systems effectively integrate heterogeneous knowledge from different sources and have applications in various fields. This article aims to combine multicontext systems with fuzzy logic theory to deal with uncertainty in heterogeneous contexts. The research in this area, particularly in terms of systematic integration, is limited. The article proposes a class of heterogeneous nonmonotonic fuzzy multicontext systems, establishing a syntactic and semantic framework for their representation and reasoning. The proposed fuzzy multicontext system extends the capabilities of nonmonotonic, probabilistic, and possibilistic multicontext systems.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Ismail Mendil, Yamine Ait-Ameur, Neeraj Kumar Singh, Guillaume Dupont, Dominique Mery, Philippe Palanque
Summary: This paper discusses how formal ontologies can be used to model domain-specific knowledge and shows how system models can refer to these ontologies through annotation. The framework proposed in this paper formalizes domain-specific knowledge ontologies as Event-B theories, which are used to define data types for Event-B system design models. A case study on the Traffic Collision Avoidance System (TCAS) is developed to illustrate the proposed approach.
JOURNAL OF SYSTEMS ARCHITECTURE
(2023)
Article
Computer Science, Artificial Intelligence
Cheng Luo, Dayiheng Liu, Chanjuan Li, Li Lu, Jiancheng Lv
Summary: This paper proposes a knowledge-driven conversation system that uses external knowledge to generate diverse sentences and incorporate actual knowledge. The system consists of three modules: topic predictor, knowledge selector, and dialogue generator. Experimental results show that the proposed system outperforms baseline methods and achieves significant improvement on the KdConv corpus.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Energy & Fuels
Mahboob Elahi, Samuel Olaiya Afolaranmi, Wael M. Mohammed, Jose Luis Martinez Lastra
Summary: This paper presents a data-driven approach for predicting the gradual deterioration of conveyor belts used in discrete manufacturing systems. The approach utilizes power consumption data collected under different loads and tensions to train an artificial neural network model. The trained model can then predict the belt tension class based on real-time measurements, allowing for maintenance actions to be taken to prevent catastrophic situations.
Article
Chemistry, Analytical
Aditi Site, Saigopal Vasudevan, Samuel Olaiya Afolaranmi, Jose L. Martinez Lastra, Jari Nurmi, Elena Simona Lohan
Summary: This paper presents a machine-learning based approach to classify user loneliness levels using indoor and outdoor mobility patterns. The study found that distance traveled, speed, and frequently visited clusters were the most relevant features for classifying the user's perceived loneliness levels. The machine-learning model based on XGBoost algorithm achieved high accuracy in classifying indoor, outdoor, and combined indoor-outdoor data.
Article
Chemistry, Multidisciplinary
Angela Lago Alvarez, Wael M. Mohammed, Tuan Vu, Seyedamir Ahmadi, Jose Luis Martinez Lastra
Summary: In recent years, Industry 4.0 has offered tools for replicating, monitoring, and controlling physical systems to build cyber-physical systems. One concept introduced is digital twins, which create virtual representations of physical systems to exchange information. This paper presents an approach to incorporate human factors in digital twins using a methodology for suggesting employee rotations based on their previous performance. The approach includes a human skills modelling engine and a human scheduling engine, demonstrated through a simulated assembly line.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Antti Martikkala, Bening Mayanti, Petri Helo, Andrei Lobov, Inigo Flores Ituarte
Summary: Improving the recycling system through digitalization can reduce the environmental burden of textile production. Sensor technologies assist in predicting waste accumulation in collection bins, leading to efficient route optimization and cost reduction. Testing the viability and reliability of low-cost sensors in a real-world setting, the study demonstrates the potential of a sensor-enhanced dynamic collection system to decrease costs by 7.4% and reduce CO2 emissions by 10.2%.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Multidisciplinary Sciences
Mahboob Elahi, Samuel Olaiya Afolaranmi, Wael M. Mohammed, Jose Luis Martinez Lastra
Summary: This article presents a dataset collected from the FASTory assembly line, which contains over 4,000 data samples of conveyor belt motor driver's power consumption. Machine learning models are used to learn the power consumption patterns under different load and belt tension values, and to forecast the deterioration of conveyor belts and plan maintenance strategies.
Article
Engineering, Industrial
Joe David, Eric Coatanea, Andrei Lobov
Summary: To achieve effective human-robot collaborative assembly, it is important to view robots and humans as autonomous entities capable of communication and different roles, without being bound by preplanned routines. Most existing research lacks runtime communication and self-organization, and assumes static predefined roles during collaboration. This study presents a collaborative agent for manufacturing ontology (CAMO) that uses description logic to maintain a self-organizing team network between collaborating human-robot multi-agent systems. CAMO incorporates dynamic consensus-driven collaboration based on runtime dynamic communication and is implemented using Web Ontology Language. A case study with real diesel engine assembly demonstrates the feasibility of CAMO and the framework.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Pablo Malvido Fresnillo, Saigopal Vasudevan, Wael M. Mohammed, Jose L. Martinez Lastra, Jose A. Perez Garcia
Summary: MoveIt is a primary software library in ROS for motion planning and mobile manipulation, which incorporates the latest advances in motion planning, control, and perception. However, it still lacks some important functions needed to robotize many manufacturing processes for more advanced manipulation applications. This paper analyzes the current state of MoveIt, identifies its main needs, and proposes solutions to address three gaps: automatic tool changing at runtime, trajectory generation with full control over the end effector path and speed, and generation of dual-arm trajectories using different synchronization policies. The proposed solutions have been tested and proven valid with a Motoman SDA10F dual-arm robot in various scenarios. They are generic, robot-agnostic, and openly available to enhance the capabilities of MoveIt.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Information Systems
Erlantz Loizaga, Aitor Toichoa Eyam, Leire Bastida, Jose L. Martinez Lastra
Summary: The study aims to explore the measurement of human factors in the workplace that can provide insights into workers' well-being. It identifies six crucial human factors: physical fatigue, attention, mental workload, stress, trust, and emotional state. Understanding these factors can help employers create a better work environment that improves worker well-being.
Article
Automation & Control Systems
Pablo Malvido Fresnillo, Saigopal Vasudevan, Wael M. Mohammed, Jose L. Martinez Lastra, Jose A. Perez Garcia
Summary: A novel machine vision approach is proposed in this study to estimate the shape of Deformable Linear Objects (DLOs). By modeling the shape of objects using polynomial functions, this approach can effectively handle complex environments and interferences between objects.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Anna Florea, Andrei Lobov, Tatiana Minav
Summary: Digital twins provide new insights for optimizing industrial processes and system performance, and the integration and navigation of a variety of digital twins in large-scale systems is becoming increasingly important. To address the complexity of modern industrial systems, an organized integration approach is required to help engineers make informed decisions and communicate project goals clearly.
2022 IEEE 20TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Joe David, Eeva Jarvenpaa, Andrei Lobov
Summary: This study presents a novel approach to enable standards-based explicit bidirectional intent communication by projecting a tailored web-based user interface on the shared worktable between a human and robot agent. It aims to prevent competing and turn-taking behavior, improving the efficiency and safety of collaboration.
2022 8TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND ROBOTICS ENGINEERING (ICMRE 2022)
(2022)
