| 1. |
- Despeisse, Mélanie, 1985, et al.
(författare)
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Battery Production Systems: State of the Art and Future Developments
- 2023
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Ingår i: IFIP Advances in Information and Communication Technology. - 1868-4238 .- 1868-422X. ; 692, s. 521-535
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Konferensbidrag (refereegranskat)abstract
- This paper discusses the state of the art in battery production research, focusing on high-importance topics to address industrial needs and sustainability goals in this rapidly growing field. We first present current research around three themes: human-centred production, smart production management, and sustainable manufacturing value chains. For each theme, key subtopics are explored to potentially transform battery value chains and shift to more sustainable production models. Such systemic transformations are supported by technological advances to enable superior manufacturing performance through: skills and competence development, improved production ergonomics and human factors, automation and human-robot collaboration, smart production planning and control, smart maintenance, data-driven solutions for production quality and its impact on battery performance (operational efficiency and durability), circular battery systems supported by service-based business models, more integrated and digitalized value chains, and increased industrial resilience. Each subtopic is discussed to suggest directions for further research to realise the full potential of digitalization for sustainable battery production.
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| 2. |
- Robinson, Jonathan, 1986, et al.
(författare)
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An atlas of human metabolism
- 2020
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Ingår i: Science Signaling. - : American Association for the Advancement of Science (AAAS). - 1945-0877 .- 1937-9145. ; 13:624
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Tidskriftsartikel (refereegranskat)abstract
- Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1. We demonstrated the versatility of Human1 through the generation and analysis of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data. We also present an accompanying web portal, Metabolic Atlas (https://www.metabolicatlas.org/), which facilitates further exploration and visualization of Human1 content. Human1 was created using a version-controlled, open-source model development framework to enable community-driven curation and refinement. This framework allows Human1 to be an evolving shared resource for future studies of human health and disease.
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| 3. |
- Salunkhe, Omkar, 1990, et al.
(författare)
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Review of Current Status and Future Directions for Collaborative and Semi-Automated Automotive Wire Harnesses Assembly
- 2023
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Ingår i: Procedia CIRP. - : Elsevier. - 2212-8271 .- 2212-8271. ; 120, s. 696-701
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Tidskriftsartikel (refereegranskat)abstract
- Wire harnesses are vital for any modern automotive vehicle. They control the basic functions in a vehicle, for example, windshield wipers and critical functions such as sensors, cameras, and autopilot functions. Thus, the quality of wire harness assembly is highly important. Today, wire harnesses are usually assembled manually, which creates unergonomic and tedious working conditions for operators. Traditional and collaborative industrial robots have been identified as possible solutions to overcome challenges faced by operators in this type of assembly. The international research community has proposed many solutions for automating the assembly of wire harnesses in automotive vehicles but despite these solutions, the industry has not been able to adopt a method to automate this assembly process fully or partially. This paper presents a review of findings on robot-assisted wire harness assembly processes based on a systematic literature review. Specifically, the assembly of wire harnesses in Electric Vehicles (EVs). The state-of-the-art review focuses on solutions to improve unergonomic work situations and ensure the quality of assembly operations. Best practices and reasons for the lack of extensive implementation in automotive final assembly systems are described. Further, the paper presents suggestions based on success stories where the automation of the wire harness assembly in automotive vehicles has been realised by leveraging human-centred automation solutions. Based on the findings, this paper identifies the research for future study. The findings also indicate that there is already technology that can support the automation of wire harness assembly processes in EVs but it is crucial to identify the human aspects and the role of humans in the assembly of wire harness assembly process.
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| 4. |
- Wang, Hao, 1996, et al.
(författare)
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A systematic literature review of computer vision applications in robotized wire harness assembly
- 2024
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Ingår i: Advanced Engineering Informatics. - 1474-0346. ; 62
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Tidskriftsartikel (refereegranskat)abstract
- In the current automotive industry, human operators perform wire harness assembly manually, which causes significant quality, productivity, safety, and ergonomic problems. Robotic assembly is a critical facilitator in addressing these problems. However, it remains challenging to implement for robotizing the assembly of wire harnesses. Wire harness assembly is a specific scenario of deformable linear object manipulation. Robotizing this assembly task demands robots to flexibly adapt their actions to the dynamically changing industrial environment based on robotic perception results. Existing research suggested the significance of robotic visual perception in the robotic assembly of wire harnesses. Implementing computer vision techniques is fundamental to enabling robots’ visual perception capabilities. Nonetheless, the industry has yet to introduce vision–based solutions to robotize wire harness assembly fully or partially. Through a systematic literature review, this article identifies fifteen scientific publications in vision–based robotized wire harness assembly. The results show various computer vision applications regarding wire harness components and assembly operations studied in previous research. Nevertheless, this article recognizes two significant challenges for computer vision applications in robotized wire harness assembly: (1) fulfilling production requirements on robustness and practicality and (2) exploiting the intrinsic physical features of wire harnesses for visual recognition. This article also advocated five prospective research directions toward more efficient and practical vision-based robotized wire harness assembly: (1) developing learning-based vision systems to exploit intrinsic features and multi–modality data of wire harnesses; (2) adapting vision systems proposed for robotizing assembly operations in manufacturing wire harnesses; (3) assessing the practicality, robustness, reliability, and sustainability of vision systems; (4) inquiring vision–based human–robot collaboration; and (5) exploring new product designs for facilitating visual recognition.
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| 5. |
- Wang, Hao, 1996, et al.
(författare)
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Deep Learning-Based Connector Detection for Robotized Assembly of Automotive Wire Harnesses
- 2023
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2023-August
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Konferensbidrag (refereegranskat)abstract
- The shift towards electrification and autonomous driving in the automotive industry results in more and more automotive wire harnesses being installed in modern automobiles, which stresses the great significance of guaranteeing the quality of automotive wire harness assembly. The mating of connectors is essential in the final assembly of automotive wire harnesses due to the importance of connectors on wire harness connection and signal transmission. However, the current manual operation of mating connectors leads to severe problems regarding assembly quality and ergonomics, where the robotized assembly has been considered, and different vision-based solutions have been proposed to facilitate a better perception of the robot control system on connectors. Nonetheless, there has been a lack of deep learning-based solutions for detecting automotive wire harness connectors in previous literature. This paper presents a deep learning-based connector detection for robotized automotive wire harness assembly. A dataset of twenty automotive wire harness connectors was created to train and evaluate a two-stage and a one-stage object detection model, respectively. The experiment results indicate the effectiveness of deep learning-based connector detection for automotive wire harness assembly but are limited by the design of the exteriors of connectors.
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| 6. |
- Wang, Hao, 1996, et al.
(författare)
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Overview of Computer Vision Techniques in Robotized Wire Harness Assembly: Current State and Future Opportunities
- 2023
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Ingår i: Procedia CIRP. - 2212-8271. ; 120, s. 1071-1076
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Konferensbidrag (refereegranskat)abstract
- Wire harnesses are essential hardware for electronic systems in modern automotive vehicles. With a shift in the automotive industry towards electrification and autonomous driving, more and more automotive electronics are responsible for energy transmission and safety-critical functions such as maneuvering, driver assistance, and safety system. This paradigm shift places more demand on automotive wire harnesses from the safety perspective and stresses the greater importance of high-quality wire harness assembly in vehicles. However, most of the current operations of wire harness assembly are still performed manually by skilled workers, and some of the manual processes are problematic in terms of quality control and ergonomics. There is also a persistent demand in the industry to increase competitiveness and gain market share. Hence, assuring assembly quality while improving ergonomics and optimizing labor costs is desired. Robotized assembly, accomplished by robots or in human-robot collaboration, is a key enabler for fulfilling the increasingly demanding quality and safety as it enables more replicable, transparent, and comprehensible processes than completely manual operations. However, robotized assembly of wire harnesses is challenging in practical environments due to the flexibility of the deformable objects, though many preliminary automation solutions have been proposed under simplified industrial configurations. Previous research efforts have proposed the use of computer vision technology to facilitate robotized automation of wire harness assembly, enabling the robots to better perceive and manipulate the flexible wire harness. This article presents an overview of computer vision technology proposed for robotized wire harness assembly and derives research gaps that require further study to facilitate a more practical robotized assembly of wire harnesses.
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| 7. |
- Wang, Hao, 1996
(författare)
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Toward Enabling Robotic Visual Perception for Assembly Tasks
- 2024
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Industry faces an urgent need for prospective solutions to scale up assembly automation, a challenge that requires immediate attention. In contemporary manufacturing, industrial robots need more intelligence to qualify for increasingly demanding flexible automation tasks. Research in artificial intelligence, computer vision, and robotics paints a promising picture of the future, where intelligent robots play a significant role in fostering sustainable and resilient manufacturing. However, academia and industry have yet to realize the potential of intelligent robots in production fully. This thesis plays a pivotal role in advancing the development of intelligent robots for flexible automation tasks, a crucial area of research in automation and robotics. Toward this goal, this thesis investigates perception, a prerequisite of intelligence, and mainly focuses on visual perception, a critical contactless perception approach. A multi-method research approach, comprising a qualitative literature study and a quantitative experimental study, was adopted to explore the challenges and prospective technical solutions to enabling robotic visual perception for assembly tasks. The research has identified four key challenges in enabling robotic visual perception for assembly tasks, particularly in developing and integrating vision systems in practical production. Additionally, the research has proposed six prospective directions for developing technical solutions, focusing on computer vision algorithms, dataset and benchmark, practical evaluation, human-robot collaboration, and product design.
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