Browsing by Author "Alhijaily, Abdullah"

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Development of Robots and Algorithms for Cooperative Additive Manufacturing
(University of Manchester, 2024-04-11) Alhijaily, Abdullah; Bartolo, Paulo; Cangelosi, Angelo
Additive manufacturing (AM) is dominated by single robots which present limitations in fabrication time and efficiency of the system. To address this problem, this research explores the concept of cooperative printing in which multiple printheads fabricate the same part concurrently. However, configurations for cooperative printing in the literature present several limitations such as reduced cooperative printing area and cross prevention in which no two printheads are allowed to cross each other's paths during printing. Thus, a novel configuration is proposed in this research. This configuration was realised on a custom gantry machine. As shown, the proposed configuration allows printing parts that are impossible to print or inefficiently printed by other cooperative printing configurations. Furthermore, several novel algorithms are formulated and implemented in the developed machine. Additionally, efficient algorithms were developed for path planning that allowed to reduce the computation time of slicing for cooperative printing from minutes to milliseconds. Also, the proposed system significantly increased the printing speed surpassing the maximum printing time reduction reported in the literature. Conversely, mobile robots are promising for AM due to their large workspace. However, current plastic AM by mobile robots produce parts with poor quality and rough surface finish. Thus, an accurate mobile robot specialised for mobile AM is developed for this research. The proposed mobile robot's accuracy and precision were assessed and was found to have a 0.37 mm average error surpassing the literature on mobile AM. Finally, it was shown that the developed mobile robot surpasses them both in terms of quality and accuracy. For gantry systems, offline path planning is reliable and efficient due to their high accuracy and predictability. However, it is unreliable for low accuracy and error-prone systems such as mobile robots. To overcome this, an online cooperative printing path planning designed for the developed mobile robot is proposed. Several novel real time algorithms were developed, including a novel online collision avoidance algorithm that guaranteed collision-free motions. This research stands as the first work to develop fully online path planning for cooperative printing.
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Remote Monitoring and Controlling of Additive Manufacturing Machines Using Industry 4.0 Principles
(University of Manchester, 2019-11-22) Alhijaily, Abdullah; Bartolo, Paulo
Manufacturing has seen many changes over the years; some of these changes correspond to new paradigms and are usually associated with industrial revolutions. Industry 4.0, the fourth industrial revolution, is continuing the improvements that the past industrial revolutions have done to manufacturing. It aims to impact the physical world by utilizing digital technologies. This research reviewed the concept of Industry 4.0 and key associated techniques such as the Internet of Things (IoT) and Cloud Computing. The ability to integrate different technologies in an Industry 4.0 environment to improve manufacturing is also discussed. Significant details are provided to additive manufacturing, a key element of Industry 4.0. However, as observed few attempts were made to integrate Additive Manufacturing with other technologies in an Industry 4.0 environment. This research addresses these limitations through the development of a computational application to remotely control and monitor any additive manufacturing machine, using cyber physical systems, cloud computing, and IoT. The research also applied the developed system on an additive manufacturing machine at The University of Manchester as a case study. The system opens up new dimensions for additive manufacturing by allowing the access of any machine from any place at any time. This improves the utilization of machines. Moreover, the system opens new opportunities for mass personalization.
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