| dc.description.abstract | Over the past few years, the market has shifted away from mass production towards mass customization and personalized production. This shift has made it necessary for manufacturing companies to change their manufacturing line more frequently, which can be both expensive and time-consuming. To overcome this challenge, reconfigurable manufacturing systems (RMS) have been proposed as a solution. However, there are numerous challenges associated with RMS, including a lack of research on physical implementation and automating the system, designing a new layout due to complexity, and time-consuming reprogramming of robots and other machines.
This research addresses the gaps and challenges in the physical implementation and automation of RMS. A physical platform-based RMS has been developed, which can be reconfigured automatically without any human intervention. The system uses a mobile robot to move and reconfigure different platforms, which has led to the concept of a highly flexible RMS being proposed.
Furthermore, this research investigates the impact of Industry 4.0 technologies on RMS. The study involves integrating additive manufacturing, advanced robotics, industrial big data, digital twin and simulation, and industrial internet of things (IIoT) into the physically highly flexible RMS to enhance its efficiency and performance. Wireless power transfer (WPT) is also proposed as an Industry 4.0 technology to wirelessly electrify the highly flexible RMS. Additionally, multiple Industry 4.0 technologies are used together to address the issues of layout design and reprogramming of RMS. This includes the proposal of a smart layout design system and a framework for developing an intelligent and self-RMS. | en_US |
| dc.description.popularabstract | As we increasingly crave unique, tailor-made products, manufacturers are moving from large-scale standard production to personalized goods. However, frequently switching up production isn't easy or cheap. Imagine a factory floor that needs to be rearranged daily!
Enter Reconfigurable Manufacturing Systems (RMS). Think of RMS like adaptable building blocks for factories. While RMS is promising, it’s faced hurdles like design complications and the tedious task of reprogramming robots.
Our research offers a cutting-edge solution. We’ve created an RMS that can reshape itself, much like playing Tetris, without human help. A robot moves and reconfigures sections of the production space, offering a dynamic factory floor. We've integrated the latest industrial technologies into our RMS. From 3D printing and next-gen robotics to real-time data analytics, a digital mirror of the factory, and interconnected devices, our RMS is smarter and more efficient. One standout feature is the ability to power these dynamic systems wirelessly, eliminating cumbersome cables. Our study also introduces a smart design system, ensuring that the RMS layout is optimal, and a blueprint for a intelligent RMS. | en_US |
| dc.relation.haspart | <p>Paper 1: Arnarson, H. & Solvang, B. (2022). Reconfigurable autonomous industrial mobile manipulator system. <i>2022 IEEE/SICE International Symposium on System Integration (SII), 2022</i>, 772-777. (Accepted manuscript version). Also available in Munin at <a href=https://hdl.handle.net/10037/28585>https://hdl.handle.net/10037/28585</a>. Published version available at <a href=https://doi.org/10.1109/SII52469.2022.9708887>https://doi.org/10.1109/SII52469.2022.9708887</a>.
<p>Paper 2: Arnarson, H., Mahdi, H., Solvang, B. & Bremdal, B.A. (2022). Towards automatic configuration and programming of a manufacturing cell. <i>Journal of Manufacturing Systems, 64</i>, 225-235. Also available in Munin at <a href=https://hdl.handle.net/10037/27668>https://hdl.handle.net/10037/27668</a>.
<p>Paper 3: Arnarson, H., Sæterbø, M., Khan, N. & Solvang, B. Reconfigurable 3D printing platform for warehouses. (Accepted manuscript). Now published in <i>2023 28th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, available at <a href=https://doi.org/10.1109/ETFA54631.2023.10275441>https://doi.org/10.1109/ETFA54631.2023.10275441</a>.
<p>Paper 4: Arnarson, H., Bremdal, B.A. & Hanssen, M.F. Towards automatic generation of image recognition models for industrial robot arms. (Accepted manuscript). Now published in <i>2023 28th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, available at <a href=https://doi.org/10.1109/ETFA54631.2023.10275616>https://doi.org/10.1109/ETFA54631.2023.10275616</a>.
<p>Paper 5: Arnarson, H., Bremdal, B.A. & Solvang, B. (2022). Reconfigurable Manufacturing: Towards an industrial Big Data approach. <i>IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2022</i>, 632-637, (Accepted manuscript version). Also available in Munin at <a href=https://hdl.handle.net/10037/28583>https://hdl.handle.net/10037/28583</a>. Published version available at <a href=https://doi.org/10.1109/AIM52237.2022.9863341>https://doi.org/10.1109/AIM52237.2022.9863341</a>.
<p>Paper 6: Mahdi, H., Arnarson, H., Solvang, B. & Bremdal, B.A. (2023). Investigation of wireless electrification for a reconfigurable manufacturing cell. <i>Journal of Manufacturing Systems, 67</i>, 379-388. Also available in Munin at <a href=https://hdl.handle.net/10037/30526>https://hdl.handle.net/10037/30526</a>.
<p>Paper 7: Arnarson, H., Yu, H., Olavsbråten, M.M., Bremdal, B.A. & Solvang, B. (2023). Towards smart layout design for a reconfigurable manufacturing system. <i>Journal of Manufacturing Systems, 68</i>, 354-367. Also available in Munin at <a href=https://hdl.handle.net/10037/29188>https://hdl.handle.net/10037/29188</a>.
<p>Paper 8: Arnarson, H., Tahir, S.A.R., Shu, B., Bremdal, B.A. & Solvang, B. Intelligent and self-reconfigurable manufacturing system. (Accepted manuscript). To be published in <i>Procedia Computer Science, 5th International Conference on Industry 4.0 and Smart Manufacturing</i>. | en_US |
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