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Open Access
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Prasanna Khandarkar, Shyam Ingle, Adwait Kulkarni, Sapana S. Kamble
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- Student, Student, Student, Professor Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Pune, Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Pune, Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Pune, Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Pune Maharashtra, Maharashtra, Maharashtra, Maharashtra India, India, India, India
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Abstract
nThe project introduces a new method for sampling data from a group, addressing limitations in traditional approaches. It highlights inefficiencies in inspecting only a few items from a batch, potentially leading to the rejection of entire lots due to isolated errors. To counter these challenges, a system is being designed to automatically inspect every gear in a batch. This system incorporates a conveyor belt for gear movement and a camera for analyzing gear parameters. Parameters are compared against those stored in a backend database, with gears meeting the specified criteria directed to the accepted lot and those failing diverted to the rejected lot using a shooting gun mechanism. This automated approach aims to enhance efficiency and accuracy in quality control, eliminating manual inspection and reducing the risk of rejecting entire lots due to isolated errors.
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Keywords: Gear, MATLAB, Image processing, Manufacturing industries, Power transmission
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Production Research & Management(joprm)]
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References
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- Cheng Pengfei and Feng Changyong Henan, “Characteristic Value Extraction of Gear Defect Based on Image Processing”, ‘Journal of Multimedia’, 2013, Volume- 8, pp 198-205.
- Alkhadafe, A. Al-Habaibeh, A. Lotfi, Condition monitoring of helical gears using automated selection of features and sensors, Measurement (2016)
- Hazrat Ali, Syuhei Kurokawa,Kensuke Uesugi ‘ Camera Based Precision Measurement In Improving Measurement Accuracy’ Measurement 49(2014) 138-147.
- Zhang Jing, “The Research on the Application to Digital Image Technology in Hypoid Gear Contact Zone Detection”, ‘Journal of Computers’, 2011, Volume-. 6, PP 1519-1525
- García-Hernández, C., Gella-Marín, R., Huertas-Talón, J. L., & Berges-Muro, L. (2016). Algorithm for measuring gears implemented with general-purpose spreadsheet software. Measurement, 85, 1-12.
- Wan, F., Luo, H., & Liu, J. (2019, August). Online high-precision vision measurement method for large-size gear parameters. In Proceedings of the 2019 2nd International Conference on Robot Systems and Applications (pp. 20-24).
- Wijaya, T., Caesarendra, W., Tjahjowidodo, T., Pappachan, B. K., Wee, A., & Roslan, M. I. (2018). A review on sensors for real-time monitoring and control systems on machining and surface finishing processes.
- Khan, A. W., & Chen, W. (2009, February). Calibration of CNC milling machine by direct method. In 2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications (Vol. 7160, pp. 266-275). SPIE.
- Moroni, G., & Petrò, S. (2013). Automatic cutting-edge detection for a cylindrical mill. High value manufacturing: advanced research in virtual and rapid prototyping. CRC Press, Boca Raton, 457-461.
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| Volume | 14 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | April 23, 2024 | |
| Accepted | May 3, 2024 | |
| Published | May 24, 2024 |
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