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A study on intelligent grinding systems with industrial perspective

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Abstract

The digitization thrust on high-value manufacturing and services opens up new opportunities for ensuring total system uptime, reliability, and efficiency particularly for mission-critical high-value assets. The digitization process evolves intelligent manufacturing systems (IMS) which transforms maintenance into predictive reliability for achieving consistent quality throughout manufacturing process. This article unveils the intelligent grinding systems (IGS) for challenging grinding applications. In order to provide a better chance for value addition, previous work has been scrutinized extensively in the following aspects: grinding models, process design algorithms, and process monitoring. This then leads into an analysis of various previously designed IGS. The main focus, especially in the early 2000s, was mainly database development and parameter selection, which then shifted to process monitoring and control as particular technology advances were made. In the various goals that were investigated, it was evident that researchers were aiming for an online real-time system. This notion was driven by the advances in artificial intelligence and improved monitoring sensors, for example, acoustic emission sensors and even other unusual sensors like microphones for more economical and improved data collection and analysis. Although tremendous strides have been made, a substantial amount of work is still required in achieving a full-fledged real-time intelligent grinding system. The comprehensive findings on IGS system concludes that the real-time process update has been improved from few hours to milliseconds.

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Funding

This project was supported by fund NRF GRANT: INCENTIVE FUNDING FOR RATED RESEARCHERS (IPRR)–South Africa through Reference: IFR150204113619 and Grant No: 96066.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Cape Town, Cape Town, South Africa

    Ramesh Kuppuswamy, Fungai Jani, Samiksha Naidoo & Quintin de Jongh

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  1. Ramesh Kuppuswamy
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  2. Fungai Jani
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  3. Samiksha Naidoo
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  4. Quintin de Jongh
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Contributions

Fungai Jani: investigation, methodology, and writing—original draft. Samiksha Naidoo: investigation, conceptualization, methodology, validation, and support writing—original draft. Quintin de Jongh: investigation, conceptualization, methodology, validation, and support writing—original draft. Ramesh Kuppuswamy: supervision, project administration, resources, validation, and investigation.

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Correspondence to Ramesh Kuppuswamy.

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Kuppuswamy, R., Jani, F., Naidoo, S. et al. A study on intelligent grinding systems with industrial perspective. Int J Adv Manuf Technol 115, 3811–3827 (2021). https://doi.org/10.1007/s00170-021-07315-9

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