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Research on parallel distributed clustering algorithm applied to cutting parameter optimization
- Wei, X. (author)
- Sun, Q. (author)
- Liu, X. (author)
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- Yue, C. (author)
- Liang, S. Y. (author)
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- (creator_code:org_t)
- 2022-05-05
- 2022
- English.
- In: The International Journal of Advanced Manufacturing Technology. - : Springer Nature. - 0268-3768 .- 1433-3015. ; 120:11-12, s. 7895-7904
- Journal article (peer-reviewed)
Abstract
Subject headings
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- In the big data era, traditional data mining technology cannot meet the requirements of massive data processing with the background of intelligent manufacturing. Aiming at insufficient computing power and low efficiency in mining process, this paper proposes a improved K-means clustering algorithm based on the concept of distributed clustering in cloud computing environment. The improved algorithm (T.K-means) is combined with MapReduce computing framework of Hadoop platform to realize parallel computing, so as to perform processing tasks of massive data. In order to verify the practical performance of T.K-means algorithm, taking machining data of milling Ti-6Al-4V alloy as the mining object. The mapping relationship among cutting parameters, surface roughness, and material removal rate is mined, and the optimized value for cutting parameters is obtained. The results show that T.K-means algorithm can be used to mine the optimal cutting parameters, so that the best surface roughness can be obtained in milling Ti-6Al-4V titanium alloy.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- Big data
- Cutting parameter optimization
- Data mining
- Distributed clustering
- MapReduce framework
- T.K-means algorithm
- Aluminum alloys
- K-means clustering
- Metadata
- Milling (machining)
- Parameter estimation
- Surface roughness
- Ternary alloys
- Titanium alloys
- Vanadium alloys
- Computing power
- Cutting parameters
- Cutting parameters optimizations
- Data mining technology
- Distributed clustering algorithm
- Intelligent Manufacturing
- Mapreduce frameworks
- Massive data
- TK-mean algorithm
Publication and Content Type
- ref (subject category)
- art (subject category)
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- Wei, X.
- Sun, Q.
- Liu, X.
- Yue, C.
- Liang, S. Y.
- Wang, Lihui
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- Royal Institute of Technology
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