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Information Journal Paper

Title

Clustering of Ornamental Stones Based Upon the Sawability by Using the Fuzzy Clustering Technique

Pages

  137-148

Abstract

 Summary: The complete knowledge of the cutting process and the performance of sawing machine can help increase the efficiency and quality of the manufactured product. During the field studies, 12 rock samples from two kinds of Ornamental stone were collected and some major Mechanical properties including uniaxial compressive strength (UCS), Mohs hardness (Mh), Schimazek’ s F-abrasiveness factors (SF-a) and young modulus (YM) were measured. Also, Fuzzy C-means has been used as a soft computing technique in this study. All different studied rock samples are classified into 3, 4 and 5 classes. Then, the results of classification were compared with consumed energy values. Finally, it can be concluded that FCM could be a simple but efficient tool in evaluation of the Sawability of Ornamental stone as one of the most important factors to estimation and prediction of production cost and productivity of processing plant. Introduction: The rock Sawability and prediction of consumed energy is one of the most important factors to estimation and prediction of production cost and productivity of processing plant. In this study, for laboratory tests, some rock blocks were collected from the studied quarries. Then, by using the fuzzy C-means clustering approached and considering laboratory results of rock samples, all of rocks have been classified in 3, 4 and 5 separate clusters. The results clearly showed that FCM algorithm used as a reliable and efficient tool for classifying the Ornamental stone. Methodology and Approaches: Nowadays, with the increasing growth of uncertain problems, the use of soft computing techniques with a high ability in solving these kinds of problems has increased significantly. Assessment of the Sawability of Ornamental stone is a most important factor in identification and prediction of production cost and productivity of processing plant. Given the unreliability of all experimental labatory, one of the most important tasks in the Sawability of Ornamental stone’ classification is using a method with the highest possible accuracy. According to the importance of the issue, in this study, Fuzzy C-means algorithm is used for the classification. Four important physical and mechanical characteristics of 12 rock samples are considered for the classification of Sawability of Ornamental stone from two kinds of Ornamental stone, including hard and soft rock groups using Fuzzy C-means Optimization, including uniaxial compressive strength, Mohs hardness, Schmiazek F-abrasivity factor and Young's modulus. Finally, in this study, the results of classification are compared with consumed energy. Results and Conclusions: In this study employing Fuzzy C-means as soft computing technique and some major Mechanical properties such as uniaxial compressive strength, Mohs hardness, Schmiazek F-abrasivity factor and Young's modulus to evaluate the Sawability of Ornamental stone, 3 to 5 classes are considered. Generally, according to this research, the following remarks can be concluded: 1-The 12 rock samples from two kinds of Ornamental stone, including hard and soft rock groups, are evaluated and tested. 2-A comparison was made between 3 different models (3 classes from 3 to 5 classes) with consumed energy of sawing machine. The results show that all 12 rock samples are classified as very suitable. 3-In comparison to all classes, it can be concluded that FCM is a reliable technique for clustering the Sawability of Ornamental stone with highly acceptable degrees of robustness

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    APA: Copy

    MIKAEIL, REZA, Shaffiee Haghshenas, Sina, & ATAEI, MOHAMMAD. (2020). Clustering of Ornamental Stones Based Upon the Sawability by Using the Fuzzy Clustering Technique. JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING, 10(24 ), 137-148. SID. https://sid.ir/paper/385173/en

    Vancouver: Copy

    MIKAEIL REZA, Shaffiee Haghshenas Sina, ATAEI MOHAMMAD. Clustering of Ornamental Stones Based Upon the Sawability by Using the Fuzzy Clustering Technique. JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING[Internet]. 2020;10(24 ):137-148. Available from: https://sid.ir/paper/385173/en

    IEEE: Copy

    REZA MIKAEIL, Sina Shaffiee Haghshenas, and MOHAMMAD ATAEI, “Clustering of Ornamental Stones Based Upon the Sawability by Using the Fuzzy Clustering Technique,” JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING, vol. 10, no. 24 , pp. 137–148, 2020, [Online]. Available: https://sid.ir/paper/385173/en

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