Conveyor Performance based on Motor DC 12 Volt Eg-530ad-2f using K-Means Clustering

IAES International Conference on Electrical Engineering, Computer Science and Informatics

电工学;计算机科学

Arifin, Zaenal^1 ; Artini, Sri D.P.^1 ; Ibnu Subroto, Imam Much^1

Electrical Engineering Department, Universitas Islam Sultan Agung, Semarang, Indonesia^1

关键词: clustering;    Clustering analysis;    Clustering data;    K;    means clustering;    K-means;    Performance based;    Production process;    Separation process;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/190/1/012002/pdf
DOI  :  10.1088/1757-899X/190/1/012002

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

To produce goods in industry, a controlled tool to improve production is required. Separation process has become a part of production process. Separation process is carried out based on certain criteria to get optimum result. By knowing the characteristics performance of a controlled tools in separation process the optimum results is also possible to be obtained. Clustering analysis is popular method for clustering data into smaller segments. Clustering analysis is useful to divide a group of object into a k-group in which the member value of the group is homogeny or similar. Similarity in the group is set based on certain criteria. The work in this paper based on K-Means method to conduct clustering of loading in the performance of a conveyor driven by a dc motor 12 volt eg-530-2f. This technique gives a complete clustering data for a prototype of conveyor driven by dc motor to separate goods in term of height. The parameters involved are voltage, current, time of travelling. These parameters give two clusters namely optimal cluster with center of cluster 10.50 volt, 0.3 Ampere, 10.58 second, and unoptimal cluster with center of cluster 10.88 volt, 0.28 Ampere and 40.43 second.