Apriori算法在金属复合产品质量控制中的应用
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摘要
为提高某种金属复合产品的质量,将数据挖掘技术应用于金属复合产品质量控制。提出一种基于关联规则Apriori算法的生产过程控制模型,并从该复合产品的600组生产数据中挖掘原材料厚度和复合比例之间的关联关系。实验证明,生产过程控制模型对于产品质量的提高及成本控制具有一定的帮助,可用于生产过程的指导。
To improve the quality of a metal composite product,data mining is applied to quality control of metal composite product in this paper. A production process control model is proposed based on Apriori algorithm,and the correlations between the thickness of raw materials and composite ratio are discovered from 600 production data of the product. Experimental results indicate that production process control model is helpful for product quality improvement and cost controlling,and can be used to guide production process.
To improve the quality of a metal composite product,data mining is applied to quality control of metal composite product in this paper. A production process control model is proposed based on Apriori algorithm,and the correlations between the thickness of raw materials and composite ratio are discovered from 600 production data of the product. Experimental results indicate that production process control model is helpful for product quality improvement and cost controlling,and can be used to guide production process.
引文
[1]董小格.基于数据挖掘的焊件质量诊断技术研究[D].大庆:东北石油大学,2012.
[2]王雅轩,琐聪.数据挖掘技术的综述[J].电子技术与软件工程,2015,4(8):204-205.
[3]宋敏,王社伟.一种基于关联分析的装配质量数据挖掘方法[J].制造业自动化,2013,35(8):77-80.
[4]Shahbaz M,Srinivas J,Harding A,et al.Product design and manufacturing process improvement using association rules[J].Professional Engineering Publishing,2015,220(2):243-254.
[5]张丽芳,陆新建.Apriori算法在流程工业质量控制中的应用研究[J].计算机工程与设计,2009,30(13):3228-3230.
[6]张红艳,都娟.关联规则中Apriori算法中的应用[J].数字技术与应用,2011(08):14-15.
[7]顾辉,杨青,蒋成功,等.关联规则在成绩分析中的研究及应用[J].计算机应用,2015,35(S1):149-151.
[8]崔妍,包志强.关联规则挖掘综述[J].计算机应用研究,2016,33(2):330-334.
[9]Peter Harrington.机器学习实战[M].北京:人民邮电出版社,2013:223-239.
[10]耿晓斐.关联规则中EClat算法的研究与应用[D].重庆:重庆大学,2009.
[11]刘娟,宋安军.改进FP-growth算法在气象预报中的应用[J].计算机系统应用,2016,25(10):199-204.
[12]Bernard K F,Fabien R.Mining association rules for the quali-ty improvement of the productionprocess[J].Expert Systems with Applications,2013,40(4):1034-1045.
[13]晏杰,亓文娟.基于Apriori&FP-growth算法的研究[J].计算机系统应用,2013,22(5):122-125.
[14]方洪鹰.数据挖掘中数据预处理的方法研究[D].重庆:西南大学,2009.
[2]王雅轩,琐聪.数据挖掘技术的综述[J].电子技术与软件工程,2015,4(8):204-205.
[3]宋敏,王社伟.一种基于关联分析的装配质量数据挖掘方法[J].制造业自动化,2013,35(8):77-80.
[4]Shahbaz M,Srinivas J,Harding A,et al.Product design and manufacturing process improvement using association rules[J].Professional Engineering Publishing,2015,220(2):243-254.
[5]张丽芳,陆新建.Apriori算法在流程工业质量控制中的应用研究[J].计算机工程与设计,2009,30(13):3228-3230.
[6]张红艳,都娟.关联规则中Apriori算法中的应用[J].数字技术与应用,2011(08):14-15.
[7]顾辉,杨青,蒋成功,等.关联规则在成绩分析中的研究及应用[J].计算机应用,2015,35(S1):149-151.
[8]崔妍,包志强.关联规则挖掘综述[J].计算机应用研究,2016,33(2):330-334.
[9]Peter Harrington.机器学习实战[M].北京:人民邮电出版社,2013:223-239.
[10]耿晓斐.关联规则中EClat算法的研究与应用[D].重庆:重庆大学,2009.
[11]刘娟,宋安军.改进FP-growth算法在气象预报中的应用[J].计算机系统应用,2016,25(10):199-204.
[12]Bernard K F,Fabien R.Mining association rules for the quali-ty improvement of the productionprocess[J].Expert Systems with Applications,2013,40(4):1034-1045.
[13]晏杰,亓文娟.基于Apriori&FP-growth算法的研究[J].计算机系统应用,2013,22(5):122-125.
[14]方洪鹰.数据挖掘中数据预处理的方法研究[D].重庆:西南大学,2009.