Identification and Clustering Outsourcing Risks of Aviation Part- Manufacturing Projects in Aviation Industries Organization Using Kmeans Method
Subject Areas :
Alireza Abbasi
1
,
Mehrdad Nikbakht
2
1 - Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Keywords: Data mining, Clustering, Risk, K- means Method, Aviation Industries, Manufacturing Project,
Abstract :
The purpose of this paper is to identify and clustering strategic risks in the outsourcing field of partmanufacturingprojects of aviation products, that whit survey carried out through the study ofliterature and experts opinion, meanwhile, identification risk groups in this area through interview,identified cases and factors of risks through FMEA technique, finally, 50 strategic risks identified in7 titles. In the following to resolve problems of traditional FMEA method, with definition threeindicators risk include, risk intensity, occurrence probability, and confrontation frequency by aquestionnaire and considering from three factors outsourcing assess contain cost, time and quality,risks of this area were clustered to K-means clustering and using SPSS software in 4 cluster includeof significant risks, high level of risks, medium level of risks and low level of risks. Thus, theclustering of risks for decision-making and planning of suggested actions at the time of theiroccurrence, basis for future improvements will be provided to carry out the continuousimprovement process at appropriate intervals with assessment of actions taken, the rate ofimprovement identified and therefore appropriate decisions are achieved.