Onur Doğan  
Endüstri Yüksek Mühendisi
Araştırma Görevlisi
 
Anasayfa Biyografi Endüstri Mühendisliği Bilgi-İnsan Kaynağı Eğlence İletişim
Bilimsel Çalışmalar
ICENS 2017 | 3rd International Conference on Engineering and Natural Sciences (ICENS 2017) | 3-7 May 2017, Budapest, Hungary
A Roadmap for Data Driven Decision Making to Improve Quality
Dogan Onur

Abstract

Many quality improvement programs including inspection, statistical process control, total quality control, zero defects, kaizen and lean six sigma, which is the most recognized, require collection and analysis of data to solve quality problems. With six sigma as a quality improvement program, the errors in the manufacturing are reduced to the error level of 3.4 parts per million and it is aimed to go to zero defect. With lean manufacturing, the lead-time is shortened and quality is improved by determining and eliminating all kinds of waste in the processes. Lean six sigma uses so called define-measure-analyze-improve-control (DMAIC) approach to reach six sigma quality levels, less than 3.4 part per million defectives, by reducing variations and wastes within processes. To achieve the goal depends on collection of data to attack quality problems.
Although many traditional data analysis tools can be used to develop quality of products and processes, now with industry 4.0, massive data sets collected through computerized systems should be mined with powerful data analysis methods. Data mining involves techniques used to produce meaningful results from data stacks. It is possible to make effective and quick decisions by utilizing these techniques in five steps of lean six. The use of data mining at every stage, especially in the measure and analyze stages, has critical importance to make powerful decisions.
The aim of this study is to provide a roadmap that allows companies that apply lean six sigma to make faster, more reliable and satisfied decisions with data. On the one hand, it will contribute to the manufacturing processes with lean six sigma by reducing the lead-time, producing better quality products; on the other hand, it will aid to make effective decisions using data mining techniques.

Keywords: Data mining, Lean six sigma, Quality improvement
 

Sitedeki yazılar Onur DOĞAN'ın ve diğer yazarların izni alınmadan başka bir web sitesine konulamaz, ancak link verilebilir. Sorumlu davranışınızdan dolayı teşekkür ederiz.

 
Posts on the site can not be placed on another website without the permission of Onur DOĞAN and other authors, but links can be given. Thank you for your responsible behavior.
 
Güncelleme 06.11.2017
www.onurdogan.net |©Copyright 2012 - 2017| Designed by oDogan