A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company

Based on the findings of Massachusetts Institute of Technology, organizations’ data double every five years. However, the rate of using data is 0.3. Nowadays, data mining tools have greatly facilitated the process of knowledge extraction from a welter of data. This paper presents a hybrid model usin...

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Main Authors: Seyedehpardis Bagherighadikolaei, Rouzbeh Ghousi, Abdolrahman Haeri
Format: Article
Language:English
Published: Islamic Azad University, Qazvin Branch 2020-07-01
Series:Journal of Optimization in Industrial Engineering
Subjects:
Online Access:http://www.qjie.ir/article_671443_06043ebe343f5035546caef7efb70da2.pdf
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spelling doaj-322f20db52d840f3865a334dee3124102021-03-14T05:31:42ZengIslamic Azad University, Qazvin BranchJournal of Optimization in Industrial Engineering2251-99042423-39352020-07-0113210112110.22094/joie.2020.1863364.1630671443A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing companySeyedehpardis Bagherighadikolaei0Rouzbeh Ghousi1Abdolrahman Haeri2School of Industrial Engineering, I.U.S.T Tehran, IranSchool of Industrial Engineering, I.U.S.T Tehran, IranSchool of Industrial Engineering, I.U.S.T Tehran, IranBased on the findings of Massachusetts Institute of Technology, organizations’ data double every five years. However, the rate of using data is 0.3. Nowadays, data mining tools have greatly facilitated the process of knowledge extraction from a welter of data. This paper presents a hybrid model using data gathered from an ATM manufacturing company. The steps of the research are based on CRISP-DM. Therefore, based on the first step, business understanding, the company and its different units were studied. After business understanding, the data collected from sale's unit were prepared for preprocess. While preprocessing, data from some columns of dataset, based on their types and purpose of the research, were either categorized or coded. Then, the data have been inserted into Clementine software, which resulted in modeling and pattern discovery. The results clearly state that, the same Machines’ Code and the same customers in different provinces are struggling with significantly different Problems’ Code, that could be due to weather condition, culture of using ATMs, and likewise. Moreover, the same Machines’ Code and the same Problems’ Code, as well as differences in Technicians' expertise, seems to be some causes to significantly different Repair Time. This could be due to Technicians' training background level of their expertise and such. At last, the company can benefit from the outputs of this model in terms of its strategic decision-making.http://www.qjie.ir/article_671443_06043ebe343f5035546caef7efb70da2.pdfdata miningclusteringassociation rulesclassificationautomated teller machine (atm)
collection DOAJ
language English
format Article
sources DOAJ
author Seyedehpardis Bagherighadikolaei
Rouzbeh Ghousi
Abdolrahman Haeri
spellingShingle Seyedehpardis Bagherighadikolaei
Rouzbeh Ghousi
Abdolrahman Haeri
A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
Journal of Optimization in Industrial Engineering
data mining
clustering
association rules
classification
automated teller machine (atm)
author_facet Seyedehpardis Bagherighadikolaei
Rouzbeh Ghousi
Abdolrahman Haeri
author_sort Seyedehpardis Bagherighadikolaei
title A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
title_short A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
title_full A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
title_fullStr A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
title_full_unstemmed A Data Mining approach for forecasting failure root causes: A case study in an Automated Teller Machine (ATM) manufacturing company
title_sort data mining approach for forecasting failure root causes: a case study in an automated teller machine (atm) manufacturing company
publisher Islamic Azad University, Qazvin Branch
series Journal of Optimization in Industrial Engineering
issn 2251-9904
2423-3935
publishDate 2020-07-01
description Based on the findings of Massachusetts Institute of Technology, organizations’ data double every five years. However, the rate of using data is 0.3. Nowadays, data mining tools have greatly facilitated the process of knowledge extraction from a welter of data. This paper presents a hybrid model using data gathered from an ATM manufacturing company. The steps of the research are based on CRISP-DM. Therefore, based on the first step, business understanding, the company and its different units were studied. After business understanding, the data collected from sale's unit were prepared for preprocess. While preprocessing, data from some columns of dataset, based on their types and purpose of the research, were either categorized or coded. Then, the data have been inserted into Clementine software, which resulted in modeling and pattern discovery. The results clearly state that, the same Machines’ Code and the same customers in different provinces are struggling with significantly different Problems’ Code, that could be due to weather condition, culture of using ATMs, and likewise. Moreover, the same Machines’ Code and the same Problems’ Code, as well as differences in Technicians' expertise, seems to be some causes to significantly different Repair Time. This could be due to Technicians' training background level of their expertise and such. At last, the company can benefit from the outputs of this model in terms of its strategic decision-making.
topic data mining
clustering
association rules
classification
automated teller machine (atm)
url http://www.qjie.ir/article_671443_06043ebe343f5035546caef7efb70da2.pdf
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