TY  - JOUR
T1  - A Decision Tree-Based Approach for Classifying and Characterizing the Failure Type of White Goods
AU  - Peker, Serhat
AU  - Solmaz, Çağlar
AU  - Doğan, Onur
PY  - 2025
DA  - September
Y2  - 2025
DO  - 10.54287/gujsa.1655744
JF  - Gazi University Journal of Science Part A: Engineering and Innovation
JO  - GU J Sci, Part A
PB  - Gazi University
WT  - DergiPark
SN  - 2147-9542
SP  - 858
EP  - 872
VL  - 12
IS  - 3
LA  - en
AB  - After-sales service plays a vital role in the white goods industry, significantly affecting both customer satisfaction and operational performance. This paper presents a decision tree-based approach for classifying and characterizing failure types in white goods, using after-sales service data from a white goods manufacturer. We employ the Classification and Regression Tree (CART) algorithm to identify patterns in failure occurrences based on product category, region, usage duration, and brand. The model generates interpretable decision rules, providing insights into the factors contributing to failures. The results reveal that product category and region are the most significant factors influencing product failures. These findings support manufacturers and service providers in optimizing maintenance strategies and improving service operations. The proposed approach enhances decision-making processes in after-sales service, leading to higher customer satisfaction and extended product life cycles.
KW  - Data Mining
KW  - Classification
KW  - Decision Tree Analysis
KW  - Rule-Based Approach
KW  - Predictive Maintenance
KW  - Business Analytics
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UR  - https://doi.org/10.54287/gujsa.1655744
L1  - https://dergipark.org.tr/en/download/article-file/4681495
ER  -