Comparison between ANN and multiple linear regression models for prediction of warranty cost

• Main Authors: Mohd Faaizie, Darmawan, Nur Izzati, Jamahir, Saedudin, Rd Rohmat, Shahreen, Kasim
• Format: Article
• Language: English
• Published: Penerbit UTHM 2018
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/29839/1/Comparison%20between%20ANN%20and%20multiple%20linear%20regression%20models.pdf; http://umpir.ump.edu.my/id/eprint/29839/; https://doi.org/10.30880/ijie.2018.10.06.027; https://doi.org/10.30880/ijie.2018.10.06.027
• Institution: Universiti Malaysia Pahang

Nowadays, warranty has its own priority in business strategy for a manufacturer to protect their benefit as well as the intense competition between the manufacturers. In fact, warranty is a contract between manufacturer and buyer in which the manufacturer gives the buyer certain assurances as the condition of the property being sold. In industry, an accurate prediction of warranty costs is often counted by the manufacturer. Underestimation or overestimation of the warranty cost may have a high influence to the manufacturers. This paper presents a methodology to adapt historical maintenance warranty data with comparison between Artificial Neural Network (ANN) and multiple linear regression approach.