Campus Units
Industrial and Manufacturing Systems Engineering
Document Type
Article
Publication Version
Published Version
Publication Date
12-21-2020
Journal or Book Title
Logistics
Volume
4
Issue
4
First Page
35
Research Focus Area(s)
Operations Research
DOI
10.3390/logistics4040035
Abstract
The rising popularity of smart factories and Industry 4.0 has made it possible to collect large amounts of data from production stages. Thus, supervised machine learning methods such as classification can viably predict product compliance quality using manufacturing data collected during production. Elimination of uncertainty via accurate prediction provides significant benefits at any stage in a supply chain. Thus, early knowledge of product batch quality can save costs associated with recalls, packaging, and transportation. While there has been thorough research on predicting the quality of specific manufacturing processes, the adoption of classification methods to predict the overall compliance of production batches has not been extensively investigated. This paper aims to design machine learning based classification methods for quality compliance and validate the models via case study of a multi-model appliance production line. The proposed classification model could achieve an accuracy of 0.99 and Cohen’s Kappa of 0.91 for the compliance quality of unit batches. Thus, the proposed method would enable implementation of a predictive model for compliance quality. The case study also highlights the importance of feature construction and dataset knowledge in training classification models.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Owner
The Author(s)
Copyright Date
2020
Language
en
File Format
application/pdf
Recommended Citation
Sankhye, Sidharth and Hu, Guiping, "Machine Learning Methods for Quality Prediction in Production" (2020). Industrial and Manufacturing Systems Engineering Publications. 256.
https://lib.dr.iastate.edu/imse_pubs/256
Comments
This article is published as Sankhye, Sidharth, and Guiping Hu. "Machine Learning Methods for Quality Prediction in Production." Logistics 4, no. 4 (2020): 35. DOI: 10.3390/logistics4040035. Posted with permission.