딥러닝을 이용한 핸드크림의 마찰 시계열 데이터 분류

• 영문명: Deep Learning-based Approach for Classification of Tribological Time Series Data for Hand Creams
• 발행기관: 한국산업경영시스템학회
• 저자명: 김지원(Ji Won Kim) 이유민(You Min Lee) 한상헌(Shawn Han) 김경택(Kyeongtaek Kim)
• 간행물 정보: 『산업경영시스템학회지』제44권 제3호, 98~105쪽, 전체 8쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2021.09.30

영문 초록

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

목차

1. 서론

2. 배경

3. 실험장치 및 실험방법

4. 분석방법

5. 실험 및 분석

6. 결론

키워드

Time Series Classification Deep Learning Tribology Cosmetics