TY - JOUR
T1 - Prediction of a standard requirement for the development of modular architecture-based gasoline turbo engine using time series analysis
AU - Chung, Seung Hyun
AU - Park, Joonyoung
AU - Um, Jin Yeong
N1 - Publisher Copyright:
© 2020 Alpha Publishers. All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - Environmental regulations have been tightened since Volkswagen's diesel gates. To cope with environmental regulations, eco-friendly cars should be developed, but due to the high price, it is difficult to be accepted by all consumers. As customer needs diversify, the product life cycle is shortening and needs to be addressed. Manufacturers need to innovate their processes to diversify their products and reduce lead times. This paper aims to predict long-term future engine torque to secure development efficiency and competitiveness of internal combustion engines, which are the major components of automobiles. Sales data for 20 years from 1998 to 2017 were used, with weights based on sales volume. Based on the above data, time series analysis was conducted using three methods, MA, ARIMA, and Fitted Regression. The results of the prediction for each segment were derived, and the engine can be used to plan the engine with appropriate torque.
AB - Environmental regulations have been tightened since Volkswagen's diesel gates. To cope with environmental regulations, eco-friendly cars should be developed, but due to the high price, it is difficult to be accepted by all consumers. As customer needs diversify, the product life cycle is shortening and needs to be addressed. Manufacturers need to innovate their processes to diversify their products and reduce lead times. This paper aims to predict long-term future engine torque to secure development efficiency and competitiveness of internal combustion engines, which are the major components of automobiles. Sales data for 20 years from 1998 to 2017 were used, with weights based on sales volume. Based on the above data, time series analysis was conducted using three methods, MA, ARIMA, and Fitted Regression. The results of the prediction for each segment were derived, and the engine can be used to plan the engine with appropriate torque.
KW - ARIMA
KW - Data mining
KW - Fitted Regression
KW - Integrated Product Planning
KW - Market Needs Forecasting
KW - Time series analysis
UR - http://www.scopus.com/inward/record.url?scp=85090679507&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85090679507
SN - 1904-4720
VL - 10
SP - 3547
EP - 3558
JO - Journal of Green Engineering
JF - Journal of Green Engineering
IS - 7
ER -