Open AccessBig data analysis for product design
Author(s) -
Juliza Hidayati,
Shelvy Riry Gusrina,
Nazaruddin Matondang
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1122/1/012064
Subject(s) - big data , product (mathematics) , product design , new product development , identification (biology) , sentiment analysis , computer science , order (exchange) , marketing , business , process management , data science , manufacturing engineering , knowledge management , engineering , artificial intelligence , data mining , botany , geometry , mathematics , finance , biology
Currently all industries have the same challenges, namely the challenges facing disruptive technology, including the telecommunications industry. Disruptive Technology is a form of industrial revolution 4.0 as a result of robotic technology, machine learning and artificial intelligence. The company’s innovation capacity will be one of the best indicators for the company. So that to face disruptive technology in the industrial era 4.0, companies must design a technology with sustainable market needs in order to survive in the industrial market. Accordingly, a literature review is conducted to explore values of big data in the perspective of product designers. Product features and sentiment polarities would be the first identification of consumer opinion data. Some methods is discussed in this study such Kalman filter which used to forecast the trends of customer requirements (CR) and Bayesian method to compare products. This study aimed to help designers their advantages and understanding every possibilities of changes customer requirements (CR). And by exploring valuable information from big data the designers may decide kind of product based on customer needs and market driven product design.