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Cluster-based data filtering for manufacturing big data systems
- Source :
- Journal of Quality Technology. 54:290-302
- Publication Year :
- 2021
- Publisher :
- Informa UK Limited, 2021.
-
Abstract
- A manufacturing system collects big and heterogeneous data for tasks such as product quality modeling and data-driven decision-making. However, as the size of data grows, timely and effective data utilization becomes challenging. We propose an unsupervised data filtering method to reduce manufacturing big data sets with multi-variate continuous variables into informative small data sets. Furthermore, to determine the appropriate proportion of data to be filtered, we propose a filtering information criterion (FIC) to balance the tradeoff between the filtered data size and the information preserved. The case study of a babycare manufacturing and a simulation study have shown the effectiveness of the proposed method.
- Subjects :
- Computer science
Strategy and Management
media_common.quotation_subject
Big data
0211 other engineering and technologies
02 engineering and technology
Management Science and Operations Research
computer.software_genre
01 natural sciences
Industrial and Manufacturing Engineering
010104 statistics & probability
Data filtering
Quality (business)
Product (category theory)
0101 mathematics
Safety, Risk, Reliability and Quality
Smart manufacturing
media_common
021103 operations research
Database
business.industry
Manufacturing systems
Data quality
business
computer
Cluster based
Subjects
Details
- ISSN :
- 25756230 and 00224065
- Volume :
- 54
- Database :
- OpenAIRE
- Journal :
- Journal of Quality Technology
- Accession number :
- edsair.doi.dedup.....c5351a011ea63cfeb063c319895b6db4