Enabling Big Data Analytics at Manufacturing Fields of Farplas Automotive

04/24/2020
by   Ozgun Akin, et al.
0

Digitization and data-driven manufacturing process is needed for today's industry. The term Industry 4.0 stands for today industrial digitization which is defined as a new level of organization and control over the entire value chain of the life cycle of products; it is geared towards increasingly individualized customer's high-quality expectations. However, due to the increase in the number of connected devices and the variety of data, it has become difficult to store and analyze data with conventional systems. The motivation of this paper is to provide an overview of the understanding of the big data pipeline, providing a real-time on-premise data acquisition, data compression, data storage and processing with Apache Kafka and Apache Spark implementation on Apache Ha-doop cluster, and identifying the challenges and issues occurring with implementation the Farplas manufacturing company, which is one of the biggest Tier 1 automotive supplier in Turkey, to study the new trends and streams related to topics via Industry 4.0.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/01/2019

Big Data Analytics for Manufacturing Internet of Things: Opportunities, Challenges and Enabling Technologies

The recent advances in information and communication technology (ICT) ha...
research
07/03/2018

Industrial Big Data Analytics: Challenges, Methodologies, and Applications

While manufacturers have been generating highly distributed data from va...
research
07/13/2023

Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0

Industry 4.0 involves the integration of digital technologies, such as I...
research
04/17/2020

Big data analytics architecture design

Objective. We propose an approach to reason about goals, obstacles, and ...
research
02/14/2020

Trends of digitalization and adoption of big data analytics among UK SMEs: Analysis and lessons drawn from a case study of 53 SMEs

Small and Medium Enterprises (SMEs) now generate digital data at an unpr...
research
07/28/2020

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

The implementation of robust, stable, and user-centered data analytics a...
research
01/29/2023

Time-Series Pattern Recognition in Smart Manufacturing Systems: A Literature Review and Ontology

Since the inception of Industry 4.0 in 2012, emerging technologies have ...

Please sign up or login with your details

Forgot password? Click here to reset