Fully Automated Quality Control of Cylinder Bores from Internal Combustion Engines and Its Implications for Industry 4.0 TUPY S.A. University of Sao Paulo

Format:

Conference/Event

Author/Creator:

Obara, Obara, author.

Contributor:

Guedes, L.C.

Conference Name:

26th SAE BRASIL Inernational Congress and Display (2017-11-07 : Sao Paulo, Brazil)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2017

Summary:

Internet has transformed all industries and the automotive sector is on its list. It is true that manufacturing has experienced great advances in recent years, but the massive use of internet in industry is about to revolutionize it once again. The Internet of Things (IoT), the Big Data Analytics and the use of RFID technology will revolutionize manufacturing, giving to the so called "smart factories" the ability for self-diagnosis, self-configuration and self-optimization. That is what we call Industry 4.0, or the fourth industrial revolution. However, how will Industry 4.0 affect automakers and end users of vehicles? What are the challenges to bring Industry 4.0 innovations to the manufacturing industry? The present work discusses future trends in engine manufacturing, focusing on the quality control of its main components. Also, a fully automated inspection technique for quality control of cylinder bores from internal combustion engines is presented. The proposed method, which is based upon topography decomposition and multiscale analysis, was used to compare two honing variants. The results show that standardized roughness parameters are not enough to properly evaluate honed surfaces. Finally, this work shows that the proposed methodology for characterization of honed surfaces can not only increase quality and reliability of engine components, but can also allow more significant advances in engine optimization. Thereby, the described method can support automakers to attend the demands of increasingly stringent markets

Notes:

Vendor supplied data

Publisher Number:

2017-36-0082

Access Restriction:

Restricted for use by site license