Enabling Real-Time Quality Inspection in Smart Manufacturing Through Wearable Smart Devices and Deep Learning

Sie sind hier: Homepage > Suche

Enabling Real-Time Quality Inspection in Smart Manufacturing Through Wearable Smart Devices and Deep Learning

Freier Zugriff

Sarivan, Ioan-Matei / Greiner, Johannes / Díez Alvarez, Daniel / Euteneuer, Felix / Reichenbach, Matthias / Madsen, Ole / Bøgh, Simon

Abstract

In this paper, we present a novel method for utilising wearable devices with Convolutional Neural Networks (CNN) trained on acoustic and accelerometer signals in smart manufacturing environments in order to provide real-time quality inspection during manual operations. We show through our framework how recorded or streamed sound and accelerometer data gathered from a wrist-attached device can classify certain user actions as successful or unsuccessful. The classification is designed with a Deep CNN model trained on Mel-frequency Cepstral Coefficients (MFCC) from the acoustic input signals. The wearable device provides feedback on three different modalities: audio, visual and haptic; thus ensuring the worker’s awareness at all time. We validate our findings through deployments of the complete AI-enabled device in production facilities of Mercedes-Benz AG. From the conducted experiments it is concluded that the use of acoustic and accelerometer data is valuable to train a classifier with the purpose of action examination during industrial assembly operations, and provides an intuitive interface for ensuring continued and improved quality inspection.

Zugriff

Download

Exportieren, teilen und zitieren

Dokumentinformationen

Titel :

Enabling Real-Time Quality Inspection in Smart Manufacturing Through Wearable Smart Devices and Deep Learning

Beteiligte:

Sarivan, Ioan-Matei (Autor:in) / Greiner, Johannes (Autor:in) / Díez Alvarez, Daniel (Autor:in) / Euteneuer, Felix (Autor:in) / Reichenbach, Matthias (Autor:in) / Madsen, Ole (Autor:in) / Bøgh, Simon (Autor:in)

Erscheinungsdatum :

2020-11-01

Anmerkungen:

Sarivan , I-M , Greiner , J , Díez Alvarez , D , Euteneuer , F , Reichenbach , M , Madsen , O & Bøgh , S 2020 , ' Enabling Real-Time Quality Inspection in Smart Manufacturing Through Wearable Smart Devices and Deep Learning ' , Procedia Manufacturing , vol. 51 , pp. 373-380 . https://doi.org/10.1016/j.promfg.2020.10.053

DOI :

https://doi.org/10.1016/j.promfg.2020.10.053

Medientyp :

Aufsatz (Zeitschrift)

Format :

Elektronische Ressource

Sprache :

Englisch

Schlagwörter :

Deep Learning , CNN , Convolutional Neural Network , MFCC , Smart Wearable Devices , Sound Classification , Smart Manufacturing , Quality Inspection

Klassifikation :

DDC: