Efficient Modeling of Digital Shadows for Production Processes: A Case Study for Quality Prediction in High Pressure Die Casting Processes

IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 1–9

Abstract

The advent of Industry 4.0 has led a wide variety of engineering fields to incorporate more automation into their existing work processes. Various engineering sectors intend to imbibe aspects of Industry 4.0 technologies by leveraging Internet of Things coupled with Machine Learning and Artificial Intelligence for process optimization. This, in turn, has led to the surge of cross-domain data integration strategies which when enriched with domain specific knowledge creates dynamic models, termed as Digital Shadows. In this paper, we present the adaptation of the Digital Shadow modeling approach to die casting processes. We propose a generic pipeline for the creation of the model and test the efficacy of such an approach by transforming a predictive analytics model into a digital shadow model. For the predictive modeling, we present a novel approach of image based pixel classification which accurately predicts the occurrence as well as the location of damages on the cast object surfaces.

Authors 6

1. Arnab Chakrabarti Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Information Systems & Databases,Germany

2. Ravi Prasanna Sukumar Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Information Systems & Databases,Germany

3. Matthias Jarke Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Information Systems & Databases,Germany

4. Maximilian Rudack Aachen Giesserei Institute

   RWTH Aachen University

   Affiliation as printed

   Giesserei Institute, RWTH Aachen University,Germany

   Giesserei Institute, RWTH Aachen University, Germany

5. Paul Buske Aachen Technologie Optischer Systeme TOS

   RWTH Aachen University

   Affiliation as printed

   Technologie Optischer Systeme TOS, RWTH Aachen University,Germany

   Technologie Optischer Systeme TOS, RWTH Aachen University, Germany

6. Carlo Holly Aachen Technologie Optischer Systeme TOS

   RWTH Aachen University

   Affiliation as printed

   Technologie Optischer Systeme TOS, RWTH Aachen University,Germany

   Technologie Optischer Systeme TOS, RWTH Aachen University, Germany