Guideline for Deployment of Machine Learning Models for Predictive Quality in Production

Procedia CIRP, vol. 107, pp. 815–820

Abstract

Predicting product quality represents a common area of application of machine learning (ML) in manufacturing. However, manifold challenges occur during the integration of ML models into production processes. Therefore, this paper aims to provide a guideline for the deployment of ML models in production environments. Relevant decisions and steps for deploying models in predictive quality use cases are demonstrated. The results for each component of the proposed guideline - deployment design, productionizing & testing, monitoring, and retraining - have been validated with industry experts including exemplary implementations.

Authors 5

1. Henrik Heymann corresponding Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

2. Alexander D. Kies Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

3. Maik Frye Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

4. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology IPT Laboratory for Machine Tools and Production Engineering WZL

   Fraunhofer Institute for Production Technology IPT · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

   Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University, Campus-Boulevard 30, Aachen 52074, Germany

5. Andrés Boza

   Universitat Politècnica de València

   Affiliation as printed

   Centro de Investigación Gestión e Ingeniería de la Producción (CIGIP), Universitat Politècnica de València, Camino de Vera s/n, Valencia 46022, Spain