Evaluation Methodology for Interpretation Methods of Predictive Quality Models

Procedia CIRP, vol. 126, pp. 969–974

Abstract

Quality predictions have great potential in production. However, establishing predictive quality models requires to understand and therefore explain the predictions generated by these models based on production data. Model-independent interpretation methods claim to deliver such insights. As to date there is no approach for assessing the suitability of these methods in production context, we provide a methodology to evaluate them against general requirements as well as requirements specific for the context of process- and product-centered quality prediction. The results show that the proposed methodology is capable to effectively evaluate the interpretation methods based on selected criteria.

Authors 3

1. Tobias Schulze corresponding Aachen Laboratory forMachine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory forMachine Tools and Production Engineering (WZL), RWTH Aachen University, 52074 Aachen, German

2. Daniel Buschmann Aachen Laboratory forMachine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory forMachine Tools and Production Engineering (WZL), RWTH Aachen University, 52074 Aachen, German

3. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology Laboratory forMachine Tools and Production Engineering (WZL)

   RWTH Aachen University · Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology (IPT), 52074 Aachen, Germany

   Laboratory forMachine Tools and Production Engineering (WZL), RWTH Aachen University, 52074 Aachen, German