Production rescheduling through product quality prediction

Procedia Manufacturing, vol. 54, pp. 142–147

Abstract

In production management, efficient scheduling is key towards smooth and balanced production. Scheduling can be well-supported by real-time data acquisition systems, resulting in decisions that rely on actual or predicted status of production environment and jobs in progress. Utilizing advanced monitoring systems, prediction-based rescheduling method is proposed that can react on in-process scrap predictions, performed by machine learning algorithms. Based on predictions, overall production can be rescheduled with higher efficiency, compared to rescheduling after completion of the whole machining process with realization of scrap. Series of numerical experiments are presented to demonstrate potentials in prediction-based rescheduling, with early-stage scrap detection.

Authors 4

1. Maik Frye corresponding Aachen Fraunhofer Institute for Production Technology

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology (IPT), Steinbachstraße 17, 52074 Aachen, Germany

2. Dávid Gyulai

   HUN-REN Institute for Computer Science and Control

   Affiliation as printed

   EPIC Centre of Excellence in Production Informatics and Control, Institute for Computer Science and Control (SZTAKI), 13-17 Kende, Budapest 1111, Hungary

3. Júlia Bergmann

   HUN-REN Institute for Computer Science and Control

   Affiliation as printed

   EPIC Centre of Excellence in Production Informatics and Control, Institute for Computer Science and Control (SZTAKI), 13-17 Kende, Budapest 1111, Hungary

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

   Fraunhofer Institute for Production Technology IPT · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Production Technology (IPT), Steinbachstraße 17, 52074 Aachen, Germany

   Laboratory for Machine Tools WZL RWTH Aachen University, Steinbachstraße 19. 52074 Aachen, Germany