Data-Based Traceability in Gear Manufacturing

(01.07.2019)
The complete chain of gear production includes various steps as the design of macro- and micro geometry, design of manufacturing processes, gear manufacturing and quality control. The performance of a gear is the result of all steps of the process chain from the gear design to gear manufacturing and assembly. Due to space limitations, rising environmental awareness and aspired cost savings, the requirements towards gears in industrial gear production are continuously rising. Furthermore, especially in aerospace industry, failures of relevant components such as gears can endanger human life and bring tremendous image loss to the company. Since all production processes directly influence the geometry und surface characteristics of the gear, modeling and monitoring of gear manufacturing processes offers high potential to avoid scrap parts and failures in operation. Furthermore, an improved predictability of the resulting gear properties before and during manufacturing can reduce the need for cost- and time intensive tests of the gear operation behavior.

In order to predict and prevent gear failure already within the manufacturing process, the concept of data-based traceability can be applied. In this concept, a digital shadow of the workpiece is generated, which evolves with the physical component along the process chain. These aspects are one of the central topics of research on production technology and the focus of research in the recently started Cluster of Excellence “Internet of Production (IoP)” of RWTH Aachen University. The aspired digital shadow consists on the one hand of state of the art simulation models starting at the design phase, continuing during the production chain up to the resulting running behavior. On the other hand, the digital shadow contains physical process data accumulated from the machine control and measurement devices during the machining process and integrated in an intelligent database.

The combination of process data with simulative information in real time provides new approaches for the adaptive process control in terms of part functionality and for the analysis of new cause-effect dependencies that have not been covered by existing models. By this means, the digital shadow can support gear production in different aspects. As one example, the standard manufacturing process condition included in the digital shadow can be compared to a current manufacturing process condition represented by measured real-time process data. In this way, inadmissible process conditions can be detected and corrected during the process and therefore, scrap parts and image loss due to component failures can effectively be avoided. Furthermore, if scrap parts or failures do still occur, the digital shadow can contribute to a successful detection of the causes by means of the contained cause-and-effect relationships. By this means, the repeating occurrence of errors can be avoided and the stability of production can be optimized.

Figure 1: Digital shadow in gear production

The digital shadow for gear production is part of current research at Gear Technology Department of the Laboratory for Machine Tools (WZL) of RWTH Aachen University. Basis for an exact model of the whole gear production process within the digital shadow is the knowledge of the exact influence of each production step on the exact gear properties. As part of the digital shadow, the modeling of the resulting gear properties including deviations is currently implemented in the gear manufacturing simulation. The simulation of manufacturing deviations enables a virtual measurement and can be used as input data for a realistic virtual gear contact analysis.

In recent work at WZL a simulation method was developed to model the exact process kinematics for continuous generating and discontinuous profile grinding based on the system of machine tool axes. With this method, any axis movements of the grinding machine can be defined and modeled. Subsequently, deviations of the ground gear resulting from the axis movements can be determined out of the kinematics. In this way, the effect of axis deviations or process-related characteristic axis movements on the gear quality can be predicted near real-time. The modeling of the process kinematics was then validated by transferring the machine axis positions recorded during a profile grinding process to the simulation. A good agreement of the predicted component deviations with the actually measured component deviations could be determined. Therefore, the developed simulation method offers an improved understanding of the influence of process deviations on the gear quality. In addition, the method enables a virtual measurement of ground gears and, therefore, a reduction of real measuring time.

Figure 2: Validation of the kinematics simulation for grinding processes

In summary, the use of a digital shadow in gear production can heavily support process design, near real-time assessment of workpieces and the avoidance of scrap. Current investigations at the Laboratory for Machine Tools (WZL) of RWTH Aachen University, which deal with the modeling and digitization of manufacturing processes and the operation behavior of gears, form the basis for the development of a digital shadow in gear production. Latest research results allow for the assessment of the resulting gear quality based on NC data traces of the grinding processes in near real-time.


Authors

  1. Mareike Solf M.Sc., Team Leader Gear Hard Machining, Laboratory for Machine Tools WZL of RWTH Aachen University
  2. Christopher Janßen M.Sc., Research Assistant Gear Technology, Laboratory for Machine Tools WZL of RWTH Aachen University
  3. Jens Brimmers M.Sc. M.Sc., Chief Engineer Gear Technology, Laboratory for Machine Tools WZL of RWTH Aachen University
  4. Dr.-Ing. Dipl.-Wirt.-Ing. Christoph Löpenhaus, Chief Engineer Gear Technology, Laboratory for Machine Tools WZL of RWTH Aachen University
  5. Professor Dr.-Ing. Thomas Bergs, Head of Chair of Manufacturing Technology, Laboratory for Machine Tools WZL of RWTH Aachen University
  6. Professor Dr.-Ing. Christian Brecher, Head of Chair of Machine Tools, Laboratory for Machine Tools WZL of RWTH Aachen University