A framework for the physics-based estimation of tool wear in machining process (WEAR-FRAME)
Purpose and goal:
WEAR-FRAME aims to develop a generic physics-based platform (software) for modelling and simulation of tool wear in machining of case-hardening and low alloyed steels. This platform benefits from semi-analytical and Finite Element based methods for the estimation of thermo-mechanical loads on the tool as well as throughput DFT-MD and CALPHAD simulations to obtain the material inputs for tool wear estimation. The goal of this simulation-based platform is to enable the optimization and adaptation of machining processes to batch-to-batch material variations.
Expected results and effects:
The WEAR-FRAME objectives target the optimization and adaptation of machining processes to material variations: 1) Availability - 10% lower lead time when introducing material in production line due to better control of material variations 2) Quality - improvement in machined and ground surface quality due to better control (15%) of tool-change & dressing intervals. 3) Performance increase (10-15%) resulting from simulation-based predictions of the tool wear; and use of optimal machining parameters (i.e. machining data); improved energy consumption and resource efficiency.
Planned approach and implementation:
WEAR-FRAME consortium includes three OEMs: Scania, Volvo AB and Seco Tools, one SME: Gnosjö Automatsvarvning, one association: Skärteknikcentrum Sverige (SKTC) and two departments at Chalmers University of Technology. The project comprise of 6 work-packages: WP1: Industrial data collection and analytics, WP2: Experimental machining tests, WP3: Material Characterisation, WP4: Modelling & simulation - software integration, WP5: Demonstration, WP6: project management & dissemination. The industrial and research partners collaborate closely to achieve the project goals.
Amir Malakizadi (contact)
Associate Professor at Chalmers, Industrial and Materials Science, Materials and manufacture
Full Professor at Chalmers, Microtechnology and Nanoscience (MC2), Electronics Material and Systems Laboratory
Gnosjö Automatsvarvning AB
Scania CV AB
Seco Tools AB
Skärteknikcentrum Sverige (SKTC)
Project ID: 2020-05179
Funding Chalmers participation during 2021–2024
Related Areas of Advance and Infrastructure
Areas of Advance
C3SE (Chalmers Centre for Computational Science and Engineering)
Chalmers Materials Analysis Laboratory