BOOST 4.0 VIII
PILOT : TRIMEK ZDM POWERED BY MASSIVE METROLOGY
ZERO DEFECT MANUFACTURING (ZDM) IN AUTOMOTIVE
CONTACT NAME MISS PALOMA TABOADA
PILOT PRODUCT DESCRIPTION
In this trial is aimed at improving the metrology workflow within the manufacturing process, providing an advanced inline inspection solution for quality control that will be integrated in order to analyse and manage quality information about great number of components as well as finished and complex products (3D pointclouds of up to 10 million points) like car chassis frame. Moreover, this new approach will allow to integrate and manage quality data from different production lines to be subsequently analysed and processed, detecting defects in an early and accurate way, getting statistics, and customized reports so that all the quality information will be stored and managed in the M3 Cloud. In this context, this data will be accessible for the models and apps developed so will be able to be used in collaboration with data from other sources, preventing major failures and waste of material.
OBJETIVE OF THE PILOT
The main goal is to rapid process and visualize massive quality data in order to better understand what is happening within the process. In spirit of this, the business process will consist of product scanning and rapid quality data acquisition, processing and visualization of big and complex products, instead of analysing individual components as it is done currently. Interactive and high-performance visualization and distributed processing of big 3D point clouds, like typical car chassis frame. Only one of these point clouds might consist of up to 10 million points.
The main objective will be the optimization of current 3D quality control solutions to enable point cloud generation and visualization of big and complex products and data analysis of high volume of points. Hybrid inspection systems (touch and optical sensors) will be used for the scanning process. The goal is to be capable of visualizing and analysing the final product at different levels, from the individual components to the whole piece. The high performance computationally efficient framework to be developed will be used for a generic analysis and comparison between the generated point cloud and the nominal model (e.g., STEP based CAD-model) of the product in order to detect defects, deviations and anomalous conditions/performances.
Currently, traditional visualization consists on reports with the geometric dimensioning and tolerancing (GD&T) results which provides information only about the geometries and dimensions and it is ideal for metrology uses when only few points are sampled. Furthermore, the resolution of the visualization and understanding about the product is low and some information might be missed. TRIMEK will optimize current process by integrating and developing new algorithms for graph & multi-level visualization methods for individual big 3D point clouds (advanced colour mapping) and prediction of production error based on the surface parameter evolution. Eventually, quality process will be optimized and become more productive, reducing the number of rejected parts.
In the end, a rapid quality control process will be deployed capable of processing and visualizing complex products. Hence, this business process is aimed at optimizing massive metrological data acquisition.
KPIS AND METRICS
The main KPIs of the pilot are:
- 2-5% reduction in costs
- Reduction of rejected products 5-15%
- Reduction in time of the inspection process
- Increase product and data traceability