Variation Prediction and Source Identification for Zero-defect Machining Line

Project time: 2016 – 2018

Budget: 8 332 000 kronor

Funding: SIP Produktion2030

In multi-stage machining, errors or variations in machined part features propagate downstream from process to process through the entire machining line. The objective of the project is to enable achieving a zero defect production by predicting and controlling variation and their propagation in multi-stage machining. This demands capturing the relations between variations and their sources in a multi stage machining. The project activities will be based on three industrial cases at Scania, LEAX AB, and GKN. The cases are meant to ground the already proven state of the art concepts in variation modelling, data analytics, measurement, precision pallet system, and simulation in real industrial applications. The application area of the project result covers manufacturability analysis, tolerance analysis, process planning as well as quality assurance strategies. The results and the demonstrations will be of interest to SME and large companies having multi stage machining.

Variations in machined part features propagate along the machining line. PRIZE aims to develop accurate representations of these to predict variations and identify sources

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