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Automated inspection of defects onmetal surfaces
University West, Department of Engineering Science, Division of Industrial Engineering and Management, Electrical- and Mechanical Engineering.
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The aerospace industry is today manufacturing a large variety of parts. Some which are classifiedas critical, these parts are today manually inspected and validated according to proceduresand standards. The Aero space industry is interested in a product that can aid in the process of inspection and validation to reduce the manual work.

The identification of the needs is done by a study visit at GKN Aerospace Sweden, in Trollhättan, and through questions and discussions with the staff from GKN. The main need is identified as an automated visual inspection of defects on metal surfaces. The automated inspection is divided into sub-functions, which in turn allows identification of potential robot tool modules.

Modular design is a method which enables variations and updates of a product's features without being locked into a singular solution. Modular design also allows sustainability due to the ease of upgrading and recycling a product.

The robot tool modules are developed into several concepts. The concepts are 3D modelled in CAD software and in parallel with the concept development, a simulation of an inspection procedure, including the 3D models, is developed in ABBs simulation environment RobotStudio. The development of the solution for the automated inspection is an iterative process. When the simulated solution is satisfying functionality and customer needs, construction drawings are created for the modules of the robot tool.

The simulation and the manufactured tools are implemented in a real robot cell and as a result, the objective the project is met, an automated inspection of defects on metal surfaces.

Place, publisher, year, edition, pages
2019. , p. 23
Keywords [en]
Machine vision, quality control, visual inspection, automation, repeatability, robotics, sustainability
National Category
Robotics
Identifiers
URN: urn:nbn:se:hv:diva-14353Local ID: EXC915OAI: oai:DiVA.org:hv-14353DiVA, id: diva2:1347209
Subject / course
Robotics
Educational program
Robotteknik
Supervisors
Examiners
Available from: 2019-09-05 Created: 2019-08-30 Last updated: 2019-09-05Bibliographically approved

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