Scrapping waste

Fuel injection pump component manufacturer Zorn Maschinenbau manufactures small-to-micro-components for fuel injection pumps used in a variety of high-performance automobile engines.

In twin-turbocharged engines the pumps deliver fuel at much higher pressure than a normally-aspirated engine.

These pumps not only affect engine performance, but pump failure could result in the engine suddenly stalling or stopping outright, forcing the driver into a potentially dangerous situation.

The variety of machining operations that are used in the manufacture of these small components lead to vastly differing surface finishes, the Germany-based manufacturer says.

These complex surfaces reflect light in a variety of ways, leading to a strong contrast between bright and dark or matte areas.

This makes it extremely difficult to reliably detect any minute surface defects using conventional 2D optical inspection methods, especially given the small size of the components.

The inspection process needs to be as fast and cost-effective as possible, but the limitations of conventional inspection techniques means that up to 10% of components that pass through this phase of inspection actually have defects.

The manufacturer has therefore had to implement additional manual inspections to remove these defective components.

This increases both production time and costs. Any new imaging system needs to be able to differentiate between the complex and varying surface types and the relevant topology.

Multi-dimensional imaging such as Stemmer Imaging’s CVS Trevista system is a powerful quality assurance technology which has been demonstrated to reliably detect surface defects even on incredibly small and complex objects.

CVS Trevista is the solution implemented at Zorn.

It delivers a detailed inspection of everything from highly reflective metals to matte ceramic objects and even curved surfaces by suppressing brightness and differences in gloss.

The CVS Trevista system makes use of a domed structured diffuse illumination source in combination with a ’shape-fromshading’ process that can differentiate the 3D shape of the object from its light reflection and surface shading.

This allows it to close the gap between traditional 2D imaging and more advanced optical 3D shape recognition by combining the speed of 2D imaging with the precision of the advanced 3D system.

The result is cost-effective, 100% inspection.

The system features a specially-developed LED dome lighting device that can illuminate an object from four different angles while simultaneously capturing a camera image.

The dome covers the object, eliminating any ambient light which could cause errors.

The resulting 3D topographical images make it possible to detect defects of just a few micrometres in depth.

Four different images are produced and processed: two slope images, a curvature image and a texture image.

The slope images depict the surface inclination in two different directions.

These images are particularly good at bringing to light defects with a defined preferential direction.

The curvature image shows the position and size of a defect as well as the surface topography of the item, regardless of direction.

The fourth image provides a purely textural view, in two dimensions, illuminating the areas that are simply surface discolourations.

These images are evaluated with algorithm-based calculations made using Sherlock machine vision software from Teledyne DALSA and the Common Vision Blox imaging toolkit from Stemmer Imaging.

All four images are overlaid into a 3D image.

The improved capabilities of advanced imaging systems like CVS Trevista are helping to redefine quality assurance processes for manufacturers.

Modern quality inspection is moving away from the traditional view of zero tolerance of any defect and more towards differentiating between critical and non-critical defects - those that affect the functionality of the object and those that do not.

Advanced 3D imaging solutions are particularly well suited for the reliable detection of anomalies that have adverse effects on functionality.

In this way, manufacturers can dramatically lower the volume of scrap components they produce from typical levels of 10% using conventional inspection techniques to below 2% with the Trevista method.