29865 Six Mile Road
Livonia, Michigan 48152 USA
Products and Solutions for Process Improvement
Machine Vision Components, Systems and Turnkey Inspection Solutions
Front Cover Porosity Application Profile
As an OEM supplier to Chyrsler, Diversified Machining (Howell, MI. recently purchased a part of a three plant deal from UniBoring, Inc.), is a company adept at specialized precision machining, assembly and inspection of powertrain products. To provide its customers with quality, high-performance, and competitive products, Diversified precision machines and assembles intake manifolds, cylinder heads, bedplates, covers and engine blocks as well as partial and full engine assembly for niche and production markets.
One of the high volume parts supplied to DaimlerChyrsler is the Engine Front Timing Chain Case covers for both the 3.7L and 4.7L models. These Engines are installed into DaimlerChrysler’s Jeep and Dodge vehicles at seven Assembly Plants worldwide. To ensure the integrity of this part each surface must be carefully examined for all cast and machined, deformities and sealing face porosity defects. For this to be accomplished, they contracted Phoenix Imaging (Livonia, MI; www.phoeniximaging.com) to develop a custom-built image processing system.
The company implemented Phoenix Imaging’s AVIS (automated visual inspection system) to perform multiple operations including porosity inspection, presence of clear and/or tapped holes, robot guidance and optical character recognition (OCR) for component traceability. “Moving these inspection tasks from Human vision to robust Machine Vision ensures defects won’t reach our Customers while providing traceability into the Vehicle” says John Wagnitz, Quality & Manufacturing Systems Mgr. The system inspects the front cover on a vertical pallet conveyor. By holding the front cover in a vertical orientation both sides and all features can be viewed at the same time.
“To perform an accurate inspection of the part,” says Gerald Budd, President of Phoenix Imaging, “it is necessary to create software that encompassed all of the desired inspection task. The task required porosity inspection of the “A” and “D” faces, non clean up on all machined surfaces, casting variations, presence of all through holes, presence of tapped holes and traceability of every inspected component by means of optical character recognition of indent marker serial number.
The application required multiple sensors of various pixel resolutions. When initially developed the resolution of CCD sensors were large, 1300 x 1030 x 10-bit CV-M4+ Camera Link cameras from JAI Pulnix. This is small when compared to the sensor sizes that are implemented in similar applications of today. However, this technology established the standard for on-line porosity inspection and demonstrated its use in a real world production environment.
The application implemented a number of new technologies created by Phoenix Imaging, several of which are patent pending. Every successful vision application requires a well designed illumination system. This is even more critical for surface inspection applications. Phoenix Imaging manufactures over 300 different types of illumination systems. We have designed a special illumination system that could be implemented on-line and provide uniform illumination for viewing the machined surfaces of the front cover. One of the most difficult problems to overcome using such a system is to reduce the false rejects due to surface contamination or machining operations. Phoenix Imaging has developed a unique illumination system that reduces information from surface anomalies.
The sensors are interfaced to the company’s PC-based PVS-100 machine vision system using two CL1 frame grabbers from Epix (Buffalo Grove, IL). The machined features of the component, i.e. quality of irregular shaped surfaces, holes, and threads are inspected using specific vision algorithms. The vision algorithms are created using the company’s VisionMaker™ software. The software allows each of the inspection algorithms to be developed and tested very quickly. The VisionMaker™ software acts as a pre-filter to all of the company’s ACTIVE-X vision tools. The software allows the vision developer to construct the vision algorithm as a list of low level vision functions arranged to massage the image and prepare it before being analyzed by the ACTIVE-X tool. Unlike many vision products, there is no need to compile the vision algorithm before implementation. This allows the vision developer (or trained user) to modify a vision algorithm in the production environment without special computers, development tools or libraries. According to Budd “VisionMaker™ allows us to generate and test vision algorithms in minutes rather than hours.”
Figure 1. Complete AVIS Installation
Figure 1 shows the components used in the Automated Visual Inspection System (AVIS) used by Diversified for the DaimlerChyrsler 3.7 / 4.7 L Front Cover inspection. The main electrical panel sits to the left with a large touch screen operator interface. The main inspection enclosure housing sensors and lighting system is shown at the right. The Front Covers are held in pallets and translate through the opening in the middle of the inspection enclosure. A stack of checked parts appear at the extreme right waiting robot pickup for placement is air decay leak testers.
The front covers move through the inspection system on a pallet conveyor system. The inspection system acquires images of both sides of the front cover simultaneously while being held on a transfer pallet. The software first locates the position of the component within the field of view of each sensor. It is important to compensate for both component translation and rotation because the pallet may experience ware and tear during normal use. After components are located, a number of inspection zones may be applied to specific regions. Each inspection zone can apply its unique inspection criteria. The inspection system can perform tasks that human inspectors find difficult, including the ability to accurately measure the size of imperfections, count the total number of imperfections, determine the density of imperfections per unit area, and determine the proximity of imperfections with respect to each other.
Using the M4 medium resolution cameras, it was possible to check for porosity defects of <1mm with a field of view of about 400 mm x 400 mm. The large format or high resolution cameras allow the machine vision engineer to use one camera in the place of four or more cameras simplifying both system setup and calculations. The resolution of a machine vision system can be determined by the ratio of the number of pixels in the sensor to the field of view (FOV). Cameras with a pixel resolution of 1300 x 1030 to 2000 x 1600 are considered as medium resolution formats. Cameras with a pixel resolution of 3000 x 2000 or greater are currently considered to be a high-resolution format. Budd further states that the latest generation system has demonstrated the ability to detect porosity < 400µm on a 500 mm long automotive component using an 8 mega-pixel camera. There are even larger format cameras in the development pipeline.
In order to perform the inspection of features in other regions of the casting six (6) 752 x 582 x 8-bit CV-M50 low-resolution (Pulnix-JAI) cameras are used. The low-resolution cameras were interfaced to second PVS-100M using three (3) SV5 frame grabbers from Epix. The inspection system is designed using a modular format in which one image processor acts as the “Cell Master” and additional image processors serve as “Slave” devices. The image processors communicate with each other using a high-speed Ethernet link, 100MB/s or 1 GB/s. Figure 2 below illustrates the basic system configuration for multi-processor inspection system.
Figure 2. Basic System Configuration
The main program is called the Automated Visual Inspection System (AVIS). AVIS acts as the main nerve center of the inspection system. All inspection parameters, tolerance limits, and results are displayed through AVIS. The operator interface is generated using Microsoft Visual Studio, usually programmed in VisualBasic. The VisualBasic environment is preferred because it allows us to rapidly customize screens to meet specific customer requirements.
The actual inspection process starts on a “Viewport”, this is a screen that displays the image as acquired from an individual sensor. Each sensor requires at least one Viewport on which the live or processed images are displayed. The image processing tools used to perform the actual inspection tasks are provided in an ACTIVE-X format. The specific tools required for each task may be added by simply dragging and dropping them on the Viewport. The ACTIVE-X toolset includes utilities for alignment, blob characteristics, curve fitting, etc., that permit the developer to select the functions that can be used individually or together to measure the specific features of a component. In this application the Phoenix Imaging team developed a system that could be used to classify specific defects in a number of zones, each with a specific set of requirements.
Figure 3. Screen shot highlighting the suspect area that failed inspection
Figure 3 is representative of an example log file of a component that failed one of the inspections. The file is labeled with the serial number of the component and indicate the type and location of flaws by drawing a circle around the defect location. This method was selected so that the defect was obscured by graphics and the image could be examined at a later time. Every front cover has a serial number indent marked on the neck in the machining process. The mark is positioned so that it can be identified in “Car Position” and read by the OCR software during the inspection process. Every image acquired by the inspection is archived on DVD using the serial number. The archive database includes images of “Accepted” and “Rejected” components. The database can be used to verify the condition of an individual product as tested just prior to shipment to the customer. The technology developed for this project has demonstrated unique inspection and traceability capabilities and is patent pending.
A typical system with a cost between $200k and $400k can pay for itself in less than a year. When you consider the cost of onsite sorting after a suspect products enters the production stream costs associated with such as system become immediately justifiable. Human inspection has been shown to be about 70% effective at best, an online AVSIS™ will provide consistent inspection capability and will never require a break.