Data are good. Data gathered quickly are better. Good data gathered at the earliest point in a process are best of all. That's the premise behind in-process gaging. For decades, manufacturers in many industries have been pulling product samples from a production line, testing them and making decisions based upon the data. The problem with this methodology is that the testing aspect is often too far removed, both physically and environmentally, from the production aspect. The goal is to develop test equipment that's fast enough and environmentally rugged enough to go directly onto the production line. Ideally, such equipment would measure 100 percent of a process output at the source and provide real-time feedback. The gaging data are used to determine if product is acceptable, thereby enabling a corrective course of action. In some industries, the benefits of moving the inspection point from outside the manufacturing process to a point within it can produce 8-percent to 12-percent higher productivity levels and a 40-percent to 90-percent reduction in rejects, thereby lowering costs.
This article will discuss one type of in-process measurement, optical gaging, in a particularly harsh environment, aluminum extrusion manufacturing. Extruding aluminum involves heating an aluminum log (called a billet) and pushing the billet through a die in an extrusion press. In some cases 20 or 30 dies change over in one day. The aluminum is heated from 700º F to 930º F, depending on the application. During the process, the metal remains a pleasant-looking, shiny, silvery color, but it could melt your hand instantly. The extruded shape is a precision-
engineered part and is pulled to fifty feet and then stretched, cooled, age-hardened and finally cut for further fabrication.
The extrusion plant itself is a very hot, dirty and noisy environment involving the continuous operation of furnaces that soften the billets, heating dies, extrusion presses, ovens that temper aluminum pieces and finish saws that cut pieces prior to packaging for the customer. Although not a bad place to be during winter months, the extrusion plant is extremely hot during the summer. In many cases, the production environment for this industry has prevented the use of all but manual measurement techniques.
Optical measurement systems have evolved from quality lab inspection tools, utilized post-manufacture, to critical inspection tools used during manufacture. To achieve this, lens and camera technologies have adapted to overcome environmental constraints such as temperature and dirt. For instance, advances in lenses and camera resolution were needed to address the ambient temperature and air cleanliness constraints faced by small field-of-view (FOV) video/optical coordinate measurement machines, which offer accuracies of ±18 µm at 20º C. The issue is that small FOV systems have to be scanned across a sample to capture a complete view. Stage accuracies are severely hampered by dirt and temperature. Advancements leading to large FOV systems that allow a complete view of a part without stage movement eliminate that problem. As a result, the desired precision can be achieved at a much higher temperature so that deployment is possible on the manufacturing floor. Today's in-process optical systems have accuracies of ±10 µm across a wide temperature range.
With regard to dimensional inspection, the advantage of optical vs. contact-based inspection systems is largely one of flexibility and speed. When many different profiles are extruded, these factors are critical to the success of an in-process gage. Flexibility means the ease and speed to program measurement points to set up the reference file. Driven by advances in software engineering, reference file setup is now a five-minute process vs. 60-plus minutes for older technologies. In addition, the cycle time to take the measurements in process using the latest hardware is now fewer than 10 seconds; in earlier scanning systems, more than two minutes were required. Because the optical system has no moving parts, both reference file programming and actual measurement cycle time is dictated by the software in the system. This means that the complexity of parts has little to no effect on inspection cycle time.
However, disadvantages for optical inspection often include sample preparation requirements and limitation to 2-D applications. Because the optical image taken is from a 2-D perspective, the sample part must be presented in a specific way. Depending on the manufacturing process itself, some form of preparation may be required. Clearly, not all in-process applications are appropriate for optical inspection.
Optical imaging techniques utilize four primary components: camera, optical lens, light source, and the part fixture or positioning device.
The world of high-resolution cameras has grown dramatically in recent years, leading to more accurate measurements from optical systems within a much shorter cycle time. For example, in the last 18 months, 3.1-megapixel cameras have evolved to 12.1-megapixel cameras, an almost 300-percent improvement in precision. Camera cycle time (i.e., the amount of time it takes to capture an image) has been reduced from 60 seconds to one second.
For cameras of any given resolution, the smaller the area under view, the higher the measurement resolution. In the past, capturing an accurate image for measurement meant using a lens with a small FOV paired with a high-resolution camera. This worked well except when parts were larger than the viewing area of the lens. In these cases, the optical system had to take multiple pictures of the part with a moving camera, introducing more error. With the advent of higher resolution cameras, wider FOV lenses could be used. The need for multiple part images was reduced or eliminated while still maintaining an acceptable level of measurement accuracy.
Variations in light source and part fixtures are typically sample part-specific, with the major variations stemming from part size and material.
All of the above-mentioned components can be purchased off the shelf. There is nothing technologically arcane in constructing an optical system. It's the software that brings the system to life and is the discriminating factor between an adequate vs. an exceptional optical gaging system. Speed, precision and usability are the result of a successful software program that addresses a unique gaging requirement. An optical system may do a competent measurement job, but if it lacks an easy user interface, the system is likely to be relegated to the back office.
Two important areas in profile-measurement software are reference file creation and production interface. The reference file is the basis of the profile-measurement system and is generally managed by the engineering or quality staffs. A robust system will include functionality such as complete CAD file import, intelligence of specific measurement setup, automatic identification of tolerances based on ANSI or other standards, ability to define pass/fail and informational measurement points, macro functionality for symmetrical profiles, and the ability to modify reference specifications as needed, without rebuilding the entire reference file from start. A benchmark setup time for a new profile should be 10 minutes or fewer for 25 distinct measurement points.
In the production interface, one needs to keep in mind that the user is not a software specialist but an operational person whose focus is on the manufacturing process. To ensure adoption by the operations person, ease of use and speed to result is crucial. Key functionality should include simple data input (ideally only the part number currently in production), ability to present measurement results in a variety of formats for easy viewing, ability to drill down on a problem area for diagnostic purposes and network capability so other departments have real-time access to measurement results. Given the importance of in-process feedback, benchmark cycle-time responses on results should be fewer than 60 seconds. Best practices today are three to five minutes to set up a new profile reference file and three to 10 seconds for the measurement cycle to be completed for each part.
Aluminum extruded parts are instrumental in many automotive and aerospace programs. With the drive to increase the use of aluminum in advanced applications, there's a real need for tighter tolerances. To achieve this, improved gaging feedback is required during production by the entire supply chain, from die maker to extruder to customer to end user.
The application of in-process gaging to extruded aluminum shapes is one of the most demanding measurement processes in all of industry. The extrusion process is very unfriendly for high-accuracy inspection devices and proves to be a difficult challenge for automated dimensional inspection. Temperature, dirt and vibration are common in the extrusion press area. Hence, in-process gaging for dimensions has traditionally been a manual exercise using digital calipers, micrometers or custom go/no go gages. Industry experience is approximately a five- to 10-minute manual measurement cycle, with many concerns about reliability because complexities in extruded shapes create difficulties for even the simplest measurements.
The variables involved in extrusion further complicate the process, including continuous die wear, press speed and pressure, temperature variation and aluminum-stretching variation. This makes the reliable use of in-process gaging most difficult. Considering the production of parts for the aerospace and automotive industries, dimensional quality cannot be a variable.
With extruded parts, the critical issues related to in-process measurement revolve first around the measurement system location in the extrusion process and second, the sampling process and preparation. The traditional CMM-type system can be used to inspect extruded samples and capture dimensional data, but this approach is staged after the extrusion process, with no feedback to extrusion. In this case, 100 percent of the production is at risk. The bottleneck in quality assurance to approve customer orders further compounds reject-rate issues. This results in higher scrap rates and lower quality-assurance standards for the customer.
An example of an optical system designed for in-process inspection for aluminum extrusion is the Contur Projector from DII ASCONA. In the case of an extruded part, the entire cycle of preparing a sample and performing a dimensional measurement for, say, 75 measurement points, can be fewer than 60 seconds. Pass/fail feedback is provided to the extrusion team and all data are captured automatically on the network for statistical process control or customer-reporting purposes.
The nature of extruded part manufacturing, in which a piece of the extrusion must be cut off and prepared for measurement, precludes an automatic or closed-loop system. However, the dimensional results feedback enables an operator to take
corrective action, such as stopping the press. Stopping the press and pulling the die can reduce scrap by as much as 90 percent, in addition to avoiding lost press time, which could amount to hundreds of press hours per year.
Almag Aluminum in Brampton, Ontario, is a leading aluminum extruder and fabricator to the automotive industry and other advanced markets. The company's expertise in design and extrusion for engineered aluminum parts is recognized by tier one suppliers in Canada and the United States.
In 2004, Almag undertook a project to establish in-process dimensional measurement at the extrusion press.
As is current practice with many aluminum extruders, dimensional gaging at the extrusion press was done manually using hand gages. The reason for Almag's project was to determine out-of-tolerance rejects at the press and thereby eliminate downstream scrap and increase press productivity. Furthermore, a plant bottleneck existed due to quality assurance dimensional inspection in the pack/ship area. Based on internal cost studies,
the potential profit improvement was significant, as were the direct customer quality benefits.
Evaluation of an optical projector was quite extensive to ensure all quality standards were met (e.g., production part approval process, gage repeatability and reproducibility) especially because the dimensional inspection was now happening in-process. The line operators needed training to understand the feedback from the measurement process and, more important, to know what decisions to make for corrective action.
The project was very successful. Results included a reduction in scrap rates, which led to higher press productivity, and dimensional data capture was consistent across all shifts, which standardized customer quality.
Payback on the projector is expected to be achieved within 12 months. As a result of the improved performance on the one extrusion line, a second projector has been added to support another extrusion line.
Clearly, even within difficult environments such as aluminum extrusion, in-process gaging can have a dramatic effect on quality and profits. Customer feedback for Almag Aluminum has been positive, which further validates its drive to continuously improve its engineering and extrusion processes.
The case for in-process gaging is compelling because lower rejects and increased line efficiency is the natural result. However, given the constraints from environmental factors and the capability of the inspection technology, every manufacturing and inspection niche must be assessed individually. Examples used in this article relate to aluminum extrusion, where productivity increases of 10 percent coupled with scrap-reduction opportunities of about 50 percent can mean a substantial improvement to the business case for in-process dimensional measurement. Of course, the more difficult the inspection challenge, the higher the investment and the greater the opportunity for significant cost/productivity savings.
Derek Nogiec is vice president, marketing for DII ASCONA, a research and development-based optical systems company headquartered in Meckenbeuren, Germany, serving the extrusion, automotive, aerospace and advanced electronics markets. Visit DII ASCONA online at www.diiascona.com.