Composites manufacturers are all too familiar with quality challenges. Inclusions and foreign object debris (FOD), incorrect ply orientation, internal voids, porosity, disbonds, delamination and more, both on the surface and interior of composite materials, may result in scrap, rework or worse – failure in the field. Efficient and accurate non-destructive evaluation (NDE) can help manufacturers save time, money and their reputation without cutting apart or altering the composite material.
“NDE should be used at various stages of the part’s life cycle – in the development phase, during manufacture of the part, in final factory inspection and when examining the part in the field to identify and assess damage or health and service life longevity,” says Lou Dorworth, direct services manager for Abaris Training Resources Inc., a provider of advanced composites training.
Dorworth notes that NDE methods for evaluating composites fall under two main categories – contact (such as traditional ultrasonic) and non-contact testing (thermographic, radiographic, infrared and shearography) – with a few unique technologies sprinkled in, such as acoustic emission testing and electromagnetic testing. “The change [in the NDE landscape] is not so much in the introduction of wholly new technology, rather in the increased capability of existing methods, the sophistication of software and interconnectivity, and the advancement of automation and robotics for conducting evaluations,” says Dorworth.
Investing in sophisticated NDE equipment and software may be expensive, but the cost/benefit equation weighs in favor of NDE. Providers of NDE solutions are stepping up with next-generation advancements.
Simulated NDE through Cloud Computing
“Simulating NDE inspections prior to conducting NDE on a manufactured part can facilitate evaluation in a reduced timeframe and reduce the number and expense of physical tests later on,” says Dorworth.
OnScale, founded in 2018, offers a finite element analysis software that conducts scalable ultrasonic simulations using cloud-based high-performance computing (HPC). The software performs ultrasonic modeling and simulations used in a variety of NDE applications to augment real-world data from NDE studies. Cloud-based computing allows for entire inspections to be simulated in parallel to reduce the time frame required for the simulations. OnScale says it is 100 times faster than traditional computer-aided engineering tools.
Using OnScale, multi-element arrays can be simulated to generate full inspections without hardware. The rapid simulations assist in eliminating the need for fabricating expensive, bespoke test pieces for pioneering new inspection techniques.
In August 2019, OnScale announced a partnership with Eclipse Scientific to network its software with BeamTool 9, an open development software for the design of phased array, time-of-flight diffraction (TOFD) and conventional ultrasonic inspection plans.
The user constructs an inspection scenario in BeamTool 9. Using the software to interface with OnScale, the user uploads the scenario problem and parameters to OnScale to perform simulations that model transducers and conduct wave propagation and defect interaction. The simulation results are then downloaded to BeamTool 9 and laid over the BeamTool build model for viewing.
Both OnScale and BeamTool 9 are available on-demand as a subscription, so no license is required to use these simulation tools.
Laser Systems for In-Process Evaluation
“When you are building a laminate, the time to work out structural defects is during lay-up,” says Dorworth. “What I’m looking for are NDE systems to inspect for process flaws in a factory. Laser systems can identify problems such as FOD or misaligned ply orientation that are critical.” This kind of NDE is often underutilized in the composites industry, he adds.
Aligned Vision is the maker of LASERVISION, a laser guidance technology combined with an aimed vision system for in-process NDE that draws comparative information directly from the part’s design data. According to Scott Blake, president of Aligned Vision, quantitative automatic in-process inspection may help composites manufacturers lessen the overdesign required to address manufacturing variation and uncertainty. Lessening overdesign may, in turn, reduce material usage, process time, part weight and cost.
First, LASERVISION’s laser projector delivers design data to the tool or work surface via laser templates rather than traditional templates. A template of light helps the worker to lay down precut material precisely by identifying edge locations and correct fiber orientation. Next, the aimed vision system (camera), which is connected to the laser projector, captures and automatically analyzes build data to optically check three parameters: the presence and location of each piece of material, the fiber orientation of the material and the absence of FOD.
“We’re guiding the assembly, we’re checking it against a digital template during the build process, and we’re directing the operator to any suspect areas,” says Blake. For example, if a fiber orientation is incorrect, the system sends the message “incorrect fiber orientation” and won’t proceed with the laser template for the next ply. “The result is less rework and scrap, enabling the manufacturer to make corrections at the earliest possible stage,” says Blake. “Customers have complete traceability through a database of data and imagery for the inspected areas.”
In a previous generation of the system, a handheld camera system was placed at the inspection location, guided by the laser. The new generation LASERVISION inspects the material placement from a mounted system. “The wing skins of Boeing’s 777X are our largest application at 100 feet long and 20 feet wide at the root,” says Blake. “We view the material as it is placed by an automatic fiber placement robot. With our software, interconnectivity enables our LASERVISION system to stop the process of a robotically built part if the variation is unacceptable.”
Blake notes that inspection time is reduced and the potential for human error is replaced with computer-driven analysis and accuracy. “We have found problems that our customers did not even know they had,” he says. “We were able to prevent some potential part failures.”
Blake believes future applications will incorporate artificial intelligence and deep learning to build and analyze images captured by LASERVISION to create “classifiers” of good and bad parts. “Using deep learning fed by the thousands of images we’re now creating, resulting algorithms will help LASERVISION reliably recognize if the image it is fed is acceptable or unacceptable,” he says. “Composite parts manufacturers will be able to use the images collected by LASERVISION to apply feature recognition and statistical processing to improve automated inspection even further.”