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SENSORS FOR COMPOSITE PROCESSING

Top left, clockwise: RVmagnetics microwire sensor for composites; Com&Sens vision for use of fiber optic sensors in pressure vessels; SuCoHS project’s fiber optic sensors (yellow) embedded using AFP; disposable dielectric sensors from Synthesites with graph of cure monitoring data; and CosiMo project’s battery box cover demonstrator and ultrasonic sensor.

Why use sensors?

The composites industry has begun to prioritize sustainability, which demands not only reduction of waste but also reduced consumption of energy, water and raw materials. Manufacturing, thus, must become more efficient and intelligent. But this requires information. For composites, where does this data come from? 
 

One of the first steps toward intelligent manufacturing is to define the data required for more efficient processes and the sensors that can provide this data. Throughout 2020 and 2021, CW has reported on sensors that can be used to process composites — dielectric sensors, thermal flux sensors, fiber optic sensors and contactless sensors that use ultrasound and electromagnetic waves — as well as projects that demonstrate their installation and capabilities.

This microsite collates CW’s reporting on sensors to provide, in one place, information about the types of sensors being used in composites, the physics on which they’re based, their installation, promised benefits and challenges, as well as the potential they offer for even further developments in smart structures with sensing capabilities and fully digital production with closed-loop process control.

Goal #1 

Save money

Parts manufacturers are beginning to use sensors networks that can visualize and control the manufacturing process in-situ, based on multiple parameters (e.g., temperature and pressure) and the state of the material (e.g., viscosity, polymerization, crystallization). Cycle times can be shortened because it is now possible to see when mixing, infusion, cure and polymerization are complete. Sensors can also reduce post-processing inspection and testing to validate properties. With this new vision into the black box of processing, it is possible to understand issues during production and develop solutions to address these for improvements in productivity, scrap and energy use versus processing that is less optimized.

Goal #2

Increase process knowledge/visualization

The sensor network developed in CosiMo helped to provide full visibility into the thermoplastic RTM process and material behavior — including local effects due to variations in part thickness or materials (e.g., foam core), the shape of the resin flow front, the time for it to infiltrate the preform and the degree of polymerization at each sensor location. Collo has worked with manufacturers of epoxy adhesive, paint and even beer to create a process profile for each batch produced, enabling them to see dynamics of each process and set more optimal parameters, including alarms to enable intervention when the batch is out of spec.

Goal #3

Reduce cycle time

Collo sensors can measure the homogeneity of two-part, snap-cure epoxy as parts A and B are mixed and injected during RTM and at every location in the mold where such sensors are placed. This could help to qualify faster cure resins for applications such as urban air mobility (UAM), which would offer much faster cure cycles versus current one component epoxies like RTM6. Most sensors used in composites also enable monitoring of resin flow and cure so that these processes may be stopped when complete versus conservative time-based recipes which have extra time included.

Goal #4

Closed-loop control for adaptive processes

For the CosiMo project, the ultimate quest was to enable automated, closed-loop control during composites part production. This was also the goal for the ZAero and iComposite 4.0 projects. Even though these projects dealt with different processes — automated placement of prepreg tape, fiber spray preforming for RTM with snap-cure epoxy and high-pressure T-RTM for a PA6 composite, all of these projects used sensors with digital models and algorithms to simulate the process and predict outcomes for the finished part. Closed-loop control uses the data collected from sensors to adapt processes based on real-time changes in materials — for example, increasing or decreasing temperature and/or pressure, closing resin inlets when infusion in complete or opening a heated mold or press when target cure is reached.

 

Sensors for Composite Processing: CW Trending

In this episode of CW Trending, CW senior editor Ginger Gardiner and editor-in-chief Jeff Sloan discuss the use of sensors in composites manufacturing to optimize processes, reduce cycle time and waste, and improve part quality and sustainability. Ginger presents slides reviewing a variety of different sensor technologies and case histories in composites. She also explains how these technologies are not only enabling the digital twin and intelligent manufacturing, but also opening new possibilities for composites, such as thermoplastic-overmolded thermosets and sensing structures that can incorporate, for example, haptics allowing the captain of an 81-meter yacht to steer more efficiently by feeling and reacting to actual ocean loads on the composite rudder.

Sensors: Data for next-gen composites manufacturing

Featured in our March 2022 magazine, Senior Editor of ÂÌñÏ×ÆÞ Ginger Gardiner reported on an overview of sensors. She notes that, "In the quest for sustainability, sensors are reducing cycle times, energy use and waste, automating closed-loop process control and are increasing knowledge to open new possibilities for intelligent manufacturing and structures."

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Discover the sensors data

Sensors used in composites manufacturing provide a wide range of data and have different capabilities based on the physics each type uses for measurement.

Learn More

RVmagnetics - Technology behind the MicroWire Sensors

Synthesites: Online cure monitoring for composites manufacturing

How every liquid has a fingerprint

Collo | How every liquid has a fingerprint

RVmagnetics - Technology behind the MicroWire Sensors

Optical vs Conventional Sensing Technologies