Sticky New Tech – Article from SME Advanced Manufacturing
Juergen Dennig, President, Coherix Inc. Aug 25, 2025
Article originally appeared on AdvancedManufacturing.org
New technology to monitor and adjust the application of adhesives used to manufacture small but essential automotive, consumer-electronics and medical-equipment components will have a major impact on cost and product quality.
However, current quality control systems often fail to catch critical assembly errors. Today the application of adhesives is checked on only one in 500 parts, on average, resulting in assembly-line shutdowns and a host of other quality-related issues.
New 3D-laser-based inspection systems equipped with machine learning, artificial intelligence and adaptive process-control software will allow manufacturers to inspect and automatically adjust dispensing processes for small parts without slowing or shutting down production lines.
The use of adhesives is growing rapidly. Sealant and adhesive use, for example, is expected to increase dramatically as automakers transition to electrification and switch to lighter-weight materials, such as aluminum and composites.
The adhesives industry is growing as well. Nearly 30,000 people are employed in the manufacturing of adhesives and sealants in North America, and the number is expected to grow substantially. The market size today is valued at more than $22 billion, according to the Adhesives and Sealants Council.
In a world of cell phones, lightweight laptops and electric vehicles (EVs) equipped with hundreds of electronic control units (ECUs), all with an ever-increasing focus on electronics, the use of adhesives has become more important, especially in the assembly of extremely small components.
Precision Vision
For the first time, recently introduced 3D-laser-based computer-vision systems allow manufacturing engineers to check the application of adhesive beads as small as two human hairs in width at speeds of up to 1,000 times per second. This makes them much faster and more effective than traditional 2D systems currently in use. When equipped with process-control software, the new computer-vision technology also can result in a near-zero defect rate by monitoring and adjusting the application of adhesives to ensure that every part meets specification.
Coherix Inc. economists estimate that the global market for adhesive-dispensing systems with advanced inspection technology for extremely small automotive, medical and consumer-electronics parts totals more than $300 million annually and is expected to grow at a rate of 7% or more over the next 5-10 years. The consumer-electronics industry alone is expected to install more than 30,000 new adhesive-dispensing systems in the next year.
The rapid expansion of EV and consumer-electronics production in China makes it the single largest potential market for the new technology, followed by Europe and North America. Europe has a large number of dispensing and robotics companies that likely will be interested in adopting the technology, and companies in the U.S. and Mexico are expected to follow suit.
The new technology can reduce assembly-line operating costs by 20% or more. In a recent beta test, a major manufacturer of ECUs for the auto industry estimated an annual savings of up to $160,000 in operating costs with the installation of eight 360-degree inspection sensors on just one assembly line.
The technology is relatively complex but easy to install and use. A 3D-computer-vision system to check adhesive application on fast-moving assembly lines for extremely small parts took just one day to install. Less than two days of on-site training were required before assembly-line and quality-control employees could use the new technology.
Benefits in 3D
What are the benefits of 3D-vision technology compared to the 2D systems commonly used today?
The major downside to 2D vision is that it is unable to measure volume, a critical measurement in the dispensing process. Many 2D systems also are “post inspection,” which means they start only after adhesives are applied. Floor space is valuable in a manufacturing environment, and 2D systems require additional space for lighting rigs, cameras, fixtures and automatic equipment.
In addition, 2D vision is unable to decipher the difference between a part and an adhesive bead when the colors of the part and the adhesive are relatively the same—gray on gray or black on black, for example—because cameras can’t pick up contrast between the two.
Robotic dispensing systems require “vision” to perform optimally. Some dispensers indicate how much adhesive is dispensed but are unable to tell where the material was applied. A robot may run a programmed path and dispense adhesive whether a part is present or not. If a part is moved or improperly fixtured, the material might also be dispensed in an incorrect location.
In a 3D system, machine vision (also known as computer vision) provides manufacturing engineers with data needed to evaluate the performance of the dispensing process. When properly used, engineers can view and record whether or not adhesive has been properly applied. 3D-vision technology also can ensure that the dispensed material meets width, height, location and volume specifications.
There are many other advantages to an in-line 3D-inspection system. When inspection is completed in-line, there is no need for additional floor space, fixturing or cycle time. With 3D vision, part and material color can be the same without affecting accurate volume measurements. It also can detect if a dispensed bead meets height and volume specifications.
One of the most important benefits of a 3D-inspection system is its ability to provide robust inspection with real-time feedback to the robot and dispenser for immediate in-line process-control adjustments.
Artificial intelligence (AI) also plays a role in newer 3D-laser-based inspection processes. Using data collected by computer vision, AI methods can be used to continually adjust the application of adhesives to meet specification on every dispensing cycle. For example, if a gap is missed on the original cycle, AI can take control of the robot to fill the gap before moving on to the next part, resulting in significant savings in labor and scrappage costs
With real-time feedback from a 3D-vision system, AI software can also make adjustments to overcome part-to-part variation. The system, for example, can detect waviness in a part that wasn’t programmed in the original robot path, then calculate and send adjustments to the robot on the fly.
In addition to major improvements in quality, material cost savings also can be achieved through in-line process control. Adhesives can be costly, running as much as $180 or more per gallon. Reducing the unnecessary use of material helps keep programs on budget.