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The human eye is a remarkable structure, but it’s not even the most impressive organ of its kind in the animal kingdom. That makes it fallible. When it comes to carrying out repeatable, detailed, zero-defect product inspections for quality control, modern demands simply require a more powerful camera than the human body can provide.
Machine vision is an innovative intersection of artificial intelligence and optics technologies. With the combination of high-powered camera lenses and algorithms that become “smarter” over time, manufacturing quality is taking a big leap forward right now.
Here’s a look at some of the advantages of machine vision for manufacturing quality, along with some clues about how to implement it successfully.
What Can Machine Vision Do?
Before you begin exploring the advantages of machine vision for manufacturing quality control, it’s wise to familiarize yourself with its general capabilities. Here’s a rundown of nine applications that modern assembly and distribution plants have found for machine vision:
- Counting, sorting or measuring parts or components
- Checking for missing parts and incomplete shipments
- Performing calibrations and other product testing
- Verifying positioning of individual parts
- Recognizing and checking for proper shapes, colors and sizes of items
- Performing 3D imaging for digital twinning, compliance, documentation or other functions
- Reading and verifying printed identifiers or barcodes
- Providing data for traceability, process improvements and tracking defects to their source
- Delivering Pass/Fail product inspection and kicking out rejected parts and shipments
That last one — performing high-quality product inspections for manufacturing and shipping QA — is why the market for machine vision technology is growing so rapidly. It’s on track to reach $18.24 billion in value by 2022 at a compound annual growth rate of 7.7%.
What, specifically, are the quality assurance benefits for manufacturers? Here’s a closer look at five of the key advantages of machine vision — or “smart cameras” — for product inspections.
1. Enabling Continuous Operation
Machine vision is a type of selective automation that can make the daily operations within manufacturing plants far more efficient. Inspection stations powered by machine vision can operate continuously, including at night, and at times when productivity would otherwise have been low.
Machine vision helps relegate repetitive work, with a low tolerance for errors, to the nighttime “machine shift,” and then save more cognitively demanding work for employees during the daytime.
Deploying selective automation could also help industrial employers stagger or reconfigure their employee shifts more easily to answer the current public health crisis, as the CDC and other bodies have recommended.
2. Reskilling Opportunities for Employees
At the same time, making the shift to automated quality control using machine vision doesn’t have to come at the expense of human workers and their livelihoods.
Some of the doomsaying about lost jobs could be overblown, as plenty of small and mid-sized employers have invested successfully in automated inspections for years without shedding employees. Instead, inspection experts get reskilled into better-paying, even higher-value work for the same employer while automated systems carry out inspections instead.
Abundant research shows that workers value employers that provide avenues for personal and skillset growth. Machine vision may help create some of those opportunities.
3. No Worker Fatigue, Greater Safety and Consistency
Reducing a manufacturer’s dependence on manual inspection processes is one of the most attractive benefits of machine vision. Even the most skilled flesh-and-blood QA professionals experience burnout sometimes, and burnout may mean lapses in quality control.
Machine vision delivers a higher level of consistency without the worry of eye strain and other types of physical exhaustion from carrying out highly repetitive tasks. This win is a big one from a safety and culture standpoint, as well.
4. Facilitates Data-Gathering
Data is one of the most powerful tools at a manufacturer’s fingertips. Deploying automation at the quality assurance stage of manufacturing and distribution is an opportunity to collect new types of data.
As mentioned, smart cameras and automated inspections identify and react to a variety of conditions and attributes, such as color, size, position, condition and more. Manufacturers can use data gathered by machine vision systems to:
- Identify and trace problems with the manufacturing process to their source, including to individual pieces of equipment.
- Implement process improvements or allocate investments based on the gathered data
- Engage in real-time industrial process control to react to changes and problems as they develop
Machine vision is as much about data mobility as it is about product quality. Automating binary processes like Pass/Fail is useful. Seamlessly gathering data that’s relevant to the other processes in the facility takes it to another level. The data gathered here may inform machine calibration, maintenance intervals, staffing and training and other variables within the employer’s control.
The result is a recursive loop of constructive data and feedback and continuous process improvement, all led by an algorithm and smart camera system that becomes more useful and “observant” over time.
5. Day-One and Ongoing Cost Savings
By some estimates, an autonomous machine vision inspection system can be delivered and implemented for one-tenth of the cost of a “traditional solution.” The cost savings over the long run are probably of even more interest to the modern manufacturer.
Machine vision facilitates substantial product throughput with close-to-zero defect rates. That makes manufacturing operations more stable and scalable.
Plus, at any time — and especially at times when many essential products seemingly can’t be produced fast enough — keeping defects out of the supply chain is literally a matter of financial survival. A single product recall for a household staple can be more than enough to damage a company’s reputation beyond repair.
Automated inspection is also easier and more cost-effective to scale than traditional solutions because they don’t require a new hiring blitz, additional employee training or substantial additions to facility infrastructure. As mentioned, reskilling employees into higher-value work is another perk of machine vision. Removing the labor variable from lower-value, highly repetitive functions translates to cost savings and higher profitability as well.
General Tips for Implementing Machine Vision
Successfully implementing machine vision inspection in a manufacturing environment requires attention to a few details.
The first detail is your vendor. Machine vision systems require the right amount and configuration of lighting so the cameras and software can perform their visual inspections unimpeded. Make sure you’re working with hardware, software and lighting providers with relevant experience and documented results.
It’s also worth paying attention to emerging industry standards. There’s no such thing as “future-proof,” but newer vision systems with 10 to 25 Gigabit Ethernet cameras may soon emerge as the industrial standard for the foreseeable future. Buying the right system at the right time delivers a competitive advantage for manufacturers that understand their needs today as well as how those needs might change in the near future as their operations mature.
Recent research suggests manufacturers and others will have around 16.9 million machine vision systems in operation by 2025. Some 11% of these installed systems will be based on deep learning. Clearly, from QA peace-of-mind, more manageable costs, and a stronger company reputation to better employee safety and morale, machine vision is a welcome addition to the world of manufacturing technology.