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Machine Vision Integration

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Industrial Machine Vision

Reshoring of our manufacturing to stabilize the supply chain and the increased requirements on production quality is driving rapid growth in automation.  Tolerances are getting tighter, cost pressures are rising, and traceability requirements are making Machine Vision increasingly common in all manufacturing industries.

Some modern manufacturing processes just wouldn't be possible without Machine Vision or Deep Learning technology.

Machine Vision solutions are most effective when they are integrated strategically, for it needs to enhance the manufacturing process and must enable the team on the plant floor to be more effective.

Smart Camera Inspection System

Where's the Field Manual?

The US Army has over 500+ field manuals in use. They contain detailed information and essential how-tos for soldiers serving in the field. The training and functional information allow them to perform in a VUCA (volatile, uncertain, complex, and ambiguous) environment.

V
Volatility
Rapid response required to deal with the unexpected or unstable

U
Uncertainty
Absence of objective trends or patterns

C
Complexity
Dynamic problems with many interdependencies

A
Ambiguity
Lack of clarity on the root cause behind what's happening


Machine Vision in manufacturing is increasing in maturity, but it still is a specialized discipline.

Poorly architected inspection systems lead to...
 unpredictable long term reliability,
  inspection data that is difficult to extract,
   lack of documentation and substandard support.

 This only makes the jobs for the team on the production floor that much more challenging.

Our Role as a Vision Systems Integrator

Vision Systems Integration

Off-the-shelf machine vision packages are great for rapid prototyping, but a fully functional vision system needs to interact with the rest of the industrial environment. And commercial deep learning packages require a lot of time collecting images, organizing the data, feeding and tuning the deep learning network. A vision systems integrator's role is to drive the solution so that it interacts seamlessly and shorten the timeline to commission but, most importantly, guarantee the system is reliable and consistent.

The era of Industrial 4.0 is creating an environment where automation needs to capture the physical world and transform it into networked digital data; not only to drive efficiency, but also to provide information transparency. In an increasingly complex automation environment, today's Machine Vision solutions must also address intelligent support for Maintenance, Quality Assurance, and Process Engineers.

How does deep learning and machine vision solutions benefit manufacturing?

Deep learning and machine vision system can be used to inspect, identify, and measure a product. With increased processing power of CPUs and GPUs, more complex quality inspection problems can be solved with 3D or deep learning solutions. Regardless, a vision system's robustness depends on the machine vision integrator who is designing the system's architecture. This includes lighting, optics, camera hardware, a control system, and most importantly, make it work within the existing production equipment.

It's true that cutting material costs can save pennies per unit and, when done over millions of units, the savings can be significant. However, another approach is for a machine vision integrator to strategically place systems inline with the process at specific intermediate steps. This way rejected products, won't have further value added to them.

Unfortunately, opening up tolerances to minimize false positives on a vision system is a typical response; doing so can increase the risk of a true reject making it out into the marketplace. One of 4th Vector Technologies' strategies for mitigating this risk, is to have ready a directory of images where an offline playback script can be used to validate tolerance changes.

Capturing trending data of inspection results for both rejected and good products is important for tracking performance. A vision systems integrator can also enhance a system by having it monitor inspection result trends against inspection tolerances. If inspection result trend lines are creeping up near tolerance thresholds, this could indicate that it is time for preventative maintenance on an upstream processes; before marginal conformances become true rejects.

Traceability is becoming increasingly important to minimize recall costs and prevent counterfeit product injection into the supply chain. Capturing trending data of inspection results for both rejected and good products is essential for tracking performance. In the event of a recall, all assembled products containing the defect can be narrowed down.

A vision systems integrator can collect and send system data to the plant's Scada or MES. Alternatively, 4th Vector Technologies has a standalone fileserver, database, and dashboard solution that is the size of a shoebox and can installed on the production floor.

Whether it is a PLC, robot, or .Net program, a vision systems integrator should design their systems with Fault Tolerance in mind. If an error or fault occurs, the program needs to exit its routine cleanly and log errors for later identifying the fault.

A lean manufacturing process is dependent on minimizing downtime. When a system goes sideways, a lack of documentation makes it harder for Maintenance to diagnose the problem. A vision systems integrator must create training and documentation that is targeted towards both the Operator and Maintenance staff.

Covid-19 has forced many industries to pivot and, during that time, 4th Vector Technologies has matured its remote support package. A small, open source firewall/VPN that is IT friendly now comes standard with our turnkey solutions. A toggle switch on the front of the control panel enables Maintenance to turn it on only when needed.





Industries Served

Industries Automotive

Automotive

Industries Consmer Products

Consumer Products

Industries Electronics

Electronics

Industries Food&Beverage

Food and Beverage

Industries Government

Government

Industrial Products

Industrial Products

Industries Life Sciences

Life Sciences

Industries Medical Devices

Medical Devices

Industries Packaging Inspection

Packaging

Industries Pharmaceutical

Pharmaceutical

How to Get Started

A discovery process is required to understand your unique requirements so that 4VT can design and build a vision solution that meets your objectives and manufacturing needs regarding performance, reliability, and adaptability.

STEP
01

Fill Out a Project Brief or Call Us

The Project Brief allows us to collect some necessary information about you and the best time to call back and some details on your objectives. Filling out the form should take less than 10 minutes.

You will receive a callback or email engagement from us either the same day or on the next business day. The Project Brief and notes from our conversation will allow 4VT to dive deeper into the discovery process.

STEP
02

Collect Samples of Good & Bad Product

To determine the best components and approach in using machine vision technology to meet your objectives, we will need to do some testing in our lab.

Ideally, you should collect 5-10 good products and several rejected products representing the defects you are looking to detect. Once collected, ship us the samples.

Some products might not be practical to ship or may require our eyes on the overall process, in which case one of 4VT's team members will come to your facility.

STEP
03

Let Us Do the Math

After we have received your samples, testing will begin in our lab. These samples will allow 4VT to determine the lighting requirements to enhance the visibility of the features you are interested in inspecting and suppress the contrast of everything that is not important.

Then 4VT will dig into the math related to the optics, camera, and acquisition system to ensure that any hardware selected will meet your objectives.

Once we are done in the lab and finish checking the optics/performance numbers in our spreadsheets, we will email screenshots or a little demo video of our preliminary results.

STEP
04

Verify the Functionality and Constraints Will Meet Your Needs

The final stage of the discovery process is to flush out the Functionality & Constraints of the system and submit them for your review. Once signed off, budgetary numbers can be generated.



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Why Is Machine Vision So Challenging?

80% of a Projects Success is in the Lighting & Optical Design



The purpose of lighting in machine vision is to:
  • enhance the contrast of features we are interested in inspecting,
  • suppress the contrast of everything that is not important, and
  • minimize external influences.
Understanding when and where to use particular lighting techniques is like a boxer learning when to apply a jab, cross/hook, or uppercut. 

There is the theory of what should work and what will work and not interfere with production. Environmental factors need to be taken into consideration when installing a vision system. These include hot or cold rooms, conveyor vibration, space restrictions from the surrounding equipment, and interface requirements. The system's design engineer needs to review their plan with Production's maintenance crew to avoid interfering with routine preventative maintenance of existing equipment.

80% of a project's success is in the lighting and optical design. Not all glare, uneven illumination, motion blur, optical distortions, overhead lighting, or dirt can be overcome with magical filters or cutting edge algorithms in the software. It is better to light it right, then write around it!

Looks Doable but the Math Says No



Back-of-the-napkin calculations using similar triangles to calculating Field of View and Work Distance works for most cases when the subject is more than 300mm away. Still, there are other details and considerations to be considered when trying to produce a quality image. We'll use this comic strip from Buddy Gator Comics as an example.

After taking some pixel measurements in an art program and assuming the camera is a Canon EOS 80D, it can be determined that the lens being used is 18mm. The distance from the Rabbit to the camera is 334mm. And the distance from the Elephant to the camera is 3503mm. Finally, when the depth of field is calculated, that comes out to 3170mm and an f/# of 116. The pupil diameter of the aperture would be 0.15mm (2x the thickness of a human hair).

With an F/# of 116, that would require more light than a bright summer day at noon, and the image would still have low contrast and appear to be blurry. The low contrast is due to the modular transfer function (MTF) of the lens. Edmund Optics has a good article explaining what MTF is.

Why does it matter? Without a high contrast image, if gauging, results would have a high variance. If pattern matching, inspection time would increase dramatically. It looks doable, but the Math Says No. There is no need to "try and buy" to see if it will work.

Machine Vision Challenges

Lack of Validation or Reference Images, Makes it Difficult to Know What Has Changed



When a Vision System Engineer collects the product's images, they deconstruct what "features" determine a good product vs. a reject product. Lighting is adjusted to enhance those features (or lack thereof). Each feature is codified into the system with a set of rules and respective thresholds.

The effort put into collecting images of product variances and changes in orientations helps produce a robust system. The challenge is, not all variances created by the process or material handling are available or can be predicted at the time of initial commissioning of a project.

As time goes by, process and production variances can cause false rejects, and tolerances are "opened up" to reduce the number of good products being rejected. Unfortunately, if inspection tolerances are opened too far, there is a potential of true non-conforming products reaching the consumer. A lack of validation or reference images makes it difficult to know what had changed between now and when the system first went live.

Red herring tests could mitigate bad products getting accepted, but consider what could be possible if a Vision System had a directory of images where the system can perform a 'Validation Check' every time a tolerance is changed.

Focused on Your Team's Success



At 4th Vector Technologies, Machine Vision, Deep Learning, and related disciplines are what we do. It is our craft. Our Founder grew up blue collar in a manufacturing town, and with integrating industrial machine vision systems since 1999, he understands the needs of the team on the production floor.  

Here is how our integrated solutions focus on your team's success:

Ensure A Quality Product

Systems are architected by someone with 20+ years of experience in industrial machine vision integration and can design a robust solution

Installing machine vision systems between high value-add processes removes rejects before it becomes a completed product, mitigating the need for your team to run extra shifts to catch up on production quotas at the end of the month

When changed tolerances can be validated against test data (that was collected and organized by our team), it reduces the chance of you getting a call back during 3rd shift



Improve Process with Data Collection, Traceability & Analytics

Give your team alerts when trends shift so that potential problems can be addressed before they occur

Auto-saving images/data by accept, warning, reject, product number, and by shift, it can save your team time in collating the data

Production floor database/file server solutions allow your team to begin collecting and tweaking data before getting IT involved



Provide Maintenance Friendly and Remote Support When Needed

Your team will know from our error logs what step or line of code caused a fault

If the Field Manual (or thumb drive system backup) ever gets lost, we'll gladly provide your team a new one

Our Remote support package is IT-friendly and shortens our response time for supporting your team

Our Services

We invest the time to understand your unique requirements. We will design and build a vision solution that meets the functionality and constraints for your specific manufacturing needs regarding performance, reliability, and adaptability.

Whether the application is Inspection, Identification, Vision-Guided Robotics, 3D Vision, or Deep Learning: We Own The Result.


Learn More


For some of our past projects, see our portfolio:


Portfolio

Machine Vision Integration Turnkey Systems

Turnkey Solutions

We can provide stand-alone turnkey Machine Vision systems with Cognex Dataman, In-Sight, VisionPro, or MvTec Halcon for a wide range of manufacturing, assembly, and packaging applications. Our in-house front-end HMI decouples the Camera Acquisition and Vision Algorithms so that we can choose the best hardware and software to solve the problem.

Details

Machine Vision System Retrofits

Retrofits

As Machine Vision and Deep Learning Integrators, we can surgically add machine vision into existing equipment and ensure consistent quality after changeover. We can also engineer to have the excess capacity to meet future needs for faster line rates. Our understanding of the math behind the optics of a machine vision system, and our experience in Illumination design, allow us to know—prior to an installation—what we can make fit and be robust in the existing available space on a machine.

Details

Machine Vision Systems Field Support

Field Support & Resource

Like any system installed in an industrial environment, it will need a little bit of love at some point. Poorly designed systems will require a tune-up much sooner than later. Our team can evaluate existing machine vision installations and make recommendations along with an execution plan to improve the overall system robustness.
We can also assist your engineering team by being part of the initial system design process and, if desired, be a resource until the Factory Acceptance Test (FAT) and beyond.

Details

Machine Vision Integration Research & Feasibility Studies

Industrial Research & Feasibility Studies

Our engineering studies can narrow down a project's risk and cost by putting together a proof-of-concept demo. We would start by bringing samples into our lab (or onsite) and piecing together a lighting mockup system to acquire a series of images. From there, we develop a vision script, and results and performance tabulated. All of this is then summarized into a report.
Engineering time and key components may qualify for up to 60% of the cost as a Research and Innovation tax credit in the US.

Details

Machine Vision Data Collection and analytics

Traceability, Data Collection & Analytics

Quality inspection and traceability are becoming essential factors in both recalls and prevention of counterfeit products introduced into the supply chain. Getting the data and tracking trends from the machine vision systems on the production floor can be a challenge, and with our software and database experience, we can bridge the gap and save time.

Details

Machine Vision Open Source Development

OEM Open Source Development

Are you developing an OEM product that will have a few hundred to a few thousand identical installations? We have worked with several different camera vendors, open-source computer vision libraries, and propriety machine vision software and can help eliminate the need for runtime licenses.

Details

Preventative Maintenance Graphic

Preventative Maintenance

A crucial part of keeping a machine vision system running effectively, is assessing all devices, equipment, and software that comprise a vision system are "five by five." Regular quarterly checkups and routine maintenance can prevent unexpected downtime.

Details





Our Platforms

MvTec Halcon PC-based Machine Vision Toolkit

MvTec Halcon
PC-based Machine Vision Toolkit

Cognex VisionPro PC-based Machine Vision Toolkit

Cognex VisionPro
PC-based Machine Vision Toolkit

Cognex MX1000 Vision Enabled Mobile Terminal

Cognex MX1000
Vision Enabled Mobile Terminal

Cognex Vidi Image Based Deep Learning

Cognex Vidi
Image Based Deep Learning

Cognex In-sight Smart Camera Vision

Cognex In-Sight
Smart Camera Vision

Cognex Dataman Vision Barcode Reading

Cognex Dataman
Vision Barcode Reading

Basler Machine Vision Camera

Basler
Machine Vision Camera

Opteon Machine Vision Camera

Opteon
Machine Vision Camera

Metaphase LED Lighting

Metaphase
LED Lighting

CCS LED Lighting

CCS
LED Lighting

Smart Vision Lights LED Lighting

Smart Vision Lights
LED Lighting



Latest Tech Briefs

Read our Tech Briefs for information on lighting, optics, algorithms and trends in industrial machine vision technology.

Machine Vision in Packaging
Packaging Hierarchy

Smartphone as an Alternative to Thin Clients for Track & Trace

Smartphone vision-enabled mobile terminals can help lower the cost of edge systems used in Track and Trace applications.
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Technology

Industrial Machine Vision and Deep Learning uses cameras, lighting, and computer processors to automatically extract information from digital images with ruggedized hardware suitable for a manufacturing environment. As product moves along a production line, the system analyzes features against defined criteria. Products are removed from a production line that has features that are outside of tolerance.


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Inspection


Deep learning and machine vision used in inspection applications can perform presence or absence verification, gauge a product's dimensions, look for surface defects or contaminants.

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Identification


Deep learning and machine vision used in identification applications can read data codes, barcodes, printed lettering, and locating unique patterns on products based on color, shape, or size. 

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Guidance


Machine vision used in guidance applications can locate a part's position and orientation in 2D or 3D space. The positional information can be sent to a robot controller so that a robot can position an end-effector to pick or place a part. Alternatively, it can set a camera into an optimal position for inspection.

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3D Vision


Multiple cameras, or a laser projection, pairing with a camera(s) can be used to generate points for a 3D image. Point clouds can generate a highly accurate surface representation of a product so that features can be found and measured. With traditional 2D machine vision technology, this might not be possible.

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Deep Learning


Deep Learning can be a powerful tool for automating industrial quality inspection because it excels at finding anomalies or non-conformances. Some defects easily found by a deep learning system would be complicated to quantify with a traditional rule-based machine vision system.

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Contact

For any kind of query, contact us with the details below.

  • (919) 746-7720
    • x102 Sales
    • x103 Accounting
    • x101 Engineering

  • 3209 Gresham Lake Rd, Ste 147, Raleigh, NC 27615

About Us

4th Vector Technologies specializes in Machine Vision Integration and Deep Learning Integration and currently serves industries in NC, SC, and VA. We integrate top-tier commercial machine vision packages, including MvTec Halcon and Cognex's full product line. We provide industrial vision solutions for inspection, identification, gauging, barcode reading, OCR, guidance, 3D vision, and image-based deep learning.

We also provide preventative maintenance and support contracts, industrial vision research and development feasibility studies, and serve as subject matter experts on SBIR projects.

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