Inspection, Detection and Documentation – The Trifecta of Work in Process

As the rolling hills of the Bluegrass state turn from frost covered gold of winter to sun splashed green of spring, most Kentuckians are gearing up for “the most exciting two minutes in sports”, otherwise known as The Kentucky Derby. While some fans are interested in the glitz and glamour of the event, the real supporters of the sport, the bettors, are seeking out a big payday. A specific type of wager called a Trifecta, a bet that requires picking the first three finishers in the correct order, traditionally yields thousands, if not tens of thousands, of dollars in reward. This is no easy feat.  It is difficult to pick one horse, let alone three to finish at the top. So while the bettors are seeking out their big payday with a trifecta, the stakeholders in manufacturing organizations around the globe are utilizing the trifecta to ensure their customers are getting quality products. However, the trifecta of work in process is valued in millions of dollars.

WorkinProcess_Header

Work in process, or “WIP”, is an application within manufacturing where the product is tracked from the beginning of the process to the end. The overall goal of tracking the product from start to finish is, among other things, quality assurance. In turn, ensuring the product is of good quality creates loyal customers, prevents product recalls, and satisfies regulations. In a highly competitive manufacturing environment, not being able to ensure quality can be a death sentence for any organization. This is where the trifecta comes back into play. The three processes listed below, when used effectively together, ensure overall product quality and eliminate costly mistakes in manufacturing.

  1. Inspection – Typically executed withWorkinProcess Trifecta a vision system. Just like it sounds, the product is inspected for any irregularities or deviation from “perfect”.
  2. Detection – This is a result of the inspection. If an error is detected action must then be taken to correct it before it is sent to the next station or in some cases the product goes directly to scrap to prevent the investment of any additional resources.
  3. Documentation – Typically executed with RFID technology. The results of the inspection and detection process are written to the RFID tag. Accessing that data at a later time may be necessary to isolate specific component recalls or to prove regulatory compliance.

Whether playing the ponies or manufacturing the next best widget, the trifecta is a necessity in both industries. Utilizing a time tested system of vision and RFID technology has proven effective for quality assurance in manufacturing, but a reliable system for winning the trifecta in the derby is still a work in process.

To learn more about work in process, visit www.balluff.com.

To OCV, or OCR, that is the question

VisionOWLTo OCV, or OCR: that is the question:
Whether ’tis nobler to use OCV (Optical Character Verification) to verify print,
Or OCR (Optical Character Recognition) to decode a sea of print troubles.
And by decoding will turmoil end?
No more to have the camera sleep; we program the TTL (Time to Live)
That font won’t print correctly, ’tis a communication issue?
The undiscover’d font no longer puzzles the will as I can check with OCV.

OCR in Machine Vision software has a library of numbers, letters, fonts, and special characters. Sometimes print is not readable when quality checked using the ISO 1831:1980 specification library. Fortunately, we can teach printed characters utilizing OCV. To verify the quality of print, it can be graded following the ISO 15415,15416 AIM DPM-1-2006/ISO29158 standard. This standard also checks print quality when 1D or 2D barcodes are read.

Hence, methinks even Shakespeare would be impressed by modern-day OCV and OCR technology.

To learn more about machine vision visit www.balluff.us/vision.

Special thanks to Diane Weymier-Dodd for her contribution to this post. 

QR Codes for Business vs Industry

QRCode
Example of a QR code for business use

In a previous post I discussed the different types of bar codes. Aside from the 1D bar codes that we see in the grocery store, the most common type of bar code today is the QR code.

The QR code was 1st designed for the automotive industry to track vehicles in the assembly process. The QR code system became popular outside the automotive industry due to its greater storage capacity compared to standard UPC bar codes. A QR code can have up to 7,089 ASCII characters and can read numeric, alphanumeric, byte/binary, and kanji. Businesses often use this type of QR code on vehicles and products for advertising. When a picture is taken with a cell phone, typically in a QR code reader app, the user will be taken to a website for more information.

Sharpshooter vision sensor for reading micro & QR codes
Sharpshooter vision sensor for reading micro & QR codes

Micro QR codes, on the other hand, have a limitation of 35 digits of numeric characters. These are usually seen in industrial applications. For example, they are seen on cam shafts, crankshafts, pistons, and circuit boards. An example of data that is often written to a micro QR code would be a serial number to track and trace through an assembly plant. An industrial vision sensor is typically needed to decipher micro QR codes.

ILoveBalluffQRCodes
An example of a QR code (left) vs a micro QR code (right)

For more information visit www.balluff.us.

Isn’t a bar code just a bar code?

Bar codes are normally read via a red line laser scanner, or a camera with decoding and positioning software.

There are 3 main types of bar codes.

1D (one dimensional), 2D (two dimensional) and a different type of 2D code is QR (Quick response) codes that we use today.

Each code has a little different attribute and how it’s read.

 1D bar codes are the ladder line bar codes you typically see in a grocery store, on merchandise and packaging.

While there are many different types of 1D bar codes and how they decipher a code the appearance is typically like the picture below.

1Dbarcode

 

 

 

 

 

A 2D Data Matrix code is much smaller than a 1D and can hold quite a bit more information. They can actually hold up to 2,335 alphanumeric characters.

There is redundancy built into the code, in case the code is scratched or defaced.

The code below is an example of a 2D Data Matrix code.

2Dbarcode

The code is read by utilizing a camera and decoding / positioning software.

A QR Code can hold more information than a Data Matrix code.

It can decipher numeric, alphanumeric, byte/binary and kanji.

While it was 1st developed for the automotive industry tracking parts during vehicle manufacturing, it is typically linked to a website when the code is scanned with a camera in a cell phone.

An example of the QR Code is pictured below.

QR Code

The code is read by utilizing a camera and decoding / positioning software.

There are various types of vision sensors that can be used to read different types of bar codes. You can learn more on Balluff’s website at www.balluff.us/vision.

What’s best for integrating Poka-yoke or Mistake Proofing sensors?

Teams considering poka-yoke or mistake proofing applications typically contact us with a problem in hand.  “Can you help us detect this problem?”

We spend a lot of time:

  • talking about the product and the mistakes being made
  • identifying the error and how to contain it
  • and attempting to select the best sensing technology to solve the application.

However this can sometimes be the easy part of the project.  Many times a great sensor solution is identified but the proper controls inputs are not available or the control architecture doesn’t support analog inputs or network connections.  The amount of time and dollar investments to integrate the sensor solution dramatically increases and sometimes the best poka-yoke solutions go un-implemented!”

“Sometimes the best poka-yoke solutions go un-implemented!”

Many of our customers are finding that the best controls architecture for their continuous improvement processes involves the use of IO-Link integrated with their existing architectures.  It can be very quickly integrated into the existing controls and has a wide variety of technologies available.  Both of these factors make it the best for integrating Poka-yoke or Mistake Proofing due to the great flexibility and easy integration.

Download this whitepaper and read about how a continuous improvement technician installed and integrated an error-proofing sensor in 20 minutes!

When to use a Vision Sensor for Error-Proofing Applications

Vision sensors are powerful Poka-Yoke tools ideal for error proofing your process. However, traditional sensors still solve more applications at a much lower cost. So, how do you decide when to jump up to a vision sensor? There are three application categories that require the use of a vision sensor, which include:

  

  1. Parts are not well fixtured: If the part is not contained in a fixture, or there is no opportunity to bring the part into an inspection station that has better tolerance, then a vision system is the best choice.
    Example: parts directly on moving conveyor belt.

    Parts on free conveyor
    Parts on free conveyor

    Continue reading “When to use a Vision Sensor for Error-Proofing Applications”

To Avoid Trouble Later, Consider Your Application Conditions Up Front

Hardly a day passes by where we are not contacted by a desperate end-user or equipment manufacturer seeking assistance with a situation of sensors failing at an unacceptably high rate.  Once we get down to the root cause of the failures, in almost every case it’s a situation where the specific sensors are being applied in a manner which all but guarantees premature failure.

Not all sensors are created equal.  Some are intentionally designed for light-duty applications where the emphasis is more on economical cost rather than the ability to survive in rough service conditions.  Other sensors are specifically designed to meet particular challenges of the application environment and as a result may carry a higher initial price.

Some things to think about when choosing a sensor for a new application:

Continue reading “To Avoid Trouble Later, Consider Your Application Conditions Up Front”

”Well Jack Me Up!” – Error Proofing a Car Jack Kit

Picture this scenario.   You, your spouse, or one of your kids happens to be riding one night in the middle of nowhere when a tire blows on the car.  First, we can only hope that your loved one remembered the lesson they received on how to change a flat tire in a pinch (if we gave it to them in the first place), because on this particular night, there’s no cell coverage where they’re at, AAA isn’t going to get to them very quickly, there isn’t a can of Flat Fix in the trunk, and there isn’t much traffic on the road they’re traveling on for a good Samaritan to likely show up any time soon (the scenario is extreme, but not impossible).  The jack kit sitting under the spare tire is going to seem pretty doggoned important, don’t you think?

We take a lot for granted these days and for those of us who have been involved in the world of factory automation for many years, getting to work with customers to help solve Error-Proofing challenges on the plant floor is like one big “Class Trip” every single day!   It’s kind of like providing our customers with “toys for adults”.  And it’s a real hoot.  We get to see how stuff is made, get the opportunity to help manufacturers build better products through our Error-Proofing sensing technologies and learn over time which end products to buy and which ones to shy away from!  We also quickly realize the extreme importance of the DETAIL!  Like the components in the emergency jack kit!  What if the main handle was missing when you or your relative went to jack up the car?  What if there wasn’t any grease on the main lift shaft threads and the car couldn’t be raised?  What if other parts were missing from the kit? Not a good scenario.

Continue reading “”Well Jack Me Up!” – Error Proofing a Car Jack Kit”

Finding Good Machine Vision Resources Isn’t So Hard Anymore

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Finding information that is not biased or a shrouded sales pitch for a companies products can sometimes be a difficult proposition in today’s open communication society. The world of machine vision is no exception. So when seeking un-biased information, sometimes it can seem like the deck is stacked against you.

Continue reading “Finding Good Machine Vision Resources Isn’t So Hard Anymore”