RFID Replaces Bar Codes Efficient Asset Tracking

Bar code technology has been around for many years and is a tried and true means for tracking asset and product movement, but it has its limitations. For example, a bar code reader must have an unobstructed view of the bar code to effectively scan. And the bar code label cannot be damaged, or it is then unreadable by the scanner.

In more recent years, additional RFID technologies have been more readily available for use to accomplish the same task but with fewer limitations. Using RFD, a scanner may be able to read tags that are blocked by other things and not visible to the naked eye. UHF RFID can scan multiple tags at the same time in a single scan, whereas most bar codes need to be scanned individually. This, therefore, increases efficiency and reduces the time required to perform the scans.

Then, of course, there is the human factor. RFID can help eliminate mistakes caused by human error. Most bar code scanning is done with hand scanners held by workers since the scanner has to be in the exact position to see the bar code to get a good scan. While manual/hand-held scanning can be done using RFID, most times a fixed scanner can be used as long as the position of the RFID tag can be guaranteed within certain tolerances. These tolerances are much greater than with a bar code scanner.

With the advent of inexpensive consumable RFID labels, the ease and cost of transitioning to RFID technology has become more feasible for manufacturers and end users. These labels can be purchased for pennies each in rolls of several thousand at a time.

It should be noted that several companies now produce printers that can actually code the information on a RFID label tag while also printing data, including bar codes, on these label tags so you have the best of both worlds. Tags can be scanned automatically and data that can be read by the human eye as well as a bar code scanner.

Some companies have expressed concern about the usage of RFID in different countries due to local regulations regarding the frequencies of radio waves causing interferences.

This is not an issue for HF  and UHF technology. HF is an ISO standard (ISO 15693) technology so it applies to most everywhere. For UHF, which is more likely to be used due to the ability to scan at a distance and scan multiple tags at the same time, the only caveat is that different areas of the world allow scanners to only operate in certain frequencies. This is overcome by the fact that almost all UHF tags that I have encountered are what are called global tags.

This means these tags can be used in any of the global frequency ranges of UHF signals. For example, in the North America, the FCC restricts the frequency range for UHF RFID scanners to 902-928 MHz, whereas MIC in Japan restricts them to 952-954 MHz, ETSI EN 300-220 in Europe restricts them to 865-868 MHz, and DOT in India restricts them to 865-867 MHz. These global tags can be used in any of these ranges as they work from 860 to 960 MHz.

On the subject of UHF, it should be mentioned that in addition to the frequency ranges restricted by various part of the world, maximum antenna power is also locally restricted.

For more information on RFID for asset tracking, visit https://www.balluff.com/local/us/products/product-overview/rfid/


Turning Big Data into Actionable Data

While RFID technology has been available for almost seventy years, the last decade has seen widespread acceptance, specifically in automated manufacturing. Deployed for common applications like automatic data transfer in machining operations, quality control in production, logistics traceability and inventory control, RFID has played a major role in the evolution of data collection and handling. With this evolution has come massive amounts of data that can ultimately hold the key to process improvement, quality assurance and regulatory compliance. However, the challenge many organizations face today is how to turn all that data into actionable data.

Prominent industry buzzwords like Industry 4.0 and the Industrial Internet of Things (IIOT) once seemed like distant concepts conjured up by a marketing team far away from the actual plant floor, but those buzzwords are the result of manufacturing organizations around the globe identifying the need for better visibility into their operations. Automation hardware and the infrastructure that supports it has advanced rapidly due to this request, but software that turns raw data into actionable data is still very much in demand. This software needs to provide interactive feedback in the form of reporting, dashboards, and real time indicators.

The response to the demand will bring vendors from other industries and start-ups, while a handful of familiar players in automation will step up to the challenge. Competition keeps us all on our toes, but the key to filling the software gap in the plant is partnering with a vendor who understands the needs on the plant floor. So, how do you separate the pretenders from the contenders? I compiled a check list to help.

Does the prospective vendor have:

  • A firm understanding that down time and scrap need to be reduced or eliminated?
  • A core competency in automation for the plant floor?
  • Smart hardware devices like RFID and condition monitoring sensors?
  • A system solution that can collect, analyze, and transport data from the device to the cloud?
  • A user-friendly interface that allows interaction with mobile devices like tablets and phones?
  • The capability to provide customized reports to meet the needs of your organization?
  • A great industry reputation for quality and dependability?
  • A chain of support for pre-sales, installation, and post-sales support?
  • Examples of successful system deployments?
  • The willingness to develop or modify current devices to address your specific needs?

If you can check the box for all of these, it is a safe bet you are in good hands. Otherwise, you’re rolling the dice.

Document Product Quality and Eliminate Disputes with Machine Vision

“I caught a record-breaking walleye last weekend,” an excited Joe announced to his colleagues after returning from his annual fishing excursion to Canada.

“Record-breaking?  Really?  Prove it.” demanded his doubtful co-worker.

Well, I left my cell phone in the cabin so it wouldn’t get wet on the boat so I couldn’t take a picture, but I swear that big guy was the main course for dinner.”

“Okay, sure it was Joe.”

We have all been there — spotted a mountain lion, witnessed an amazing random human interaction, or maybe caught a glimpse at a shooting star.  These are great stories, but they are so much more believable and memorable with a picture or video to back them up.  Now a days, we all carry a camera within arm’s reach.  Capturing life events has never been easier and more common, so why not use cameras to document and record important events and stages within your manufacturing process?

As the smart phone becomes more advanced and common, so does the technology and hardware for industrial cameras (i.e. machine vision).  Machine vision can do so much more than pass fail and measurement type applications.  Taking, storing, and relaying pictures along different stages of a production process could not only set you apart from the competition but also save you costly quality disputes after it leaves your facility.  A picture can tell a thousand words, so what do you want to tell the world?  Here are just a couple examples how you can back up you brand with machine vision:

Package integrity: We have all seen the reduced rack at a grocery store where a can is dented or missing a label.  If this was caused by a large-scale label application defect, someone is losing business.  So, before everyone starts pointing fingers, the manufacturer could simply provide a saved image from their end-of line-vision system to prove the cans were labeled when shipped from their facility.

Assembly defects: When you are producing assembled parts for a larger manufacturer, the standards they set are what you live and die by.  If there is ever a dispute, having several saved images from either individual parts or an audit of them throughout the day could prove your final product met their specifications and could save your contract.

Barcode legibility and placement: Show your retail partners that your product’s bar code will not frustrate the cashier by having to overcome a poorly printed or placed barcode.  Share images with them to show an industrial camera easily reading the code along the packaging line ensuring a hassle-free checkout as well as a barcode grade to ensure their barcode requirements are being met.

In closing, pictures always help tell a story and make it more credible.  Ideally your customers will take your word for it, but when you catch the record-breaking walleye, you want to prove it.

Which RFID Technology is Best for Your Traceability Application?

There are a lot of articles on using RFID for traceability, but it’s hard to know where to begin. Examples of traceability include locating an important asset like a specific mold that is required to run a machine or verifying a specific bin of material required to run production. Spending time looking for these important assets leads to lost time and production delays. RFID can help but understanding the different RFID capabilities will narrow down the type of RFID that is required.

Not all RFID technology is the same. Each RFID technology operates differently and is categorized by the frequency band of the radio spectrum, such as low frequency, high frequency and ultra-high frequency. In low and high frequency RFID, the read range between RFID tag and reader antenna is measured in millimeters and inches. The read range on ultra-high frequency (UHF) RFID technology can range from one meter to 100 meters. Typically, inventory traceability is done using ultra-high frequency band of the radio frequency spectrum, due to the need to read the asset at a further distance so it does not interfere with the production flow. Also, there are cases where there needs to be a reading of multiple tags in an area at the same time to determine where an asset is located. UHF RFID technology allows for simultaneous reading of multiple RFID tags from a single antenna reader.

There are two types of UHF RFID, passive and active.  Passive UHF RFID means that the RFID tags themselves have no additional power source. The UHF reader antenna sends out an electromagnetic wave field, and the RFID tags within the electromagnetic field have an internal antenna that receives the energy which activates the integrated circuit inside the tag to reflect the signals back to start communicating. The read distance between the passive RFID tag and antenna reader is determined by several factors, such as the size of the electromagnetic wave field generated out of the reader antenna and the size of the receiver antenna on the RFID tag. Typical read ranges on passive UHF systems can be anywhere from one to 12 meters, where the larger the power and RFID tag, the longer the range.

Active UHF RFID systems do not require the tag to reflect signals back to communicate because the active RFID tag has its own transmitter and internal battery source. Because of this, with active UFH RFID you can get read ranges of up to 100 meters. There are active tags which wake up and communicate when they receive a radio signal from a reader antenna, while others are beacons which emit a signal at a pre-set interval. Beacon active tags can locate in real time the location of the asset that the RFID tag is attached to. However, a downfall to active RFID tags is the battery life on the tag. If the battery is dead, then the asset will no longer be visible.

Figure 1

Once the strengths and weaknesses of each type of UHF RFID system is known, it’s easier to work with the constraints of the system. For example, the application in Figure 1 shows a reader antenna for reading bins of material placed a few feet away so that its’ not in the way of production. A passive UHF RFID system will work in this case, due to the distance between the antenna and the RFID tag on the bin a few feet away. There is no need to worry about battery life on the passive RFID tag.

Figure 2

If the exact location of a production mold is required in a large facility, then using an active UHF RFID system is likely a better fit. Incorporating an active RFID tag that sends out a beacon at a fixed interval to a data center ensures the location of all assets are always known. With this setup, the exact location of the mold can be found at any time in the facility.

Examining the different types of RFID technology can help determine the correct one to use in a traceability application. This includes analyzing the pros and cons of each technology and seeing which one is the best fit for the application.

Injection Molding: Ignore the Mold, Pay the Price

Are you using a contract molding company to make your parts? Or are you doing it in house, but with little true oversight and management reporting on your molds? As a manufacturer, you can spend as much on a mold as you might for an economy, luxury or even a high-performance car. The disappointing difference is that YOU get to drive the car, while your molder or mold shop gets to drive your mold. How do you know if your mold is being taken care of as a true tooling investment and not being used as though it were disposable, or like the car analogy, like the Dukes of Hazzard used the General Lee?

What steps can you take in regard to using and maintaining a mold in production that can help guarantee your company’s ROI? How can you ensure your mold is going to produce the needed parts and provide or exceed the longevity required?

It is important for any manufacturer to understand the need for the cleaning and repair required for proper tool maintenance. The condition of your injection mold affects the quality of the plastic components produced. To keep a mold in the best working order, maintenance is critical not only when issues arise, but also routinely over time.

In the case of injection molds specifically, there are certain checks and procedures that should be performed regularly. An example being that mold cavities and gating should be routinely inspected for wear or damage. This is as important as keeping the injection system inspected and lubricated, and ensuring all surfaces are cleaned and sprayed with a rust preventative.

Figure 1 An example of the mold usage process.

The unfortunate reality is that some molders wait until part quality problems arise or the tool becomes damaged to do maintenance. One of the biggest challenges with injection molders is being certain that your molds are being run according to the maintenance requirements. Running a mold too long and waiting until problems arise to perform routine maintenance or refurbish a mold can result in added expense, supply/stock issues, longer time to market and even loss of the mold. However, when molders have a clear indication of maintenance and production timing, and follow the maintenance procedures in place, production times and overall costs can decrease.

Figure 2 Balluff add-on Mold ID monitoring and traceability system.

Creating visibility and accuracy into this maintenance timing is something today’s automation technology can now address. With todays modern, industrial automation technology, visibility and traceability can be added to any mold machine, regardless of machine age, manufacturer and manufacturing environment.

With the modern networked IIoT (industrial internet of things)-based monitoring and traceability system solutions available today, the mold can be monitored on the machine in real-time and every shot is recorded and kept on the mold itself using, for example, an assortment of industrial RFID tag options mounted directly on the mold. Mold shot count information can be tracked and kept on the mold and can be reported to operations or management using IIoT-based software running at the molder or even remotely using the internet at your own facility, giving complete visibility and insight into the mold’s status.

Figure 3 Balluff IIoT-based Connected Mold ID reporting and monitoring software screens.

Traceability systems record not only the shot count but can provide warning and alarm shot count statuses locally using visual indicators, such as a stack light, as the mold nears its maintenance time. Even the mold’s identification information and dynamic maintenance date (adjusted continuously based on current shot count) are recorded on the RFID tag for absolute tracability and can be reported in near real-time to the IIoT-based software package.

Advanced automation technology can bring new and needed insights into your mold shop or your molder’s treatment of your molds. It adds a whole new level of reliability and visibility into the molding process. And you can use this technology to improve production up-time and maximize your mold investments.

For more information, visit https://www.balluff.com/en/de/industries-and-solutions/solutions-and-technologies/mold-id/connected-mold-id/

Tag, You’re It: Choosing the Right Type of Tags for Your RFID System

Many companies have already discovered the benefits of implementing RFID into their systems. Traceability within the manufacturing process provides a competitive advantage of both efficiency and profitability. RFID tags are a major component of this technology. But it’s important to select the correct type for your specific application. These tags are classified into categories based on how they obtain power and how they use that power. The three categories are as follows:

  • Passive tags
  • Semi-passive tags
  • Active tags

Understanding the difference between these can help narrow down your decision when looking into implementing RFID systems to your process.

Passive tags do not have their own power source. The tag receives power only when the RFID reader is in range. These tags are limited since the power supplied is minimal. The biggest advantages of passive tags are that they are small and inexpensive. They can be useful in specific applications where space is limited. Also, if the environment in which the tag is being placed is harsh, the passive tag may be a good option because it can be cheaply replaced if damaged. Since these tags do not generate power, their read distance of just a few inches to about two feet is much shorter than others. Passive tags are also limited to the amount of data storage they possess. Depending on the application this can be an advantage or disadvantage.

Semi-Passive tags, as the name implies, are similar to passive tags in that they do not have an active transmitter. They still require an RFID interrogator to be in range for the device to work, although the semi-passive tags have their own battery to power the IC. If you are looking for longer read ranges than the passive tag, this could be an option. Since the read range of the passive sensor is solely based on how far away the interrogator can power the device and not the signals coming in, adding a battery unit to the semi-passive tags increases this distance. These distances can range up to 100 feet. Another advantage is the amount of data they can store. These added features do come with added costs. The onboard power supply also makes these tags larger and heavier. The electronics inside the tag are susceptible to harsh environments like high or low temperatures, resulting in shorter lifespans.

Active tags have both a battery and transmitter built within their housings. The typical read range is again increased to around 300 to 750 feet depending on the battery power and the antenna. This allows the tags to store more data with their increased memory capacity. Active tags display the most configurability in comparison to passive and semi-passive tags. They can be set up to conserve battery power when the interrogator is out of range and respond only when the reader is within range. They can also be set up as a beacon, which is when the tag does not wait until it receives a signal from the interrogator. Instead, the active tag can be configured to send the information in set time intervals. Since active tags contain an active transmitter, they can contribute to radio noise. They are also more expensive and usually larger in size and weight due to the increased electronics within its housing.

It’s important when selecting a tag for your RFID system to consider the application needs and the advantages and disadvantages of these different options.

Add Transparency and Traceability with RFID

How can traceability and easy data collection help make the assembly line more transparent and efficient? I’m sure if you ask any manufacturing engineer if being able to track vendor and lot information is going to benefit them in some way, they are going to say yes! All companies have some type of ERP system set up to track parts coming in and products going out, but what goes on between those lines? If a customer reports a missing or faulty component how do you easily know where it came from?  How do you know when the product was made or who made it?

This is where RFID comes in. RFID read/write heads and data collectors can help you track and control production on the assembly. These data collectors or “tags” come in various shapes and sizes. They can be small chips attached to the workpiece carrier or they can even come as a bolt that you screw right into your part. Read/write heads also come in different sizes and have variable read/write distances or frequencies (i.e. low frequency, high frequency, and ultra-high frequency). The read/write heads connect to a processor unit that ties directly back to the PLC. Once the PLC receives this information, it can provide it to the ERP system. This takes all the information on the floor level and makes it available to the management system.

For example, say you have an unexperienced line worker on your assembly line. You are producing large diesel engines and he has the job to put together the pistons at the front of the line. Many times, he snaps the O-rings putting them on. Other times, the rings aren’t put completely in place, but he still sends the engine to the next station. When customers start calling faulty O-rings, you need an easy way to locate the source of the problem.

If you have 10 different lines changing out various engines every day, it could be difficult to narrow down the source of the problem. But if you have RFID read/write heads at each station on the line and a tag on each engine, you can look into your ERP system and track down on which line the engines in question were assembled and who was responsible for putting together the pistons.

You can then determine if the problem was human error or if the cause was due to poor quality parts, and take steps to rectify the situation. If it is determined that the rings are poor quality, you can easily determine every engine that these rings have been used on and recall only those engines. This is just a small example of how RFID can help with transparency on the assembly line. If you are looking for better ways to track inventory, vendors, or just make data more accessible to you and your company, then RFID is your answer!

Beyond the Human Eye

Have you ever had to squint, strain, adjust your glasses, or just ask for someone with better vision to help read something for you? Now imagine having to adjust your eyesight 10 times a second. This is the power of machine vision. It can adjust, illuminate, filter, focus, read, and relay information that our eyes struggle with. Although the technology is 30 years old, machine vision is still in its early stages of adoption within the industrial space. In the past, machine vision was ‘nice to have’ but not really a ‘need to have’ technology because of costs, and the technology still not being refined. As traceability, human error proofing, and advanced applications grow more common, machine vision has found its rhythm within factory automation. It has evolved into a robust technology eager to solve advanced applications.

Take, for example, the accurate reading, validation, and logging of a date located on the concaved bottom of an aluminum can. Sometimes, nearly impossible to see with the human eye without some straining involved, it is completely necessary to ensure it is there to be able to sell the product. What would be your solution to ensuring the date stamp is there? Having the employee with the best eyes validate each can off the line? Using more ink and taking longer to print a larger code? Maybe adding a step by putting a black on white contrasting sticker on the bottom that could fall off? All of these would work but at what cost? A better solution is using a device easily capable of reading several cans a second even on a shiny, poor angled surface and saving a ton of unnecessary time and steps.

Machine vison is not magic; it is science. By combining high end image sensors, advanced algorithms, and trained vision specialists, an application like our aluminum can example can be solved in minutes and run forever, all while saving you time and money. In Figure 1 you can see the can’s code is lightly printed and overcome by any lighting due to hotspots from the angle of the can. In Figure 2 we have filtered out some of the glare, better defined the date through software, and validate the date is printed and correct.

Take a moment to imagine all the possibilities machine vision can open for your production process and the pain points it can alleviate. The technology is ready, are you?

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Figure 2

Using Data to Drive Plant Productivity

What is keeping us from boosting productivity in our plants to the next level? During a recent presentation on Industry 4.0 and IIoT, I was asked this question.

The single biggest thing, in my opinion, that is keeping us from boosting productivity to the next level is a lack of DATA. Specifically, data about the systems and the processes.


Since the beginning of time, we have been hungry for efficiency. While early man invented more efficient methods to hunt and survive, today we are looking for ways to produce more efficiently in our plants with minimum or zero waste. After exhausting all the avenues for lean operations on plant procedures and our day-to-day activities, we are now looking at how we can recover from unanticipated downtime quickly. I am sure in future we will be seeking information on how can we prevent the downtime altogether.

There are plentiful of reasons for downtime. Just a few examples:

  1. Unavailability of labor – something we might be experiencing these days, when the COVID-19 pandemic has reduced some labor forces
  2. Unavailability of raw materials
  3. Unavailability of replacement components
  4. Unavailability of assets
  5. Failures in machines/components

In this list, the first two reasons, are beyond the scope of this blog’s intentions and frankly somewhat out of controls from the production standpoint.

The next two reasons, however, are process related and the last one is purely based on the choices we made. These three reasons, to a certain extent, can be reduced or eliminated.

If the downtime is process related, we can learn from them and improve our processes with so called continuous improvement initiatives. We can only do these continuous improvements based on observable factors (a.k.a. data) and we cannot improve our processes based on speculations. Well, I shouldn’t say “cannot”, but it will be more like a fluke or luck. It is apt to say “ what can’t be measured, can’t be improved!”

A good example for elaborating my point is change-over in the plant to produce a different product. Unless there is a good process in place for ensuring all the change-over points are properly addressed and all the change parts are correctly installed and replaced, the changeover time could and will likely lead to tremendous amounts of lost productivity. Secondly, if these processes are done manually and not automated, that is also a loss of productivity or, as I like to say, an area for continuous improvement to boost productivity based on observable facts. Sometimes, we take these manual change-overs as a fact of life and incorporate that time required as a part of “planned” downtime.  Of course, if you do change-overs once a year – it may be cost effective to keep the process manual even in today’s situation. But, if your plant has multiple short batch productions per day or per week, then automating the changeovers could significant boost productivity. The cost benefit analysis should help prove if it is continuous improvement or not.

Assets are an important part of the equation for smooth operations. An example would be molds in the stamping plant or cutting-deburring tools in metal working plants. If plants have no visibility or traceability of these important assets for location, shape or form, it could lead to considerable downtime. The calibration data of these tools or number of parts produced with the tool are also important pieces of data that needs to be maintained for efficient operations. Again, this is data about the system and the integration of these traceability initiatives in the existing infrastructure.

Failures in machines or components could cause severe downtime and are often considered as unavoidable. We tackle these failures in a two-step approach. First, we hunt for the problem when it is not obvious, and two, we find the replacement part in the store room to change it out quickly. And, as process improvement, we schedule preventative maintenance to inspect, lubricate and replace parts in our regular planned downtime.

The preventative maintenance is typically scheduled based on theoretical rate of failure. This is a good measure, especially for mechanical components, but, predictive or condition-based maintenance usually yields higher returns on productivity and helps keep plants running smooth. Again, predictive maintenance relies on data about the condition of the system or components. So, where is this data and how do we get to it?

Standardization of interfaces is another important component for boosting productivity. In my next blog, I will share how IO-Link as a technology can help address all of these challenges and boost productivity to the next level.

Tracking and Traceability in Mobility: A Step Towards IIoT

In today’s highly competitive automotive environment, it is becoming increasingly important for companies to drive out operating costs in order to ensure their plants maintain a healthy operating profit.

Improved operational efficiency in manufacturing is a goal of numerous measures. For example, in Tier 1 automotive parts manufacturing it is common place to have equipment that is designed to run numerous assemblies through one piece of capital equipment (Flexible Manufacturing). In order to accommodate multiple assemblies, different tooling is designed to be placed in this capital equipment. This reduces required plant floor real-estate and the costs normally required for unidimensional manufacturing equipment. However, with this flexibility new risks are introduced, such as running the machine with incorrect tooling which can cause increased scrap levels, incorrect assembly of parts and/or destruction/damage of expensive tooling, expedited freight, outsourcing costs, increased manpower, sorting and rework costs, and more.

Having operators manually enter recipes or tooling change information introduces the Human Error of Probability (HEP).  “The typical failure rates in businesses using common work practices range from 10 to 30 errors per hundred opportunities. The best performance possible in well managed workplaces using normal quality management methods are failure rates of 5 to 10 in every hundred opportunities.” (Sondalini)

Knowing the frequency of product change-over rates, you can quickly calculate the costs of these potential errors. One means of addressing this issue is to create Smart Tooling whereby RFID tags are affixed on the tooling and read/write antennas are mounted on the machinery and integrated into the control architecture of the capital equipment. The door to a scalable solution has now been opened in which each tool is assigned a unique ID or “license plate” identifying that specific tooling. Through proper integration of the capital equipment, the plant can now identify what tooling is in place at which OP station and may only run if the correct tooling is confirmed in place. In addition, one can then move toward predictive maintenance by placing process data onto the tag itself such as run time, parts produced, and tooling rework data. Collection and monitoring of this data moves the plant towards IIoT and predictive maintenance capabilities to inform key personnel when tooling is near end of life or re-work requirement thus contributing to improved OEE (Overall Equipment Effectiveness) rates.


For more information on RFID, visit www.balluff.com.

*Source: Mike Sondalini, Managing Director, Lifetime Reliability Solutions, Article: Unearth the answers and solve the causes of human error in your company by understanding the hidden truths in human error rate tables