Manufacturers Track Goods, Reduce Errors, Decrease Workload with RFID

More and more, retailer sellers are starting to require that manufacturers place RFID tags on their products before they leave the production facility and are shipped to those retail locations. From high-end electronics all the way down to socks and underwear are being tagged.

These tags are normally supplied by the retailer or through a contracted third party. Typically disposable UHF paper tags, they are only printed with a TID number and a unique EPC that may or may not correspond to the UPC and barcode that was used in the past. Most cases I have seen require that the UPC and a barcode be printed on these RFID tags so there is information available to the human eye and a barcode scanner when used.

While this is being asked for by the retailers, manufacturers can use these tags to their own advantage to track what products are going out to their shipping departments and in what quantities. This eliminates human error in the tracking process, something that has been a problem in the past, while also reducing workload as boxes of finished goods no longer must be opened, counted and inspected for accuracy.

A well-designed RFID portal for these items to pass through can scan for quantities and variances in types of items in boxes as they pass through the portal. Boxes that do not pass the scan criteria are then directed off to another area for rework and reevaluation. Using human inspection for just the boxes that do not pass the RFID scan greatly reduces the labor effort and expedites the shipping process.

I recently assisted with a manufacturer in the garment industry who was having to tag his garments for a major retailer with RFID tags that had the UPC and a barcode printed on them. The tags were supplied through the retailer and the EPCs on the tags were quite different then the UPC numbers printed on them.

The manufacturer wanted to know how many garments of each type were in each box. Testing showed that this could be done by creating a check point on his conveyor system and placing UHF RFID antennas in appropriate locations to ensure that all the garments in the box were detected and identified.

In this case, the manufacturer wanted was a simple stand-alone system that would display a count of different types of garments. An operator reviewed the results on a display and decided based on the results whether to accept the box and let the conveyor forward it to shipping or reject it and divert it to another conveyor line for inspection and adjustment.

While this system proved to be relatively simple and inexpensive, it satisfied the desires of the manufacturer. It is, however, possible to connect an RFID inspection station to a manufacturing information system that would know what to expect in each box and could automatically accept or reject boxes based on the results of the scans without human intervention and/or human error.

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?

Figure 1
Figure 1
Figure 2
Figure 2

Palletized Automation with Inductive Coupling

RFID is an excellent way to track material on a pallet through a warehouse. A data tag is placed on the pallet and is read by a read/write head when it comes in range. Commonly used to identify when the pallet goes through the different stages of its scheduled process, RFID provides an easy way to know where material is throughout a process and learn how long it takes for product to go through each stage. But what if you need I/O on the pallet itself or an interchangeable end-of-arm tool?

Inductive Coupling

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Inductive coupling delivers reliable transmission of data without contact. It is the same technology used to charge a cell phone wirelessly. There is a base and a remote, and when they are aligned within a certain distance, power and signal can be transferred between them as if it was a standard wire connection.

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When a robot is changing end-of-arm tooling, inductive couplers can be used to power the end of arm tool without the worry of the maintenance that comes with a physical connection wearing out over time.

For another example of how inductive couplers can be used in a process like this, let’s say your process requires a robot to place parts on a metal product and weld them together. You want I/O on the pallet to tell the robot that the parts are in the right place before it welds them to the product. This requires the sensors to be powered on the pallet while also communicating back to the robot. Inductive couplers are a great solution because by communicating over an air gap, they do not need to be connected and disconnected when the pallet arrives or leaves the station. When the pallet comes into the station, the base and remote align, and all the I/O on the pallet is powered and can communicate to the robot so it can perform the task.

Additionally, Inductive couplers can act as a unique identifier, much like an RFID system. For example,  when a pallet filled with product A comes within range of the robot, the base and remote align telling the robot to perform action A. Conversely, when a pallet loaded with product B comes into range, the robot communicates with the pallet and knows to perform a different task. This allows multiple products to go down the same line without as much changeover, thereby reducing errors and downtime.

What Machine Vision Tool is Right for Your Application?

Machine vision is an inherent terminology in factory automation but selecting the most efficient and cost-effective vision product for your project or application can be tricky.

We can see machine vision from many angles of view, for example market segment and application or image processing deliver different perspectives. In this article I will focus on the “sensing element” itself, which scan your application.

The sensing element is a product which observes the application, analyzes it and forwards an evaluation. PC is a part of machine vision that can be embedded with the imager or separated like the controller. We could take many different approaches, but let’s look at the project according to the complexity of the application. The basic machine vision hardware comparison is

  1. smart sensors
  2. smart cameras
  3. vision systems

Each of these products are used in a different way and they fit different applications, but what do they all have in common? They must have components like an imager, lens, lighting, SW, processor and output HW. All major manufacturing companies, regardless of their focus or market segment, use these products, but what purpose and under what circumstances are they used?

Smart Sensors

Smart sensors are dedicated to detecting basic machine vision applications. There are hundreds of different types on the market and they must quickly provide standard performance in machine vision. Don’t make me wrong, this is not necessarily a negative. These sensors are used for simple applications. You do not want to wait seconds to detect QR code; you need a response time in milliseconds. Smart sensors typically include basic functions like:

  • data matrix, barcode and 2D code reading
  • presence of the object,
  • shape, color, thickness, distance

They are typically used in single purpose process and you cannot combine all the features.

Smart Cameras

Smart cameras are used in more complex projects. They provide all the function of smart sensors, but with more complex functions like:

  • find and check object
  • blob detection
  • edge detection
  • metrology
  • robot navigation
  • sorting
  • pattern recognition
  • complex optical character recognition

Due to their complexity, you can use them to find products with higher resolution , however it is not a requirement. Smart cameras can combine more programs and can do parallel several functions together. Image processing is more sophisticated, and limits may occur in processing speed, because of embedded PC.

Vision Systems

Typically, machine vision systems are used in applications where a smart camera is not enough.

Vision system consists of industrial cameras, controller, separated lighting and lens system, and it is therefore important to have knowledge of different types of lighting and lenses. Industrial cameras provide resolution from VGA up to 30Mpxl and they are easy connected to controller.

Vision systems are highly flexible systems. They provide all the functions from smart sensors and cameras. They bring complexity as well as flexibility. With a vision system, you are not limited by resolution or speed. Thanks to the controller, you have dedicated and incomparable processing power which provides multi-speed acceleration.

And the most important information at the end. How does it look with pricing?

You can be sure that smart sensor is the most inexpensive solution. Basic pricing is in the range of $500 – $1500. Smart cameras can cost $2000 – $5000, while a vision system cost would start closer to $6000. It may look like an easy calculation, but you need to take into consideration the complexity of your project to determine which is best for you.

Pros Cons Cost
Smart sensor
    • Easy integration
    • Simple configuration
    • Included lightning and lenses
    • Limited functions
    • Closed SW
    • Limited programs/memory
$
Smart camera
    • Combine more programs together
    • Available functions
    • Limited resolution
    • Slower speed due to embedded PC
$$
Vision system
    • Connect more cameras(up to 8)
    • Open SW
    • Different resolution options
    • Requires skilled machine vision specialist
    • Requires knowledge of lightning and lenses
    • Increased integration time
$$$

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Not All RFID is Created Equal: Is Yours Built for an Industrial Environment?

The retail environments where products are sold look nothing like the industrial environments where they are produced (think of the difference between a new car dealership and an automotive manufacturing plant). Yet the same RFID products developed for retail stores and their supply chain operations are still marketed to manufacturers for production operations. These products may work fine in warehouses, but that does not necessarily qualify them as industrial grade.

IO-Link_RFID

So what are the differences between retail and industrial RFID?

Production environments often require a level of ruggedness, performance, and connectivity that only purpose-built industrial equipment can reliably satisfy. For example, general-purpose RFID equipment may have the physical Ethernet port needed to connect to a PC or server, but will not support EtherNet/IP, Profinet or other industrial protocols that run on PLCs and other industrial automation control equipment. Many retail grade readers need to be supported with an additional protocol conversion, which can require external hardware and slow system performance, and adds to implementation time, difficulty, and expense.

When evaluating RFID equipment, it is essential to make the distinction between what is possible for use in the environment and what is optimal and, therefore, more reliable. There are three fundamental qualities to consider that can determine if RFID systems will perform reliably in demanding production environments:

  • Will the RFID system integrate seamlessly with industrial control systems?
  • Will it provide the reliability and speed that production and their information systems tied in require?
  • Can it maintain uptime and performance long term – will it last on the production line?

RFID is often marketed as a “solution,” however in manufacturing operations, it is almost always used as a supporting technology to provide data and visibility to the MES, ERP, e-Kanban, robotics, asset tracking, material handling, quality control and other systems that run in production facilities. Failure to accurately provide data to these systems at the reliability and speed levels they require eliminates the value of using RFID.

The physical environments in industrial and supply chain settings cause RFID technology to perform differently. Tag density can be a consideration for industrial RFID users like retail, but an industrial environment has much more challenging and powerful potential interference sources, for example, the presence of metal found in most industrial products and environments.

When determining whether RFID products are suitable for a specific environment, it is important to look beyond published marketing hype and misleading specifications. Consider the design and construction of the product and how it could be affected by various work processes. Whenever possible, you should test the products where they will be used rather than in a lab or demonstration area, because the actual work location has interference and environmental conditions that may be overlooked and impossible to duplicate elsewhere.

The key attributes that differentiate industrial RFID equipment from supply chain-oriented alternatives include:

  • Native support for industrial protocols;
  • High tag read reliability and the ability to continuously operate at speeds that won’t slow production systems;
  • Durable housing with secure connectors with IP65 or better rating and relevant certifications for shock, vibration and temperature resistance;
  • The ability to support multiple RFID technologies and supporting devices as needed, including sensors, PLCs, IO-Link, and other industrial automation equipment.

Compromising on any of these criteria will likely result in unnecessary implementation time, support, and replacement costs and increase the risk for system failure.

Top 5 Insights from 2019

With a new year comes new innovation and insights. Before we jump into new topics for 2020, let’s not forget some of the hottest topics from last year. Below are the five most popular blogs from our site in 2019.

1. How to Select the Best Lighting Techniques for Your Machine Vision Application

How to select the best vision_LI.jpgThe key to deploying a robust machine vision application in a factory automation setting is ensuring that you create the necessary environment for a stable image.  The three areas you must focus on to ensure image stability are: lighting, lensing and material handling.  For this blog, I will focus on the seven main lighting techniques that are used in machine vision applications.

READ MORE>>

2. M12 Connector Coding

blog 7.10_LI.jpgNew automation products hit the market every day and each device requires the correct cable to operate. Even in standard cables sizes, there are a variety of connector types that correspond with different applications.

READ MORE>>

3. When to use optical filtering in a machine vision application

blog 7.3_LI.jpgIndustrial image processing is essentially a requirement in modern manufacturing. Vision solutions can deliver visual quality control, identification and positioning. While vision systems have gotten easier to install and use, there isn’t a one-size-fits-all solution. Knowing how and when you should use optical filtering in a machine vision application is a vital part of making sure your system delivers everything you need.

READ MORE>>

4. The Difference Between Intrinsically Safe and Explosion Proof

5.14_LIThe difference between a product being ‘explosion proof’ and ‘intrinsically safe’ can be confusing but it is vital to select the proper one for your application. Both approvals are meant to prevent a potential electrical equipment malfunction from initiating an explosion or ignition through gases that may be present in the surrounding area. This is accomplished in both cases by keeping the potential energy level below what is necessary to start ignition process in an open atmosphere.

READ MORE>>

5. Smart choices deliver leaner processes in Packaging, Food and Beverage industry

Smart choices deliver leaner processes in PFB_LI.jpgIn all industries, there is a need for more flexible and individualized production as well as increased transparency and documentable processes. Overall equipment efficiency, zero downtime and the demand for shorter production runs have created the need for smart machines and ultimately the smart factory. Now more than ever, this is important in the Packaging, Food and Beverage (PFB) industry to ensure that the products and processes are clean, safe and efficient.

READ MORE>>

We appreciate your dedication to Automation Insights in 2019 and look forward to growth and innovation in 2020!

 

 

RFID for Improved Operator Accountability

One of the most fascinating parts of my job is making site visits to manufacturing plants across the country. Getting a first-hand look at how things are made in a modern manufacturing facility is nothing short of amazing. Robots whirling, automatic guided vehicles (AGV’s) navigating the floor, overhead cranes and gantries lifting tons of material over-head, flames shooting from ovens, and metal chips flying create an exciting, but sometimes dangerous, work environment. To some people this may seem like a good reason to avoid these places, but if you are fitted with the appropriate personal protective equipment (PPE) the chances for injury are minimal.

The safety of every human in the plant is the top priority.  This is why there are requirements to wear PPE that is suitable for the environment and the hazards within. The challenge is confirming that everyone is aware of the required equipment, and that they indeed are wearing that equipment.

This can be accomplished with a simple RFID kiosk system. When an operator scans their ID they are asked a series of questions to ensure they are wearing the correct PPE. If the operator confirms they are wearing all the required gear, they can begin work in the area they are assigned. If not, a supervisor will be notified so the correct equipment can be obtained. This method can serve as a daily reminder for what needs to be worn while holding the operator accountable.

Ultimately, it is up to the plant and occupational safety organizations to define what needs to be worn and where it should be worn, but it is the responsibility of the operator to actually wear it. The same system can be used for vendors, visitors or anyone else who ventures out on the plant floor.

Using RFID to Create Transparency in Production

To meet today’s requirements for fast delivery and infinite flexibility, many productions are already set up as flow production with work steps distributed to workstations. As a result, products can be individually adapted in order to optimally meet customer requirements.

The basic prerequisite for this is to continuously know where a product is in the process. Additionally, information should be available about the next workstation and the subsequent work step. Without technical assistance, the required information can only be generated by the employee with much effort. Additionally, you run the risk of production steps being confused and time delays occurring in the production process. One solution to meet the requirements with minimum effort and maximum reliability is to install automated product recognition by using an RFID system.

 
Automated product recognition with an RFID system

To install an RFID system one important prerequisite must be fulfilled. Each product that is planned to be tracked needs a compatible RFID data carrier. This enables an individual connection between the order number and the product, which is then stored in a database.

During the product creation, the stored connection is called up multiple times. Each time it is supplemented by further information. In this way product traceability can be ensured. The connection is initiated by an antenna of the RFID system, which recognizes the data carrier and its ID. The resulting data shows which product is at the workplace, the time stamp, the place of recognition and the order number, all of which are noted in the database.

image 1
Communication between RFID system, database and production employee

 

Reduction of error rate and increase of efficiency in the production

In addition to ensuring traceability, the installation of an RFID system can also significantly reduce the failure rate in the production. The connection to the database allows information to move in two ways. On one hand additional information is provided, while on the other further information is created that can be processed by other systems.

The storage of the time stamp enables an analysis of the duration of each work step. This makes the identification of potential ways to improve in the production possible. If this analysis and the implementation of the system is done consequently, the efficiency in the production can be improved continuously.

 

Tackle Quality Issues and Improve OEE in Vision Systems for Packaging

Packaging industries must operate with the highest standards of quality and productivity. Overall Equipment Effectiveness (OEE) is a scoring system widely used to track production processes in packaging. An OEE score is calculated using data specifying quality (percent of good parts), performance (performance of nominal speed) and equipment availability (percent of planned uptime).

Quality issues can directly impact the customer, so it is essential to have processes in place to ensure the product is safe to use and appropriately labeled before it ships out. Additionally, defects to the packaging like dents, scratches and inadequate labeling can affect customer confidence in a product and their willingness to buy it at the store. Issues with quality can lead to unplanned downtime, waste and loss of productivity, affecting all three metrics of the OEE score.

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Traditionally, visual inspections and packaging line audits have been used to monitor quality, however, this labor can be challenging in high volume applications. Sensing solutions can be used to partly automate the process, but complex demands, including multiple package formats and product formulas in the same line, require the flexibility that machine vision offers. Machine vision is also a vital component in adding traceability down to the unit in case a quality defect or product recall does occur.

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Vision systems can increase productivity in a packaging line by reducing the amount of planned and unplanned downtime for manual quality inspection. Vision can be reliably used to detect quality defects as soon as they happen. With this information, a company can make educated improvements to the equipment to improve repeatability and OEE and ensure that no defective product reaches the customers’ hands.

Some vision applications for quality assurance in packaging include:

  • Label inspection (presence, integrity, print quality, OCV/OCR)
    • Check that a label is in place, lined up correctly and free of scratches and tears. Ensure that any printed graphics, codes and text are legible and printed with the expected quality. Use a combination of OCR (Optical Character Recognition) to read a lot number, expiration date or product information, and then OCV (Optical Character Verification) to ensure legibility.
  • Primary and secondary packaging inspection for dents and damage
    Inspect bottles, cans and boxes to make sure that their geometry has not been altered during the manufacturing process. For example, check that a bottle rim is circular and has not been crushed so that the bottle cap can be put on after filling with product.
  • Safety seal/cap presence and position verification
    Verifying that a cap and/or seal has been placed correctly on a bottle, and/or that the container being used is the correct one for the formula / product being manufactured.
  • Product position verification in packages with multiple items
    In packages of solids, making sure they have been filled adequately and in the correct sequence. In pharmaceutical industries, this can be used to check that blister packs have a pill in each space, and in food industries to ensure that the correct food item is placed in each space of the package.
  • Certification of proper liquid level in containers
    For applications in which it can’t be done reliably with traditional sensing technologies, vision systems can be used to ensure that a bottle has been filled to its nominal volume.

The flexibility of vision systems allows for addressing these complex applications and many more with a well-designed vision solution.

For more information on Balluff vision solutions and applications, visit www.balluff.com.

Sensor and Device Connectivity Solutions For Collaborative Robots

Sensors and peripheral devices are a critical part of any robot system, including collaborative applications. A wide variety of sensors and devices are used on and around robots along with actuation and signaling devices. Integrating these and connecting them to the robot control system and network can present challenges due to multiple/long cables, slip rings, many terminations, high costs to connect, inflexible configurations and difficult troubleshooting. But device level protocols, such as IO-Link, provide simpler, cost-effective and “open” ways to connect these sensors to the control system.

Just as the human body requires eyes, ears, skin, nose and tongue to sense the environment around it so that action can be taken, a collaborative robot needs sensors to complete its programmed tasks. We’ve discussed the four modes of collaborative operation in previous blogs, detailing how each mode has special safety/sensing needs, but they have common needs to detect work material, fixtures, gripper position, force, quality and other aspects of the manufacturing process. This is where sensors come in.

Typical collaborative robot sensors include inductive, photoelectric, capacitive, vision, magnetic, safety and other types of sensors. These sensors help the robot detect the position, orientation, type of objects, and it’s own position, and move accurately and safely within its surroundings. Other devices around a robot include valves, RFID readers/writers, indicator lights, actuators, power supplies and more.

The table, below, considers the four collaborative modes and the use of different types of sensors in these modes:

Table 1.JPG

But how can users easily and cost-effectively connect this many sensors and devices to the robot control system? One solution is IO-Link. In the past, robot users would run cables from each sensor to the control system, resulting in long cable runs, wiring difficulties (cutting, stripping, terminating, labeling) and challenges with troubleshooting. IO-Link solves these issues through simple point-to-point wiring using off-the-shelf cables.

Table 2.png

Collaborative (and traditional) robot users face many challenges when connecting sensors and peripheral devices to their control systems. IO-Link addresses many of these issues and can offer significant benefits:

  • Reduced wiring through a single field network connection to hubs
  • Simple connectivity using off-the-shelf cables with plug connectors
  • Compatible will all major industrial Ethernet-based protocols
  • Easy tool change with Inductive Couplers
  • Advanced data/diagnostics
  • Parametarization of field devices
  • Faster/simpler troubleshooting
  • Support for implementation of IIoT/Industry 4.0 solutions

IO-Link: an excellent solution for simple, easy, fast and cost-effective device connection to collaborative robots.