Add Depth to Your Processes With 3D Machine Vision

What comes to mind first when you think of 3D? Cheap red and blue glasses? Paying extra at a movie theater? Or maybe the awkward top screen on a Nintendo 3DS? Neither industrial machine vision nor robot guidance likely come to mind, but they should.

Advancements in 3D machine vision have taken the old method of 2D image processing and added literal depth. You become emerged into the application with true definition of the target—far from what you get looking at a flat image.

See For Yourself

Let’s do an exercise: Close one eye and try to pick up an object on your desk by pinching it. Did you miss it on the first try? Did things look foreign or off? This is because your depth perception is skewed with only one vision source. It takes both eyes to paint an accurate picture of your surroundings.

Now, imagine what you can do with two cameras side by side looking at an application. This is 3D machine vision; this is human.

How 3D Saves the Day

Robot guidance. The goal of robotics is to emulate human movements while allowing them to work more safely and reliably. So, why not give them the same vision we possess? When a robot is sent in to do a job it needs to know the x, y and z coordinates of its target to best control its approach and handle the item(s). 3D does this.

Part sorting. If you are anything like me, you have your favorite parts of Chex mix. Whether it’s the pretzels or the Chex pieces themselves, picking one out of the bowl takes coordination. Finding the right shape and the ideal place to grab it takes depth perception. You wouldn’t use a robot to sort your snacks, of course, but if you need to select specific parts in a bin of various shapes and sizes, 3D vision can give you the detail you need to select the right part every time.

Palletization and/or depalletization. Like in a game of Jenga, the careful and accurate stacking and removing of parts is paramount. Whether it’s for speed, quality or damage control, palletization/ depalletization of material needs 3D vision to position material accurately and efficiently.

I hope these 3D examples inspire you to seek more from your machine vision solution and look to the technology of the day to automate your processes. A picture is worth a thousand words, just imagine what a 3D image can tell you.

Fork Sensors, the Best Choice for Range, Reliability, Ease of Installation

Photoelectric sensors are a staple within many industries when it comes to automation thanks to their non-contact detection over longer ranges than many other sensing types. Also available in a variety of housing types and protection classes to meet the specific demands of an application, they offer manufacturers many different variants and models. The range of styles can make selecting the perfect photoelectric sensor for your specific application challenging. This post highlights the benefits of through-beam sensors and why fork sensors specifically, are often the ideal sensor for the job.

Through-beam sensors can detect anything, regardless of color, texture or reflectivity. This makes them highly efficient in any application where material or parts need to be detected during the process. They require an emitter and receiver. The emitter sends a light beam toward the receiver. When this light beam is blocked, the sensor will trigger. A common example of this is the sensor system on a garage door that detects obstructions and keeps the door from closing. (The software can also inverse this, so the sensor triggers when the light beam is not obstructed. Read more about these light-on/dark-on modes).

Traditional Through-Beams vs. Fork Sensors

Through-beam photoelectric sensors are simple technology that are non-contact, reliable and can operate over distances up to 100 meters, making them a go-to for many applications. But they aren’t without fault. Because the emitter and receiver are typically in separate housings, the two parts must line up perfectly to work. This alignment takes extra time during assembly and is prone to problems in the future if the emitter or receiver move,  even slightly. Machine vibrations can cause a misalignment.

Fork sensors, also called C slot or U slot sensors, incorporate both the emitter and the receiver into a single body, providing the benefits of a through-beam sensor without the installation issues.

This allows for reduced installation and maintenance time of the sensor in several ways:

    • Mounting a single sensor instead of two
    • Half as many cables needed for networking
    • No touchy alignment needed when installing the sensor
    • No maintenance needed re-aligning the sensors in the future

Photoelectric fork sensors come with sensing windows widths up to 220 mm and a range of light sources to accommodate many application needs. Check them out the next time you are considering a photoelectric sensor and see if they’re the best choice for your application.

Lithium Ion Battery Manufacturing – RFID is on a Roll

With more and more consumers setting their sights on ‘Drive Electric,’ manufacturers must prepare themselves for alternative solutions to combustion engines. This change will no doubt require an alternative automation strategy for our electric futures.

The battery

The driving force behind these new electric vehicles is, of course, the battery. With this new wave of electric vehicles, the lithium ion battery manufacturing sector is growing exponentially, creating a significant need for traceability and tracking throughout the manufacturing processes.

Battery manufacturing is classified into three major production areas:

    1. Electrode manufacturing
    2. Cell assembly
    3. Finishing formation, aging and testing

These processes require flexible and efficient automation solutions to produce high quality batteries effectively. As such, there are numerous areas that can benefit from RFID and/or code reading solutions. One of the biggest of these is the electrode manufacturing process, specifically on the individual mother and daughter electrode rolls. This is a great application for UHF (Ultra-High Frequency) RFID.

The Need for RFID

The electrode formation process involves numerous production steps, including mixing, coating, calendaring, drying, slitting and vacuum drying. Each machine process generally begins with unwinding turrets and ends with winding ones. A roll-to-roll process.

Two of the three primary components of the lithium ion battery, both the anode and cathode electrode, are produced on rolls and require identification, process step validation and full traceability all the way through the plant.

During the slitting process both larger mother rolls are unwound and sliced into multiple, smaller daughter rolls. These mother and daughter rolls must also be tracked and traced through the remaining processes, into storage and ultimately, into a battery cell.

Solution

Working with our battery customers and understanding their process needs, a UHF RFID tag was developed specifically to withstand the electrode production environment. Having a tag that can withstand a high temperature range is crucial, particularly in the vacuum drying lines. This tag is capable of surviving cycling applications with temperatures up to 235 °C. Its small form factor is ideal for recess mounting in the anode and cathode roll cores with an operating range reaching 4 meters.

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The tag embedded in the roll core paired with an RFID processor and UHF antenna provides all the necessary hardware in supporting battery plants to achieve their desired objective of tracking all production steps. Customers not only have the option of obtaining read/writes, via fixed antennas at the turrets, but also handheld ones for all storage locations — from goods receiving to daughter coil storage racks within a plant.

This UHF RFID system allows for tracking from the initial electrode coils from goods received in the warehouse, through the multiple machines in the electrode manufacturing process, into the storage areas, and to the battery cell assembly going in the electric vehicle — ultimately linking all battery cells back to a particular daughter roll, and back to its initial mother roll. RFID is on a Roll!

Controls Architectures Enable Condition Monitoring Throughout the Production Floor

In a previous blog post we covered some basics about condition monitoring and the capability of smart IO-Link end-devices to provide details about the health of the system. For example, a change in vibration level could mean a failure is near.

This post will detail three different architecture choices that enable condition monitoring to add efficiency to machines, processes, and systems: in-process, stand-alone, and hybrid models.

IO-Link is the technology that enables all three of these architectures. As a quick introduction, IO-Link is a data communications technology at the device level, instead of a traditional signal communication. Because it communicates using data instead of signals, it provides richer details from sensors and other end devices. (For more on IO-Link, search the blog.)

In-process condition monitoring architecture

In some systems, the PLC or machine controller is the central unit for processing data from all of the devices associated with the machine or system, synthesizing the data with the context, and then communicating information to higher-level systems, such as SCADA systems.

The data collected from devices is used primarily for controls purposes and secondarily to collect contextual information about the health of the system/machine and of the process. For example, on an assembly line, an IO-Link photo-eye sensor provides parts presence detection for process control, as well as vibration and inclination change detection information for condition monitoring.

With an in-process architecture, you can add dedicated condition monitoring sensors. For example, a vibration sensor or pressure sensor that does not have any bearings on the process can be connected and made part of the same architecture.

The advantage of an in-process architecture for condition monitoring is that both pieces of information (process information and condition monitoring information) can be collected at the same time and conveyed through a uniform messaging schema to higher-level SCADA systems to keep temporal data together. If properly stored, this information could be used later for machine improvements or machine learning purposes.

There are two key disadvantages with this type of architecture.

First, you can’t easily scale this system up. To add additional sensors for condition monitoring, you also need to alter and validate the machine controller program to incorporate changes in the controls architecture. This programming could become time consuming and costly due to the downtime related to the upgrades.

Second, machine controllers or PLCs are primarily designed for the purposes of machine control. Burdening these devices with data collection and dissemination could increase overall cost of the machine/system. If you are working with machine builders, you would need to validate their ability to offer systems that are capable of communicating with higher-level systems and Information Technology systems.

Stand-alone condition monitoring architecture

Stand-alone architectures, also known as add-on systems for condition monitoring, do not require a controller. In their simplest form, an IO-Link master, power supply, and appropriate condition monitoring sensors are all that you need. This approach is most prevalent at manufacturing plants that do not want to disturb the existing controls systems but want to add the ability to monitor key system parameters. To collect data, this architecture relies on Edge gateways, local storage, or remote (cloud) storage systems.

 

 

 

 

 

 

The biggest advantage of this system is that it is separate from the controls system and is scalable and modular, so it is not confined by the capabilities of the PLC or the machine controller.

This architecture uses industrial-grade gateways to interface directly with information technology systems. As needs differ from machine to machine and from company to company as to what rate to collect the data, where to store the data, and when to issue alerts, the biggest challenge is to find the right partner who can integrate IT/OT systems. They also need to maintain your IT data-handling policies.

This stand-alone approach allows you to create various dashboards and alerting mechanisms that offer flexibility and increased productivity. For example, based on certain configurable conditions, the system can send email or text messages to defined groups, such as maintenance or line supervisors. You can set up priorities and manage severities, using concise, modular dashboards to give you visibility of the entire plant. Scaling up the system by adding gateways and sensors, if it is designed properly, could be easy to do.

Since this architecture is independent of the machine controls, and typically not all machines in the plant come from the same machine builders, this architecture allows you to collect uniform condition monitoring data from various systems throughout the plant. This is the main reason that stand-alone architecture is more sought after than in-process architecture.

It is important to mention here that not all of the IO-Link gateways (masters) available in the market are capable of communicating directly with the higher-level IT system.

Hybrid architectures for condition monitoring

As the name suggests, this approach offers a combination of in-process and stand-alone approaches. It uses IO-Link gateways in the PLC or machine controller-based controls architecture to communicate directly with higher-level systems to collect data for condition monitoring. Again, as in stand-alone systems, not all IO-Link gateways are capable of communicating directly with higher-level systems for data collection.

The biggest advantage of this system is that it does not burden PLCs or machine controllers with data collection. It creates a parallel path for health monitoring while devices are being used for process control. This could help you avoid duplication of devices.

When the devices are used in the controls loop for machine control, scalability is limited. By specifying IO-Link gateways and devices that can support higher-level communication abilities, you can add out-of-process condition monitoring and achieve uniformity in data collection throughout the plant even though the machines are from various machine builders.

Overall, no matter what approach is the best fit for your situation, condition monitoring can provide many efficiencies in the plant.

How Industrial RFID Can Reduce Downtime in Your Stamping Department

The appliance industry is growing at record rates. The increase in consumer demand for new appliances is at an all-time high and is outpacing current supply. Appliance manufacturers are increasing production to catch up with this demand. This makes the costs associated with downtime even higher than normal. But using industrial RFID can allow you to reduce downtime in your stamping departments and keep production moving.

Most major household appliance manufacturers have large stamping departments as part of their manufacturing process. I like to think of the stamping department as the heart of the manufacturing plant. If you have ever been in a stamping department while they are stamping out metal parts, then you understand. The thumping and vibration of the press at work is what feeds the rest of the plant.  I was in a plant a few weeks ago meeting with an engineer in the final assembly area. It was oddly quiet in that area, so I asked what was going on. He said they’d sent everyone home early because one of their major press lines went down unexpectedly. Every department got sent home because they did not have the pieces and parts needed to make the final product. That is how critical the stamping departments are at these facilities.

In past years, this wasn’t as critical, because they had an inventory of parts and finished product. But the increase in demand over the last two years depleted that inventory. They need ways to modernize the press shop, including implementing smarter products like devices with Industry 4.0 capabilities to get real-time data on the equipment for things like analytics, OEE (Overall Equipment Effectiveness), preventative maintenance, downtime, and more error proofing applications.

Implementing Industrial RFID

One of the first solutions many appliance manufacturers implement in the press department is traceability using industrial RFID technology. Traceability is typically used to document and track different steps in a process chain to help reduce the costs associated with non-conformance issues. This information is critical when a company needs to provide information for proactive product recalls, regulatory compliance, and quality standards. In stamping departments, industrial RFID is often used for applications like asset tracking, machine access control, and die identification. Die ID is not only used to identify which die is present, but it can also be tied back to the main press control system to make sure the correct job is loaded.

need for RFID in appliance stamping
This shows an outdated manual method using papers that are easily lost or destroyed.
appliance stamping can be improved by RFID
This image shows an identification painted on a die, which can be easily destroyed.

Traditionally, most companies have a die number either painted on the die or they have a piece of paper with the job set up attached to the die. I cannot tell you how many times I have seen these pieces of paper on the floor. Press departments are pretty nasty environments, so these pieces of paper get messed up pretty quickly. And the dies take a beating, so painted numbers can easily get rubbed or scratched off.

Implementing RFID for die ID is a simple and affordable solution to this problem. First, you would attach an RFID tag with all of the information about the job to each die. You could also write maintenance information about the die to this tag, such as when the die was last worked on, who last worked on it, or process information like how many parts have been made on this die.
Next, you need to place an antenna. Most people mount the antenna to one of the columns of the press where the tag would pass in front of it as it is getting loaded into the die. The antenna would be tied back to a processor or IO-Link master if using IO-Link. The processor or IO-Link master would communicate with the main press control system. As the die is set in the press, the antenna reads the tag and tells the main control system which die is in place and what job to load.

In a stamping department you might find several large presses. Each press will have multiple dies that are associated with each press. Each die is set up to form a particular part. It is unique to the part it is forming and has its own job, or recipe, programmed in the main press control system. Many major stamping departments still use manual operator entry for set up and to identify which tools are in the press. But operators are human, so it is very easy to punch in the wrong number, which is why RFID is a good, automated solution.

In conclusion

When I talk with people in stamping departments, they tell me one of the main reasons a crash occurs is because information was entered incorrectly by the operator during set up. Crashes can be expensive to repair because of the damage to the tooling or press, but also because of the downtime associated. Establishing a good die setup process is critical to a stamping department’s success and implementing RFID can eliminate many of these issues.

Choosing the Right Sensor for Your Welding Application

Automotive structural welding at tier suppliers can destroy thousands of sensors a year in just one factory. Costs from downtime, lost production, overtime, replacement time, and material costs  eat into profitability and add up to a big source of frustration for automated and robotic welders. When talking with customers, they often list inductive proximity sensor failure as a major concern. Thousands and thousands of proxes are being replaced and installations are being repaired every day. It isn’t particularly unusual for a company to lose a sensor on every shirt in a single application. That is three sensors a day  — 21 sensors a week — 1,100 sensors a year failing in a single application! And there could be thousands of sensor installations in an  automotive structural assembly line. When looking at the big picture, it is easy to see how this impacts the bottom line.

When I work with customers to improve this, I start with three parts of a big equation:

  • Sensor Housing
    Are you using the right sensor for your application? Is it the right form factor? Should you be using something with a coating on the housing? Or should you be using one with a coating on the face? Because sensors can fail from weld spatter hitting the sensor, a sensor with a coating designed for welding conditions can greatly extend the sensor life. Or maybe you need loading impact protection, so a steel face sensor may be the best choice. There are more housing styles available now than ever. Look at your conditions and choose accordingly.
  • Bunkering
    Are you using the best mounting type? Is your sensor protected from loading impact? Using a protective block can buffer the sensor from the bumps that can happen during the application.
  • Connectivity
    How is the sensor connected to the control and how does that cable survive? The cable is often the problem but there are high durability cable solutions, including TPE jacketed cables, or sacrificial cables to make replacement easier and faster.

When choosing a sensor, you can’t only focus on whether it can fulfill the task at hand, but whether it can fulfill it in the environment of the application.

For more information, visit Balluff.com

Ensure Food Safety with Machine Vision

Government agencies have put food manufacturers under a microscope to ensure they follow food safety standards and comply with regulations. When it comes to the health and safety of consumers, quality assurance is a top priority, but despite this, according to The World of Health Organization, approximately 600 million people become ill each year after eating contaminated food, and 420,000 die.

Using human manual inspection for quality assurance checks in this industry can be detrimental to the company and its consumers due to human error, fatigue and subjective opinions. Furthermore, foreign particles that should not be found in the product may be microscopic and invisible to the human eye. These defects can lead to illness, recalls, lawsuits, and a long-term negative perception of the brand itself. Packaging, food and beverage manufacturers must realize these potential risks and review the benefits of incorporating machine vision. Although machine vision implementation may sound like a costly investment, it is small price to pay when compared to the potential damage of uncaught issues. Below I explore a few benefits that machine vision offers in the packaging, food and beverage industries.

Safety
Consumers expect and rely on safe products from food manufacturers. Machine vision can see through packaging to determine the presence of foreign particles that should not be present, ensuring these products are removed from the production line. Machine vision is also capable of inspecting for cross-contamination, color correctness, ripeness, and even spoilage. For example, bruises on apples can be hard to spot for the untrained eye unless extremely pronounced. SWIR (shortwave infrared) illumination proves effective for the detection of defects and contamination. Subsurface bruising defects become much easier to detect due to the optimization of lighting and these defected products can be scrapped.

Uniformity of Containers
Brand recognition is huge for manufacturers in this industry. Products that have defects such as dents or uneven contents inside the container can greatly affect the public’s perception of the product and/or company. Machine vision can detect even the slightest deformity in the container and ensure they are removed from the line. It can also scan the inside of the container to ensure that the product is uniform for each batch. Vision systems have the ability optimize lighting intensity, uniformity, and geometry to obtain images with good contrast and signal to noise. Having the ability to alter lighting provides a much clearer image of the point of interest. This can allow you to see inside a container to determine if the fill level is correct for the specific product.

Packaging
Packaging is important because if the products shipped to the store are regularly defected, the store can choose to stop stocking that item, costing the manufacturer valuable business. The seal must last from production to arrival at the store to ensure that the product maintains its safe usability through its marked expiration date. In bottling applications, the conveyors are moving at high speeds so the inspection process must be able to quickly and correctly identify defects. A facility in Marseille, France was looking to inspect Heineken beer bottles as they passed through a bottling machine at a rate of 22 bottles/second (80,000 bottles/hour). Although this is on the faster end of the spectrum, many applications require high-speed quality checks that are impossible for a human operator. A machine vision system can be configured to handle these high-speed applications and taught to detect the specified defect.

Labels

It’s crucial for the labels to be printed correctly and placed on the correct product because of the food allergy threats that some consumers experience. Machine vision can also benefit this aspect of the production process as cameras can be taught to recognize the correct label and brand guidelines. Typically, these production lines move at speeds too fast for human inspection. An intuitive, easy to use, machine vision software package allows you to filter the labels, find the object using reference points and validate the text quickly and accurately.

These areas of the assembly process throughout packaging, food and beverage facilities should be considered for machine vision applications. Understanding what problems occur and the cost associated with them is helpful in justifying whether machine vision is right for you.

For more information on machine vision, visit https://www.balluff.com/local/us/products/product-overview/machine-vision-and-optical-identification/.

 

 

The Right Mix of Products for Recipe-Driven Machine Change Over

The filling of medical vials requires flexible automation equipment that can adapt to different vial sizes, colors and capping types. People are often deployed to make those equipment changes, which is also known as a recipe change. But by nature, people are inconsistent, and that inconsistency will cause errors and delay during change over.

Here’s a simple recipe to deliver consistency through operator-guided/verified recipe change. The following ingredients provide a solid recipe-driven change over:

Incoming Components: Barcode

Fixed mount and hand-held barcode scanners at the point-of-loading ensure correct parts are loaded.

Change Parts: RFID

Any machine part that must be replaced during a changeover can have a simple RFID tag installed. A read head reads the tag in ensure it’s the correct part.

Feed Systems: Position Measurement

Some feed systems require only millimeters of adjustment. Position sensor ensure the feed system is set to the correct recipe and is ready to run.

Conveyors Size Change: Rotary Position Indicator

Guide rails and larger sections are adjusted with the use of hand cranks. Digital position indicators show the intended position based on the recipes. The operators adjust to the desired position and then acknowledgment is sent to the control system.

Vial Detection: Array Sensor

Sensor arrays can capture more information, even with the vial variations. In addition to vial presence detection, the size of the vial and stopper/cap is verified as well. No physical changes are required. The recipe will dictate the sensor values required for the vial type.

Final Inspection: Vision

For label placement and defect detection, vision is the go-to product. The recipe will call up the label parameters to be verified.

Traceability: Vision

Often used in conjunction with final inspection, traceability requires capturing the barcode data from the final vials. There are often multiple 1D and 2D barcodes that must be read. A powerful vision system with a larger field of view is ideal for the changing recipes.

All of these ingredients are best when tied together with IO-Link. This ensures easy implantation with class-leading products. With all these ingredients, it has never been easier to implement operator-guided/verified size change.

Tire Manufacturing – IO-Link is on a Roll

Everyone working in the mobility industry knows that the tire manufacturing process is divided up into five areas throughout a large manufacturing plant.

    1. Mixing
    2. Tire prep
    3. Tire build
    4. Curing and molds
    5. Final inspection

Naturally,  conveyors, material handling, and AGV processes throughout the whole plant.

All of these areas have opportunities for IO-Link components, and there are already some good success stories for some of these processes using IO-Link.

A major opportunity for IO-Link can be found in the curing press area. Typically, a manufacturing plant will have about 75 – 100 dual cavity curing presses, with larger plants having  even more. On these tire curing presses are many inputs and outputs in analog signals. These signals can be comprised of pressure switches, sensors, pneumatic, hydraulic, linear positioning, sensors in safety devices, thermo-couples and RTD, flow and much more.

IO-Link provides the opportunity to have all of those inputs, outputs and analog devices connected directly to an IO-Link master block and hub topography. This makes it not only easier to integrate all of those devices but allows you to easily integrate them into your PLC controls.

Machine builders in this space who have already integrated IO-Linked have discovered how much easier it is to lay out their machine designs, commission the machines, and decrease their costs on machine build time and installations.

Tire manufacturing plants will find that the visual diagnostics on the IO-Link masters and hubs, as well as alarms and bits in their HMIs, will quickly help them troubleshoot device problems. This decreases machine downtime and delivers predictive maintenance capabilities.

Recently a global tire manufacturer getting ready to design the curing presses for a new plant examined the benefits of installing IO-Link and revealed a cost savings of more than $10,000 per press. This opened their eyes to evaluating IO-Link technology even more.

Tire Manufacturing is a perfect environment to present IO-Link products. Many tire plants are looking to upgrade old machines and add new processes, ideal conditions for IO-Link. And all industries are interested in ways to stretch their budget.

 

Reduce Packaging Downtime with Machine Vision

Packaging encompasses many different industries and typically has several stages in its process. Each industry uses packaging to accomplish specific tasks, well beyond just acting as a container for a product. The pharmaceutical industry for example, typically uses its packaging as a means of dispensing as well as containing. The food and beverage industry uses packaging as a means of preventing contamination and creating differentiation from similar products. Consumer goods typically require unique product containment methods and have a need for “eye-catching” differentiation.

The packaging process typically has several stages. For example, you have primary packaging where the product is first placed in a package, whether that is form-fill-seal bagging or bottle fill and capping. Then secondary packaging that the consumer may see on the shelf, like cereal boxes or display containers, and finally tertiary packaging or transport packaging where the primary or secondary packaging is put into shipping form. Each of these stages require verification or inspection to ensure the process is running properly, and products are properly packaged.

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Discrete vs. Vision-Based Error Proofing

With the use of machine vision technology, greater flexibility and more reliable operation of the packaging process can be achieved. Typically, in the past and still today, discrete sensors have been used to look for errors and manage product change-over detection. But with these simple discrete sensing solutions come limitations in flexibility, time consuming fixture change-overs and more potential for errors, costing thousands of dollars in lost product and production time. This can translate to more expensive and less competitively priced products on the store selves.

There are two ways implementing machine vision can have a benefit toward improving the scheduled line time. The first is reducing planned downtime by reducing product change over and fixturing change time. The other is to decrease unplanned downtime by catching errors right away and dynamically rejecting them or bringing attention to line issues requiring correction and preventing waste. The greatest benefit vision can have for production line time is in reducing the planned downtime for things like product changeovers. This is a repeatable benefit that can dramatically reduce operating costs and increase the planned runtime. The opportunities for vision to reduce unplanned downtime could include the elimination of line jams due to incorrectly fed packaging materials, misaligned packages or undetected open flaps on cartons. Others include improperly capped bottles causing jams or spills and improper adjustments or low ink causing illegible labeling and barcodes.

Cost and reliability of any technology that improves the packaging process should always be proportional to the benefit it provides. Vision technologies today, like smart cameras, offer the advantages of lower costs and simpler operation, especially compared to the older, more expensive and typically purpose-built vision system counterparts. These new vision technologies can also replace entire sensor arrays, and, in many cases, most of the fixturing at or even below the same costs, while providing significantly greater flexibility. They can greatly reduce or eliminate manual labor costs for inspection and enable automated changeovers. This reduces planned and unplanned downtime, providing longer actual runtime production with less waste during scheduled operation for greater product throughput.

Solve Today’s Packaging Challenges

Using machine vision in any stage of the packaging process can provide the flexibility to dramatically reduce planned downtime with a repeatable decrease in product changeover time, while also providing reliable and flexible error proofing that can significantly reduce unplanned downtime and waste with examples like in-line detection and rejection to eliminate jams and prevent product loss. This technology can also help reduce or eliminate product or shipment rejection by customers at delivery. In today’s competitive market with constant pressure to reduce operating costs, increase quality and minimize waste, look at your process today and see if machine vision can make that difference for your packaging process.