Navigating the Automotive Plant for Automation Opportunities

When one first looks at an automotive manufacturing plant, the thought of identifying opportunities for automation may be overwhelming to some.

These plants are multi-functional and complex. A typical plant manages several processes, such as:

    • Press, stamping, and dye automation
    • Welding, joining, and body in white
    • Painting
    • Final assembly
    • Robot cell
    • Material handling, including AGV, conveyor, and ASRS
    • Engine and powertrain assembly
    • Casting and machining parts
    • EV and EV sub-processes

Navigating the complexity of the automation processes in your plant to promote more automation products will take some time. You will have to look at this task by:

Time. When tackling a large automotive plant, it’s important to understand how to dissect it into smaller parts and spread out your strategies over a full year or two.

Understanding. Probably the most important thing is to understand the processes and flow of the build assembly process in a plant and then to list the strategic products that can be of use in each area.

Prioritizing. Once you have a good understanding of the plant processes and a strategic timeline to present these technologies, the next step is to prioritize your time and the technology to the highest return on investment. You may now learn that your company could use a great deal of weld cables and weld sensors, for example, so this would be your starting point for presenting this new automation technology.

Knowing who to talk to in the plant. The key to getting the best return on your time and fast approval of your automation technology is knowing the key people in the plant who can influence the use of new automation technology. Typically, you should know/list and communicate monthly with engineering groups, process improvement groups, maintenance groups, purchasing and quality departments. Narrowing down your focus to specific groups or individuals can help you get technology approval faster, etc. Don’t feel like you need to know everyone in the plant, just the key individuals.

Knowing what subjects to discuss. Don’t just think MRO! Talk about the five technology opportunities to have new automation in your plant, including:

        1. MRO
        2. Large programs and specs
        3. Project upgrades
        4. Training
        5. VMI/vending

Most people concentrate on the MRO business and don’t engage in discussions to find out these other ways to introduce automation technology in your plant. Concentrating on all five of these opportunities will lead to placing a lot of automation in the plant for a very long time.

So, when you look at your plant be very excited about all the opportunities to present automation throughout it and watch your technology levels soar to levels of manufacturing excellence.

Good luck as you begin implementing your expansion of automation technology.

Understanding Image Processing Standards and Their Benefits

In the industrial image processing world, there are standards – GenICam, GigE Vision, and USB3 Vision – that are similar to the USB and Ethernet standards used in consumer products. What do these image processing standards mean, and what are their benefits?

The GenICam standard, which is maintained by the European Machine Vision Association (EMVA), serves as a base for all the image processing standards. This standard abstracts the user access to the features of a camera and defines the Standard Feature Naming Convention (SFNC) that all manufacturers use so that common feature names are used to describe the same functions.

Additionally, manufacturers can add specific “Quality of Implementation” features outside of the SFNC definitions to differentiate their products from ones made by other manufacturers. For example, a camera can offer specific features like frame average, flat field correction, logic gates, etc. GenICam/GigE Vision-based driver and software solutions from other manufacturers can also use these features without any problem.

“On-the-wire” standards

USB3 Vision and GigE Vision are “on-the-wire” interfaces between the driver and the camera. These standards are maintained by the Automated Imaging Association (AIA). You are probably familiar with “on-the-wire” standards and their advantages if you have used plug-and-play devices like USB memory sticks, USB mice, or USB hard disks. They work together without any problem, even if they are made by different manufacturers. It’s the same thing with GenICam/GigE Vision/USB3 Vision-based driver/software solutions. The standards define a transport layer, which controls the detection of a device, configuration (register access), data streaming (device detection), and event handling, and connects the interface to GenICam (Figure 1).

USB3 Vision builds on the GigE Vision standard by including accessories like cables. The mechanics are part of the standard and defines lockable cable interfaces, as one example. This creates a more robust interface for manufacturing environments.

Are standards a must-have?

Technically, standards aren’t necessary. But they make it possible to use products from multiple manufacturers and make devices more useful in the long term. For a historical comparison, look at USB 2.0 cameras and GigE Vision. USB 2.0 industrial cameras were introduced in 2004 and only worked with proprietary drivers (Figure 2) between the client and Vision Library/SDK and between the driver and camera. Two years later, Gigabit Ethernet cameras were introduced with the GigE Vision image processing standard, which didn’t require proprietary drivers to operate.

In the case of a system crash, users of the USB 2.0 cameras wouldn’t know whether the proprietary driver or the software library was to blame, which made them difficult to support. During the decision phase of selecting sensors and support, the customer had to keep the product portfolio in mind to meet their specifications. Afterward, the application was implemented and only worked with the proprietary interfaces of the manufacturer. In case of future projects or adaptions –for example, if a new sensor was required –it would have been necessary for the manufacturer to offer this sensor. Otherwise, it was necessary to change the manufacturer, which meant that a new implementation of the software was necessary as well. In contrast, flexibility is a big advantage with Gigabit Ethernet cameras and GigE Vision: GigE Vision-compliant cameras can be used interchangeably without regard to the manufacturer.

Despite this obvious benefit, USB cameras are more prevalent in certain image processing fields like medicine, given that the applications define the camera’s sensor resolution, image format and image frequency (bandwidth), and the environment for the purpose of cable length, frame grabber, or digital camera solution. With such tightly-defined requirements, USB cameras solve the challenges of these applications.

It’s hard to believe, but a few years ago, there weren’t any standards in the image processing market. Each manufacturer had its own solution. These times are gone – the whole market has pulled together, to the benefit of customers. Because of the standards, the interaction between hardware, driver, and software delivers the experience of a uniform piece. The quality of the market is improved. For the customer, it is easier to make product decisions since they are not locked into one company’s portfolio. With standards-compliant products, the customer can always choose the best components, independent of the company. With GenICam as a base, the image processing market offers the best interface for every application, either with GigE Vision or USB3 Vision.

Edge Gateways To Support Real-Time Condition Monitoring Data

In my previous blog post from early summer, I talked about IO-Link sensors with condition monitoring features that work with PLCs. I covered how condition monitoring variables can be set up as alarms and how simple logic can be set up inside the sensor so it only sets off those alarms to the PLC in real time to alert operators when something is wrong. Many companies, however, take advantage of the IoT sensor data with the long-term goal of analyzing the environmental data conditions to predict maintenance needs in real-time versus relying on a schedule. Some even want to connect directly to their MES systems to inform maintenance personnel of daily maintenance orders, which requires a separate device, such as an IoT edge gateway.

Edge gateway benefits

The biggest benefit of an IoT edge gateway is the ability to process and store large amounts of data quickly, enabling real-time applications to use that data efficiently.

An IoT edge gateway typically sits at the end or edge of your network and gathers all the sensor data either directly from the sensors or from the PLC. Since there will be a large amount of data from all the sensors on the network, part of the edge gateway setup is to filter the relevant and important information and process this vast amount of data. The edge gateway must also handle the amount of data required reliably, and it must have low latency. These important factors are often associated with the gateway’s CPU and memory specifications.

After looking at the performance of the edge gateway, comes the ‘gateway’ aspect which provides a translation to different communications networks, whether local or cloud-based. There are the hardware specs of the gateway, whether it’s using serial, USB or Ethernet for that connection, as well as the environmental ratings on the gateway. Then, more importantly, is the software side of the edge gateway. There are cloud-based communications standards designed for different applications and for either private or public cloud networks.

Edge gateways support different communications protocols, such as HTTPS, MQTT, RESTful API, C/Python API. The gateway portion also helps in the conversion of those protocols and the ease of interoperability to different platforms, such as AWS, Azure, Ignition, and Wonderware. This provides data transparency so that all the data gathered can be used across the many different software platforms.

To get to the IoT end goal, an edge gateway is necessary and it’s important to choose the correct one.

Why Invest in Smart Manufacturing Practices?

We’re all privy to talks about smart manufacturing, smart factory, machine learning, IIOT, ITOT convergence, and so on, and many manufacturers have already embarked on their smart manufacturing journeys. Let’s take a pause and really think about it… Is it really important or is it a fad? If it is important, then why?

In my role traveling across the U.S. meeting various manufacturers and machine builders, I often hear about their needs to collect data and have certain types of interfaces. But they don’t know what good that data is going to do. Well, let’s get down to the basics and understand this hunger for data and smart manufacturing.

Manufacturing goals

Since the dawn of industrialization, the industry has been focused on efficiency – always addressing issues of how to produce more, better and quicker. The goal of manufacturing always revolved around these four things:

    1. Reduce total manufacturing and supply chain costs
    2. Reduce scrap rate and improve quality
    3. Improve/increase asset utilization and machine availability
    4. Reduced unplanned downtime

Manufacturing megatrends

While striving for these goals, we have made improvements that have tremendously helped us as a society to improve our lifestyle. But we are now in a different world altogether. The megatrends that are affecting manufacturing today require manufacturers to be even more focused on these goals to stay competitive and add to their bottom lines.

The megatrends affecting the whole manufacturing industry include:

    • Globalization: The competition for a manufacturer is no longer local. There is always somebody somewhere making products that are cheaper, better or more available to meet demand.
    • Changing consumer behavior: I am old enough to say that, when growing up, there were only a handful of brands and only certain types of products that made it over doorsteps. These days, we have variety in almost every product we consume. And, our taste is constantly changing.
    • Lack of skilled labor: Almost every manufacturer that I talk to expresses that keeping and finding good skilled people has been very difficult. The baby boomers are retiring and creating huge skills gaps in the workplaces.
    • Aging equipment: According to one study, almost $65B worth of equipment in the U.S. is outdated, but still in production. Changing regulations require manufacturers to track and trace their products in many industries.

Technology has always been the catalyst for achieving new heights in efficiency. Given the megatrends affecting the manufacturing sector, the need for data is dire. Manufacturers must make decisions in real-time and having relevant and useful data is a key to success in this new economy.

Smart manufacturing practices

What we call “smart manufacturing practices” are practices that use technology to affect how we do things today and improve them multifold. They revolve around three key areas:

    1. Efficiency: If a line is down, the machine can point directly to where the problem is and tell you how to fix it. This reduces downtime. Even better is using data and patterns about the system to predict when the machine might fail.
    2. Flexibility: Using technology to retool or change over the line quickly for the next batch of production or responding to changing consumer tastes through adopting fast and agile manufacturing practices.
    3. Visibility: Operators, maintenance workers, and plant management all need a variety of information about the machine, the line, or even the processes. If we don’t have this data, we are falling behind.

In a nutshell, smart manufacturing practices that focus on one or more of these key areas, helps manufacturers boost productivity and address challenges presented by the megatrends. Hence, it is important to invest in these practices to stay competitive.

One more thing: There is no finish line when it comes to smart manufacturing. It should become a part of your continuous improvement program to evaluate and invest in technology that offers you more visibility, improves efficiency, and adds more flexibility to how you do things.

Machine Failures and Condition Monitoring – Selecting Sensors

In previous blogs, we discussed the different types of machine failures and their implications for different maintenance approaches, the cost-benefit tradeoffs of these maintenance approaches, and the progression of machine failures and indicators that emerge at various failure phases. We now will connect the different failure indicators to the sensors which can detect them.

The Potential – Functional Failure (P-F) curve gives a rough picture of when various indicators may emerge during the progression of a failure:

Each indicator can be detected by one or more types of sensors. Selection of the “best” sensor will depend on the machine/asset being monitored, other attributes being sensed, budget/cost-benefit tradeoff, and the maintenance approach. In some cases, a single-purpose, dedicated condition-monitoring sensor may be the right choice. In other cases, a multi-function sensor (“Smart Automation and Monitoring System sensor”) which can handle both condition monitoring and standard sensing tasks may be an elegant and cost-effective solution.

The table below gives some guidance to possible single- and multi-function sensors which can address the various indicators:

* Condition monitoring sensors are specialized sensors that can often detect multiple indicators including vibration, temperature, humidity, and ambient pressure.

# Smart Automation and Monitoring System sensors add condition monitoring sensing, such as vibration and temperature, to their standard sensing functions, such as photoelectric, inductive, or capacitive sensing

There is a wide range of sensors that can provide the information needed for condition monitoring indication. The table above can provide some guidance, selecting the best fit requires an evaluation of the application, the costs/benefits, and fit with the maintenance strategy.

IO-Link Changeover: ID Without RFID – Hub ID

When looking at flexible manufacturing, what first comes to mind are the challenges of handling product changeovers. It is more and more common for manufacturers to produce multiple products on the same production line, as well as to perform multiple operations in the same space.

Accomplishing this and making these machines more flexible requires changing machine parts to allow for different stages in the production cycle. These interchangeable parts are all throughout a plant: die changes, tooling changes, fixture changes, end-of-arm tooling, and more.

When swapping out these interchangeable parts it is crucial you can identify what tooling is in place and ensure that it is correct.

ID without RFID

When it comes to identifying assets in manufacturing today, typically the first option companies consider is Radio-Frequency Identification (RFID). Understandably so, as this is a great solution, especially when tooling does not need an electrical connection. It also allows additional information beyond just identification to be read and written on the tag on the asset.

It is more and more common in changeover applications for tooling, fixtures, dies, or end-of-arm tooling to require some sort of electrical connection for power, communication, I/O, etc. If this is the case, using RFID may be redundant, depending on the overall application. Let’s consider identifying these changeable parts without incurring additional costs such as RFID or barcode readers.

Hub ID with IO-Link

In changeover applications that use IO-Link, the most common devices used on the physical tooling are IO-Link hubs. IO-Link system architectures are very customizable, allowing great flexibility to different varieties of tooling when changeover is needed. Using a single IO-Link port on an IO-Link master block, a standard prox cable, and hub(s), there is the capability of up to: 

    • 30 Digital Inputs/Outputs or
    • 14 Digital Inputs/Outputs and Valve Manifold Control or
    • 8 Digital Inputs/Outputs and 4 Analog Voltage/Current Signals or
    • 8 Analog Input Signals (Voltage/Current, Pt Sensor, and Thermocouple)

When using a setup like this, an IO-Link 1.1 hub (or any IO-Link 1.1 device) can store unique identification data. This is done via the Serial Number Parameter and/or Application Specific Tag Parameter. They act as a 16- or 32-byte memory location for customizable alphanumeric information. This allows for tooling to have any name stored within that memory location. For example, Fixture 44, Die 12, Tool 78, EOAT 123, etc. Once there is a connection, the controller can request the identification data from the tool to ensure it is using the correct tool for the upcoming process.

By using IO-Link, there are a plethora of options for changeover tooling design, regardless of various I/O requirements. Also, you can identify your tooling without adding RFID or any other redundant hardware. Even so, in the growing world of Industry 4.0 and the Industrial Internet of Things, is this enough information to be getting from your tooling?

In addition to the diagnostics and parameter setting benefits of IO-Link, there are now hub options with condition monitoring capabilities. These allow for even more information from your tooling and fixtures like:

    • Vibration detection
    • Internal temperature monitoring
    • Voltage and current monitoring
    • Operating hours counter

Flexible manufacturing is no doubt a challenge and there are many more things to consider for die, tooling and fixture changes, and end-of-arm tooling outside of just ID. Thankfully, there are many solutions within the IO-Link toolbox.

For your next changeover, I recommend checking out Non-Contact Inductive Couplers Provide Wiring Advantages, Added Flexibility and Cost Savings Over Industrial Multi-Pin Connectors for a great solution for non-contact connectivity that can work directly with Hub ID.

Detecting Fill Levels With Direct Contact and Non-contact Capacitive Sensors

Capacitive sensors are commonly used in level detection applications. Specific capacitive sensors can supply better solutions than others depending on the type of media you may be detecting and if the sensor will be in direct contact with that media. Keep reading to decide which type works best for different application solutions.

Non-contact capacitive sensors

Capacitive sensors are great for monitoring the fill level of non-conductive materials. In many cases, the capacitive sensor doesn’t need to physically touch the media it is detecting; rather, it can sit outside a thin, non-metal container or pipe. As the level rises or falls, the capacitive sensor can signal if the medium is there. Since non-contact capacitive sensors sit outside the medium, there shouldn’t be any interference or false readings from direct contact with the material.

Selecting the correct capacitive sensor for these applications is important. While you don’t have to risk contaminating the sensor face (and getting a false read) in non-contact applications, you need to keep in mind other factors that can cause a sensor to false trip. One thing that is important to keep in mind with externally mounted capacitive sensors is that viscous materials can still leave a layer of residue on the inside walls of tanks or basins. While the sensor face is not covered, if you select the wrong type of sensor this build up on the wall can cause a false reading (such as reading as reading the tank as full when it is actually half-empty).

Another thing to keep in mind when selecting the correct capacitive sensor for a non-contact application is foam. In applications such as bottling beer in glass bottles, most standard capacitive sensors will detect presence once that layer of foam reaches the sensor face. While the foam may be at the sensor face, the bottle could still be only half way full of actual liquid. Making sure you select a sensor that can account for things like foam is something to keep in mind as well.

There are many benefits when using non-contact capacitive sensors in fill level applications. Not every application requires direct contact with the medium, and not every application even allows for the medium to be touched directly. There are many capacitive sensors in many form factors that are used every day for fill level applications, but making sure the right sensor is selected is important.

Contact with media capacitive sensors

In certain applications, the capacitive sensor will only be able to detect the fill level of a container, pipe, or tank if it is in direct contact with the media it’s trying to sense.

For various reasons, a sensor must be in direct contact with a media like oil, paint, powder, or paste. You may need to place a sensor directly in a tank because the tank is made of metal, or possibly because the walls of the tank are too thick for a capacitive sensor to sense through. Direct contact applications can be difficult to find solutions for if you are not aware of what capacitive sensors are capable of.

There is a way to fix issues such as false tripping in sticky substances.

Advanced technologies allow for capacitive sensors that mask residual build-up or foam when sensing in direct media contact. These level-sensing capacitive sensors are great for applications in the food and beverage industry and for detecting practically all the same materials as non-contact capacitive sensors. In areas of detection where adhesive substances may stick to the sensor face is a perfect application for direct contact capacitive sensors. Some typical direct-contact applications include areas such as vegetable oil or ketchup container fill levels, hydraulic oil levels in a hydraulic cylinder, or even the amount of flour in a container.

For instance, if you stick a capacitive sensor inside a tank of oil to monitor the fill level, the sensor face will get covered in the oil. As the level in the tank drops below the sensor face, that oil will remain on the face. So, even if the tank is empty, the sensor will always detect something. With specialized capacitive sensors that ignore build-up, adhesive or viscous media that typically influence detection is no longer a concern.

Another use for capacitive sensors that allow for direct media contact is for leak detection. If a tank, pipe, or tub is known to leak, there are capacitive sensors that can be mounted to the ground in the area that puddles form. In some instances you know a machine could potentially leak, and puddles form in an area you can’t regularly see, which is where these sensors are perfect for application. Depending on the situation, some of these sensors can be mounted a couple millimeters to an inch off the ground waiting for a leak. As a puddle forms and reaches the sensor’s switching range, maintenance can be alerted of the issue and work to fix it.

Reduce time and costs associated with manual level-checking

Another application for a capacitive sensor with direct media contact capabilities is within the automotive industry. Inside the painting process of an assembly plant, for example, you must be able to monitor the fill levels of the e-coat, the primer, the base coat, and the clear-coat paint tanks. Without a sensor to determine the fill levels, the time and energy and dollars it can cost the workforce to manually check the fill levels can be high.. Luckily, these contact-capacitive sensors can monitor viscous media like paint, reducing the time and costs associated with manual level-checking.

While non-contact and contact capacitive sensors perform the similar functions, they are used in different applications. Some applications allow a sensor to sit outside a container or tank and detect through the walls, while others require direct contact. Now that you understand the differences and their strong points of application, you can determine which sensor is best for you.

Choosing the Right Sensor for Measuring Distance

Distance-measuring devices help with positioning, material flow control, and level detection. However, there are several options to consider when it comes to choosing the correct sensor technology to measure distance. Here I’ll cover the three most commonly used types in the industrial automation world today, including photoelectric, ultrasonic, and inductive.

Photoelectric sensors

Photoelectric sensors use a light source, such as a laser or light-emitting diode, to reflect the light off an object’s surface to calculate the distance between the face of the sensor and the object itself. The two basic principles for how the sensor calculates the distances are the time of flight (TOF) and triangulation.

    • Time of flight photoelectric distance measurement sensors derive the distance measurement based on the time it takes the light to travel from the sensor to the object and return. These sensors are used to measure over long distances, generally in the range between 500 millimeters and up to 5 meters, with a resolution between 1 to 5 millimeters, depending on the sensor specifications. Keep in mind that this sensor technology is also used in range-finding equipment with a much greater sensing range than traditional industrial automation sensors.

    • In the triangulation measurement sensor, the sensor housing, light source, and light reflection form a triangle. The distance measurement is based on the light reflection angle within its sensing range with high accuracy and resolution. These sensors have a much smaller distance measurement range that is limited to between 20 and 300 millimeters, depending on the sensor specifications.

The pros of using photoelectric distance measurement sensors are the range, accuracy, repeatability, options, and cost. The main con for using photoelectric sensors for distance measurement is that they are affected by dust and water, so it is not recommended to use them in a dirty environment. The object’s material, surface reflection, and color also affect its performance.

Photoelectric distance measurement sensors are used in part contouring, roll diameter measurement, the position of assemblies, thickness detection, and bin-level detection applications.

Ultrasonic sensors

Ultrasonic distance sensors work on a similar principle as photoelectric distance sensors but instead of emitting light, they emit sound waves that are too high for humans to hear, and they use the time of flight of reflecting sound wave to calculate the distance between the object and the sensor face. They are insensitive to the object’s material, color, and surface finish. They don’t require the object or target to be made of metal like inductive position sensors (see below). They can also detect transparent objects, such as clear bottles or different colored objects, that photoelectric sensors would have trouble with since not enough light would be reflected back to reliably determine the distance of an object. The ultrasonic sensors have a limited sensing range of approximately 8 meters.

A few things to keep in mind that negatively affect the ultrasonic sensor is when the object or target is made of sound-absorbing material, such as foam or fabric, where the object absorbs enough soundwave emitted from the sensor making the output unreliable. Also, the sensing field gets progressively larger the further away it gets from the sensing face, thus making the measurement inaccurate if there are multiple objects in the sensing field of the sensor or if the object has a contoured surface. However, there are sound-focusing attachments that are available to limit the sensing field at longer distances making the measurements more accurate.

Inductive sensors

Inductive distance measurement sensors work on the same principle as inductive proximity sensors, where a metal object penetrating the electromagnetic field will change its characteristics based on the object size, material, and distance away from the sensing face. The change of the electromagnetic field detected by the sensor is converted into a proportional output signal or distance measurement. They have a quick response time, high repeatability, and linearity, and they operate well in harsh environments as they are not affected by dust or water. The downside to using inductive distance sensors is that the object or target must be made of metal. They also have a relatively short measurement range that is limited to approximately 50 millimeters.

Several variables exist to consider when choosing the correct sensor technology for your application solution, such as color, material, finish, size, measurement range, and environment. Any one of these can have a negative effect on the performance or success of your solution, so you must take all of them into account.

On the Level: Selecting the Right Sensor for Level Detection

We’ve probably all experienced having the “pot boil over” or “run dry” at one time or another. The same is frequently true on a much larger scale with many industrial processes. These large events can prove costly whether running dry or overflowing, resulting in lost product, lost production time, damage to the tank, or even operator injury. And then there is the cleanup!

The fact is, many procedures require the operator to monitor the bin or tank level – especially on older equipment. This human factor is prone to fail due to inattention, distractions, and lack of proper training. With today’s employee turnover and the brain drain of retirements, we need to help the operators out.

Multiple solutions exist that can provide operators with sufficient warning of the tank and bin levels being either too low or too high. This article provides a framework and checklist to guide the selection of the best technology for a specific application.

What type of monitoring is necessary?

First, consider whether the application requires or would benefit from continuous monitoring, or is point-level monitoring all that is needed?

    • Point-level monitoring is the simplest. It is essentially sensing whether the product is present at specific detection point(s) in the tank or bin. If the goal is to avoid running dry or overflowing, monitoring the bin or tank point level may be all that is required. Point-level sensors typically are best if the product levels can be detected through the wall or inside the tank or bin itself. A number of sensors can prevent false readings with products that are viscous, leaving residue on the sensor, and even ignore foam.
    • Continuous-level monitoring detects levels along a range – from full to empty. This is required when the exact level of the product must be known, such as for batch mixing.

Checklist for sensor selection

The checklist below can help guide you to what should be the appropriate technologies to consider for your particular application. Frequently, more than one type of technology may work, given the media (or product) you’re detecting, so it may make sense to test more than one.

Checklist for sensor selection

Ultimately, the sensor(s) you select must reliably sense/detect the presence of the subject product (or media). Which solution is least costly is frequently a big consideration, but remember there can be a hefty cost associated with a sensor that gives a false reading to the operator or control system.

Choosing sensors for washdown or clean-in-place environments

For products that will be consumed or entered into the human body, further selection considerations may include sensors that must survive in washdown or clean-in-place environments without contaminating the product.

The encouraging news is that sensors exist for most applications to detect product levels reliably. The finesse is in selecting the best for a given application when multiple technologies can do the job.

Again, there may be some trial and error at play but this checklist should at least narrow the field and pointed you to the better solution/technology.

Reducing Assembly Line Mistakes With the Error Proofing Platform Station

About 18 months ago, one of the major automotive companies came to the Indicon Conference looking for a way to decrease mistakes on the assembly line. They found a solution in a concept named the Error Proofing Platform Station (EPP).

How it works

The EEP works by using a bar code reader, in this case a scanner, to verify that the correct parts are being used in the assembly process. The scanner connects to an RS232-to-digital-converter module, and from there to an IO-Link networking block which enables two-way communication of information with the PLC. IO-Link blocks can connect hundreds of devices, versus traditional blocks that can only connect eight to sixteen devices. This greatly simplifies the hardware, cabling and installation costs.

EEP station design

The overall design of this EPP station grabbed the automotive company’s attention for several reasons.  It is effective both in its simplicity as well as the small footprint that it takes up. The design of the components allows it to sit on the plant floor instead of having to be installed in a cabinet like previous designs. They especially liked the wiring design where a single cable goes from the IO-Link block at is managed by a single IP address back to the PLC. Should one of the devices fail, you simply replace a single cable or device and move on.

The old days of unwinding the cables and spending hours trying to decipher which cable goes to which device are gone.

The current roll-out has been at four separate plants with plans for 10 more in the next four years. Expansion of this innovation is being targeted toward the other major manufacturers.