How Vibration Measurement Saves Manufacturers Time and Money

Vibration is all around us. We can feel it and we can hear it. Some vibrations we find pleasant, such as music that we like to listen to, and some vibrations we find unpleasant such as scratching fingernails across the chalkboard. Humans also can predict when something is about to fail or determine when something needs our attention based on the vibrations we can feel or hear in our surroundings. An example almost anyone can relate to is when you are driving or riding in a car and the tires are out of balance or are damaged. In addition to the audible noise, you can feel the vibration through the steering wheel and the chassis of the car. Frequency and amplitude of the vibration typically increase as you speed up, and often amplify your worry as well. This can push you to find the cause of the vibration and fix it.

This same principle can be used in a manufacturing plant environment, which is what makes monitoring vibration so important. Without it, machines break down and stop, costing you time, and money. We all know that one maintenance guru that has a special gift of being able to determine what is happening with a machine based on its vibration feedback, the one who can place his hand on a machine, or hear the machine speak to him, and determine what is wrong with it.

However, using this institutional knowledge isn’t full-proof and it can introduce additional variables in the mix; sometimes resulting in wasted parts, labor, unplanned machine downtime, loss of production, etc. And as tenured staff retires and is replaced with less experienced staff, it has become even more important to remove the human element from the equation and properly capture the data to determine the root cause of mechanical issues. But how? By equipping machines with a monitoring system, the machine can then continuously monitor itself. And when the variables exceed the preset acceptable thresholds, the machine can act based on predetermined actions set by the OEM manufacturer or the maintenance team.

There are many monitoring systems on the market today that vary in complexity and cost. More complex systems include sensors, cables, data acquisition cards, computers, analysis software, data base, cloud subscription, and paid service contracts to pinpoint exact condition of the equipment or asset that is being monitored. This type of system or service is very costly, and in most cases, it is cost prohibitive to be used on non-critical equipment or assets. However, there are lower cost solutions that may not be able to pinpoint what has failed but can tell you when something wrong with the machine that needs to be examined by the maintenance technician. Such devices can be easily integrated into an existing controls architecture and can provide continuous condition monitoring of the machine or asset. Practice of continuous condition monitoring of machines can save the company valuable time and money by reducing unscheduled machine downtime, eliminating wasted parts and time for unnecessary scheduled maintenance, improving total OEE (Overall Equipment Effectiveness) of the machine, and increasing production. This all leads to increased profits.

Because there are more and more solutions available in the market today, there are few things you need to consider when choosing the right solution for your application:

  • Overall cost of implementation – hardware, software, and any installation costs?
  • Is the solution proprietary? Hardware, software, or communications?
  • Is there an annual service contract(s)? Subscriptions?
  • Does the machine/asset require periodic or continuous monitoring?
  • Quality of data? Do you need to know the exact failure point or is knowing that the machine is operating outside of its specified parameters good enough?
  • Can the system be easily expanded for the future state?
  • Are there any additional features that can aid in analyzing the condition of the machine such as pressure, temperature, humidity?

Knowing what you need and want ahead of time will help you better choose the correct solution for your application without wasting money and time on unnecessary features and functions.

 

Continuous and Exacting Measurements Deliver New Levels of Quality Control

Quality control has always been a challenge. Going back centuries, the human eye was the only form of quality verification. Hundreds of years ago metal tools like calipers were introduced to allow for higher repeatability compared to the human eye. This method is very cumbersome and is only an approximation based off a sample of the production, potentially allowing faulty products to be used or shipped to the customer.

What is the best solution by today’s standards? By scanning the product at all times! Using continuous measurements reduces or even eliminates the production of faulty products and allows for consistent and repeatable production. This used to be an impossible task for small products, but with the invention of the laser and CMOS(Complementary Metal Oxide Semiconductor) imaging sensors, extremely small measurements can be achieved. How small? In an industrial environment, measuring 0.3 mm components with a resolution of 10 micrometers is absolutely attainable. Using special optics to spread the beam across a window will allow for 105 mm of measuring range and up to 2 meters distance between the transmitter (laser spread light) and receiver (CMOS sensor).

Traditionally these sensor systems have one or two analog outputs and have to be scaled in the control system to be usable. These values are repeatable and accurate once scaled but there has to be a better way. IO-Link to the rescue!

IO-Link brings an enormous amount of information and flexibility to configuration. Using IO-Link will also reduce the amount of wiring and analog input cards/hubs required. The serial communications of IO-Link also reduce overall costs thanks to its use of standard cables, as opposed to shielded cables. This allows for 20 meter runs over a standard double ended M12 cables without information loss or noise injection. Another benefit to going with IO-Link is the drastic increase in bits of resolution. Analog input cards and analog input hubs tend to provide between 10-16 bits of resolution, whereas IO-Link has the ability to pass two measurements via process data in the form of dual 32 bit resolution arrays as well as more information about the status of the sensors.

With IO-Link, you also gain the ability to use system commands like restarting the device, factory reset, signal normalization, reset maintenance interval, and device discovery. With this level of technology and resolution, quality control can be taken to down to the finest details.

Turning Big Data into Actionable Data

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

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

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

Does the prospective vendor have:

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

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

Be Driven by Data and Decrease Downtime

Being “driven by data” is simply the act of making decisions based on real data instead of guessing or basing them on theoretical outcomes. Why one should do that, especially in manufacturing operations, is obvious. How it is done is not always so clear.

Here is how you can use a sensor, indicator light, and RFID to provide feedback that drives overall quality and efficiency.

 

Machine Condition Monitoring

You’ve heard the saying, “if it ain’t broke, don’t fix it.” However, broken machines cause downtime. What if there was a way to know when a machine is getting ready to fail, and you could fix it before it caused downtime? You can do that now!

The two main types of data measured in manufacturing applications are temperature and vibration. A sudden or gradual increase in either of these is typically an indicator that something is going wrong. Just having access to that data won’t stop the machine from failing, though. Combined with an indicator light and RFID, the sensor can provide real-time feedback to the operator, and the event can be documented on the RFID tag. The machine can then be adjusted or repaired during a planned maintenance period.

Managing Quality – A machine on its way to failure can produce parts that don’t meet quality standards. Fixing the problem before it affects production prevents scrap and rework and ensures the customer is getting a product with the quality they expect.

Managing Efficiency– Unplanned downtime costs thousands of dollars per minute in some industries. The time and resources required to deal with a failed machine far exceed the cost of the entire system designed to produce an early warning, provide indication, and document the event.

Quality and efficiency are the difference makers in manufacturing. That is, whoever makes the highest quality products most efficiently usually has the most profitable and sustainable business. Again, why is obvious, but how is the challenge. Hopefully, you can use the above data to make higher quality products more efficiently.

 

More to come! Here are the data-driven topics I will cover in my next blogs:

  • Part inspection and data collection for work in process
  • Using data to manage molds, dies, and machine tools

Realize Productivity Gains with Smart Robotic Tooling

In my last blog post, I shared how implementing IO-Link can expand visibility into your robot implementations and secure a high ROI. In this blog, I will share how you can better capitalize on your robot utilization and gain productivity with pneumatic and electric smart grippers.

Using Pneumatic & Electric Smart Grippers

Figure 1 – Sensors used in grippers provide position and open/closed feedback of the jaw. Photo courtesy of Balluff Worldwide.

In traditional pneumatic gripper applications, sensors are often not utilized. Proper function is assumed, i.e., the jaw opened and closed properly based on the signal sent to the air valve. This can cause unnecessary collisions or process failures due to stuck/worn mechanical components, leaks in the pneumatic lines, or small variations in the process cycle. Adding sensors to the grippers (Figure 1), creates a closed loop and minimal discrete feedback, like open or closed jaw, is provided. With the addition of smart sensors, we can monitor exact gripper jaw position and provide application diagnostics improving the capabilities of the robot end-effector. And finally, gripper intelligence features are expanded even further with electric grippers, giving precise control over the motion profile of the tool and providing detailed condition data on the equipment.

Regularly for smart sensors and smart grippers, these commands and the data are handled via IO-Link communication, which allows for process data, parameter data, and event data to be shared with the PLC and monitored via the Industrial Internet of Things (IIoT) connections. By utilizing IO-Link, both electric and pneumatic grippers can be enabled with intelligence to improve robot implementations.

Part Quality, Inspection, Delicate Part Handling & Measurement

Some of the most common applications like bin-picking, part stacking, or blank de-stacking make assumptions about the part being handled. But the first assumption many people make is that the robot is holding a part. Without sensor verification that the part is in place, how can it be guaranteed that the process is running without defect? And a second assumption that the correct part was loaded into the machine by the operator can cause hundreds of part defects if continued without verification. It is vital that the right part is loaded into the equipment every time, and as many parts look very similar manual inspection isn’t always accurate.  A gripper is an excellent place to gauge and inspect parts as it is physically touching the part. This is done by utilizing an analog position measurement sensor to determine the distance change of the gripper jaw. In addition to this, the position measurement sensor also can provide feedback for tactile gripping applications when handling delicate or precise parts. By utilizing position sensing for inspection and handling of the part, we can improve part quality and reduce production defects.

Production Flexibility, Format Change & Part Identification

In addition to quality inspection, by measuring the part, we can identify the part and make automation changes on-the-fly based upon this information, creating much higher levels of flexibility and making it possible for in-process format change. With one piece of equipment and the utilization of smart sensors on pneumatic grippers or smart electric grippers, more product can be produced. With higher efficiencies manufacturers can realize significant productivity gains.

Figure 2 – GEH6060IL-03-B servo electric gripper with delicate or elastic parts. Photo courtesy of Zimmer Group US, Inc.

In my next blog, I will discuss how expanding the use of end-effectors adds flexibility and are now easier than ever to include in your robotic applications.

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.

Eliminating Manufacturing Errors Begins with Identifying Trouble Spots

We have all gotten that dreaded phone call or email…the customer received their order, but there was a significant problem:

  • ErrorProofingTagsMissing part
  • Wrong color
  • Leaking seal
  • Improper assembly
  • Too lose…or too tight
  • Incomplete processing, e.g. missing threads
  • Something is damaged
  • Missing fluids or fluids at wrong level
  • …and so on

Assuming that we have reliable suppliers delivering quality parts that meet the required specifications…everything else that can (and often does) go wrong happens inside our own facilities. That means that solving the issues is our responsibility, but it also means that the solutions are completely under our control.

During the initial quality response meetings, at some point the subjects of “better worker training” and “more attention to detail and self-inspection” may come up. They are valid subjects that need to be addressed, but let’s face it: not every manufacturing and assembly problem can be solved by increased worker vigilance and dedication to workmanship. Nor, for that matter, is there the luxury of time or capacity for each worker to spend the extra time needed to ensure zero defects through inspection.

It is often more effective to eliminate errors at their source before they occur, so that further human intervention isn’t required or expected.

Some things to look for when searching for manufacturing trouble spots:

  • Are all fasteners present and properly tightened, in the proper torque sequence
  • Correct machine setup: is the right tool or fixture in place for the product being produced?
  • Manual data entry: does the process rely on human accuracy to input machine or product data?
  • Incorrect part: is it simply too hard to determine small differences by visual means alone?
  • Sequencing error: were the parts correct but came together in the wrong sequence?
  • Mislabeled component: would the operator realize that part is wrong if it was labeled incorrectly in the first place? Sometimes where the error has impact and where it actually occurred are in two different places.
  • Part not seated correctly: is everything is correct, but sometimes the part doesn’t sit properly in the assembly fixture?
  • Critical fluids: is the right fluid installed? Is it filled to the proper level?

Once the trouble spots have been identified, the next step is to implement a detection and/or prevention strategy. More information on the error proofing process is available on the Balluff website at www.balluff.us/errorproofing