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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    • Aging equipment: According to one study, almost $65B worth of equipment in the U.S. is outdated, but still in production.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.

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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.

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IO-Link Boosts Plant Productivity

In my previous blog, Using Data to Drive Plant Productivity, I categorized reasons for downtime in the plant and also discussed how data from devices and sensors could be useful in boosting productivity on the plant floor. In this blog, I will focus on where this data is and how to access it. I also touched on the topic of standardizing interfaces to help boost productivity – I will discuss this topic in my future blog.

Sensor technology has made significant progress in last two decades. The traditional transistor technology that my generation learned about is long gone. Almost every sensor now has at least one microchip and possibly even MEMs chips that allow the sensor to know an abundance of data about itself and the environment it which it resides. When we use these ultra-talented sensors only for simple signal communication, to understand presence/absence of objects, or to get measurements in traditional analog values (0-20mA, 0-10V, +5/-5V and so on), we are doing disservice to these sensors as well as keeping our machines from progressing and competing at higher levels. It is almost like choking the throat of the sensor and not letting it speak up.

To elaborate on my point, let’s take following two examples: First, a pressure sensor that is communicating 4-20mA signal to indicate pressure value. Now, that sensor can not only read pressure value but, more than likely, it can also register the ambient temperatures and vibrations. Although, the sensor is capable of understanding these other parameters, there is no way for it to communicate that information to the higher level controller. Due to this lack of ambient information, we may not be able to prevent some eminent failures. This is because of the choice of communication technology we selected – i.e. analog signal communication.

For the second example, let us take a simple photoeye sensor that only communicates presence/absence through discrete input and 0/1 signal. This photoeye also understands its environment and other more critical information that is directly related to its functionality, such as information about its photoelectric lens. The sensor is capable of measuring the intensity of re-emitted light, because based on that light intensity it is determining presence or absence of objects. If the lens becomes cloudy or the alignment of the reflector changes, it directly impacts the remitted light intensity and leads to sensor failure. Due to the choice of digital communication, there is no way for the sensor to inform the higher level control of this situation and the operator only learns of it when the failure happens.

If  a data communication technology, such as IO-Link, was used in these scenarios instead of signal communication, we could unleash these sensors to provide useful information about themselves as well as about their environment. If we collect this data or set alerts in the sensor for the upper/lower limits on this type of information, the maintenance teams would know in advance about the possible failures and prevent these failures to avoid eminent downtime.

Collecting this data at appropriate frequencies could help build a more relevant database and demonstrate patterns for the next generation of machine learning and predictive maintenance initiatives. This would be data driven continuous improvement to prevent failures and boost productivity.

The information collected from sensors and devices – so called smart devices – not only helps end users of automation to boost their plant’s productivity, but also helps machine builders to better understand their own machine usage and behaviors. Increased knowledge improves the designs for the next generation of machines.

If we utilized these smart sensors and devices at our change points in the machine, it would help fully or partially automate the product change-overs. With IO-Link as a technology, these sensors can be reconfigured and re-purposed for different applications without needing different sensors or manual tunings.

IO-Link technology has a built in feature called “automatic parameterization” that helps reduce plant down-time when sensors need replaced. This feature stores IO-Link devices’ configuration on the master port as well as all the configuration is also persistent in the sensor. Replacement is as simple as connecting the new sensor of the same type, and the IO-Link master downloads all the parameters and  replacement is complete.

Let’s recap:

  1. IO-Link unleashes a sensor’s potential to provide information about its condition as well as the ambient conditions, enabling condition monitoring, predictive maintenance and machine learning.
  2. IO-Link offers remote configuration of devices, enabling quick and automated change overs on the production line for different batches, reducing change over times and boosting plant productivity.
  3. IO-Link’s automatic parameterization feature simplifies device replacement, reducing unplanned down-time.

Hope this helps boost productivity of your plant!

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Rise of the Robots: IO-Link Maximizes Utilization, Saves Time and Money

Manufacturers around the world are buying industrial robots at an incredible pace. In the April 2020 report from Tractia & Statista, “the global market for robots is expected to grow at a compound annual growth rate (CAGR) of around 26 percent to reach just under 210 billion US dollars by 2025.” But are we gaining everything we can to capitalize on this investment when the robots are applied? Robot utilization is a key metric for realizing return-on-investment (ROI). By adding smart devices on and around the robot, we can improve efficiencies, add flexibility, and expand visibility in our robot implementations. To maximize robot utilization and secure a real ROI there are key actions to follow beyond only enabling a robot; these are: embracing the open automation standard IO-Link, implementing smart grippers, and expanding end-effector application possibilities.

In this blog, I will discuss the benefits of implementing IO-Link. Future blog posts will concentrate on the other actions.

Why care about IO-Link?

First, a quick definition. IO-Link is an open standard (IEC 61131-9) that is more than ten years old and supported by close to 300 component suppliers in manufacturing, providing more than 70 automation technologies (figure 1). It works in a point-to-point architecture utilizing a central master with sub-devices that connect directly to the master, very similar to the way USB works in the PC environment. It was designed to be easy to integrate, simple to support, and fast to implement into manufacturing processes.

Figure 1 – The IO-Link consortium has close to 300 companies providing more than 70 automation technologies.

Using standard cordsets and 24Vdc power, IO-Link has been applied as a retrofit on current machines and designed into the newest robotic work cells. Available devices include pneumatic valve manifolds, grippers, smart sensors, I/O hubs, safety I/O, vacuum generators and more. Machine builders and equipment OEMs find that IO-Link saves them dramatically on engineering, building and the commissioning of new machines. Manufacturers find value in the flexibility and diagnostic capabilities of the devices, making it easier to troubleshoot problems and recover more quickly from downtime. With the ability to pre-program device parameters, troublesome complex-device setup can be automated, reducing new machine build times and reducing part replacement times during device failure on the production line.

Capture Data & Control Automation

Figure 2 – With IIoT-ready IO-Link sensors and masters, data can be captured without impacting the automation control.

The final point of value for robotic smart manufacturing is that IO-Link is set up to support applications for the Industrial Internet of Things (IIoT). IO-Link devices are IIoT ready, enabling Industry 4.0 projects and smart factory applications. This is important as predictive maintenance and big-data applications are only possible if we have the capabilities of collecting data from devices in, around and close to the production. As we look to gain more visibility into our processes, the ability to reach deep into your production systems will provide major new insights. By integrating IIoT-ready IO-Link devices into robotic automation applications, we can capture data for future analytics projects while not interrupting the control of the automation processes (figure 2).

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Make 2020 the Year of Smart Manufacturing

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As we near the end of 2019, it is time to start thinking of New Year’s resolutions. Mostly, these are personal — a promise to eat better, to work out, or save money. But the clean slate of a fresh year on the calendar is also a good time to reevaluate business practices and look at how we can improve on the work floor. And as we enter a new decade, one of the areas every manufacturer needs to be considering is smart manufacturing.

Smart manufacturing uses real-time data and technology to help you meet the changing demands and conditions in the factory and supply chain to meet customer needs. This accurate, yet seemingly vague, definition means that the implementation of smart manufacturing into the workplace can help you meet an array of issues that negatively impact efficiency and the bottom line.

Implementation of smart manufacturing can:

  • Reduce manufacturing costs
  • Permit higher machine availability
  • Boost overall equipment effectiveness
  • Improve asset utilization
  • Allow for traceability of products and parts
  • Enhance supply chain
  • Ease new technology integration
  • Improve product quality
  • Reduce scrap rates
  • Minimize die crashes
  • Decrease unplanned downtime

These are big claims, but all achievable with the modernization of our systems, which is long overdue for most. According to the latest polls, 4 out of 10 manufacturers have little to no visibility into the real-time status of their manufacturing processes and an even higher percentage are utilizing at least some equipment that is far past its intended lifespan.

Half of manufacturers only become aware of system issues only after a breakdown occurs. This is unacceptable in 2020. Much like we expect our personal vehicles to alert us to upcoming issues — think of your service engine light or oil-life indicator —we need insight into the operation and performance of our manufacturing equipment.

Of course, joining the next industrial revolution comes at a cost, but if we put a dollar value on downtime and evaluate the cost benefit of the expected outcomes, it is hard to argue with the figures.

While we don’t need the start of a new year to make major changes, the flipping of the calendar page can give us the push we need to evaluate where we are and where we want to be. So, what are you waiting for?

Define your vision – Determine what you want to accomplish. Be clear and concise in articulating what you want to accomplish.

Set an objective for 2020 – You don’t have to change everything at once. Growth can come slower. What can you accomplish in the coming year?

Identify tactics and projects – Break down your vision into bite-size goals and projects. Prioritize realistic goals and set deadlines.

Link to KPIs – Make sure your smart manufacturing goals tie to key performance indicators. Having measurable results demonstrates just how effective the changes are and how they are improving business overall.

Assign responsibility – Designate owners to each step of the process. Make it someone’s responsibility to implement, track and report on the efforts. If it is everyone’s job, then it is no one’s job.

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IO-Link — Enables Industry 4.0 and Reduces Costs

Where does IO-Link fit on the road to Industry 4.0 and smart manufacturing?

IO-Link is a major enabling force for Industry 4.0 & smart manufacturing. Motivations for flexible manufacturing, efficient production and visibility require that we have more diagnostics and data available for analysis and monitoring. Lot-size-one flexible manufacturing requires that sensors and field devices be able to adapt to a rapidly changing set of requirements. With the parameterization feature of IO-Link slave devices, we can now send new parameters for production to the sensor on a part by part basis if required. For example, you could change a color sensor’s settings from red to green to orange to grey and back to red if necessary, allowing for significantly more flexible production. With efficient production, IO-Link slaves provide detailed diagnostics and condition monitoring information, allowing for trending of data, prediction of failure modes, and, thus, eliminating most downtime as we can act on the prediction data in a controlled & planned way. Trending of information like the current output of a power supply can give us new insights into changes in the machine over time or provide visibility into why a failure occurred.  For example, if a power supply reported a two amp jump in output three weeks ago, we can now ask, “what changed in our equipment 3 weeks ago that caused that?” This level of visibility can help management make better decisions about equipment health and production requirements.

Has IO-Link been widely accepted? Is anything still holding back its implementation?

In the last year IO-Link has become widely accepted. Major automation players like Balluff, Rockwell Automation, Festo, Siemens, SMC, Turck, Banner, Schmalz, Beckhoff, IFM and more than 100 other companies are engaged, promoting and, most importantly, building an installed base of functional IO-Link applications. We have seen installations in almost every industry segment: automotive OEMs, automotive tier suppliers, food & dairy machinery, primary packaging machinery, secondary packaging machinery, conveying systems, automated welding equipment, robot dress packs, on end-effectors of robots, automated assembly stations, palletized assembly lines, steel mills, wood mills, tire presses and more. The biggest roadblock to IO-Link becoming even further expanded in the market is typically a lack of skillset to support automation in the factory or a wariness of IO-Link as “another industrial network.”

What is the latest trend in IO-Link technology?

One of the biggest trends we are seeing with IO-Link technology is the reduction of analog on the machine.  With analog signals there are many “gotchas” that can ruin a good sensor application: electrical noise on the line, poor grounding design, more wiring, expensive analog input cards, and extra integration work. Analog signals cause a lot of extra math that we don’t need or want to do, for example: a linear position measurement sensor is 205mm long with a 4-20mA output tied into a 16bit input card. How many bits are there per mm?  A controls engineer needs to do a lot of mental gymnastics to integrate this into their machine. With IO-Link and a standard sensor cable, the wiring and grounding issues are typically eliminated and since IO-Link sensors report their measurements in the engineering units of the device, the mathematic gymnastics are also eliminated.  In our example, the 205mm long linear position sensor reports 205mm in the PLC, simple, faster to integrate and usually a much better overall application cost.

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Why IO-Link is the Best Suited Technology for Smart Manufacturing

While fieldbus solutions utilize sensors and devices with networking ability, they come with limitations. IO-Link provides one standard device level communication that is smart in nature and network independent. That enables interoperability throughout the controls pyramid, making it the most suitable choice for smart manufacturing.

IO-Link offers a cost effective solution to the problems. Here is how:

  • IO-Link uses data communication rather than signal communication. That means the communication is digital with 24V signal with high resistance to the electrical noise signals.
  • IO-Link offers three different communication modes: Process communication, Diagnostic communication (also known as configuration or parameter communication), and Events.
    • Process communication offers the measurement data for which the device or sensor is primarily selected. This communication is cyclical and continuous in nature similar to discrete I/O or analog communication.
    • Diagnostic communication is a messaging (acyclic) communication that is used to set up configuration parameters, receive error codes and diagnostic messages.
    • Event communication is also acyclic in nature and is how the device informs the controller about some significant event that the sensor or that device experienced.
  • IO-Link is point-to-point communication, so the devices communicate to the IO-Link master module, which acts as a gateway to the fieldbus or network systems or even standard TCP/IP communication system. So, depending on the field-bus/network used, the IO-Link master may change but all the IO-Link devices enjoy the freedom from the choice of network. Power is part of the IO-Link communication, so it does not require separate power port/drop on the devices.
  • Every open IO-Link master port offers expansion possibilities for future integration. For example, you could host an IO-Link RFID device or a barcode reader for machine access control as a part of a traceability improvement program.

For more information, visit www.balluff.com/io-link.

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The Need for Data and System Interoperability in Smart Manufacturing

As technology advances at a faster pace and the world becomes flatter, manufacturing operations are generally focused on efficient production to maximize profitability for the organization. In the new era of industrial automation and smart manufacturing, organizations are turning to data generated on their plant floors to make sound decisions about production and process improvements.

Smart manufacturing improvements can be divided roughly into six different segments: Predictive Analytics, Track and Trace, Error Proofing, Predictive Maintenance, Ease of Troubleshooting, and Remote Monitoring.IOLink-SmartManufacturing_blog-01To implement any or all of these improvements requires interoperable systems that can communicate effectively and sensors and devices with the ability to provide the data required to achieve the manufacturer’s goals. For example, if the goal is to have error free change-overs between production cycles, then feedback systems that include identification of change parts, measurements for machine alignment changes, or even point of use indication for operators may be required.  Similarly, to implement predictive maintenance, systems require devices that provide alerts or information about their health or overall system health.

Traditional control system integration methods that rely heavily on discrete or analog (or both) modes of communication are limited to specific operations. For example, a 4-20mA measurement device would only communicate a signal between 4-20mA. When it goes beyond those limits there is a failure in communication, in the device or in the system. Identifying that failure requires manual intervention for debugging the problem and wastes precious time on the manufacturing floor.

The question then becomes, why not utilize only sensors and devices with networking ability such as a fieldbus node? This could solve the data and interoperability problems, but it isn’t an ideal solution:

  • Most fieldbuses do not integrate power and hence require devices to have separate power drops making the devices bulkier.
  • Multiple fieldbuses in the plant on different machines requires the devices to support multiple fieldbus/network protocols. This can be cost prohibitive, otherwise the manufacturer will need to stock all varieties of the same sensor.
  • Several of the commonly used fieldbuses have limitations on the number nodes you can add — in general 256 nodes is capacity for a subnet. Additional nodes requires new expensive switches and other hardware.

IOLink-SmartManufacturing_blog-02IO-Link provides one standard device level communication that is smart in nature and network independent, thus it enables interoperability throughout the controls pyramid making it the most suitable choice for smart manufacturing.

We will go over more specific details on why IO-Link is the best suited technology for smart manufacturing in next week’s blog.

 

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How do I justify an IIoT investment to my boss?

Many engineers and managers I meet with when presenting at conferences on Smart Manufacturing ask some version of the question: “How can we justify the extra cost of Industrial Internet of Things (IIoT)?” or “How do I convince management that we need an Industry 4.0 project?” This is absolutely a fair and tough question that needs to be answered; without buy-in from management and proper budget allocation, you can’t move forward. While an investment in IIoT can deliver major payoffs, the best justification really depends on your boss.

I have seen three strong arguments that can be adapted to a variety of management styles and motivations.

1) Showing a ROI through Reducing Downtime

“Show me the money!” I think everyone has a manager with this expectation. It may seem like a daunting task to calculate or capture this information, but by using a team, knowing your KPIs and applying anecdotal feedback, you can get a good initial picture of the ROI that an IIoT project will bring to the organization. Many people have shared with me that their initial project’s ROI has “funded the next project.” There is a really great article from MetalForming Magazine that discusses how exactly to do this with the tables and forms they used at ODM Tool & Manufacturing.

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2) Corporate Goals for Productivity and Utilization

We can be successful getting support for a project when we link corporate goals to project goals. Smart Industry publishes a research project each year that investigates trends in the manufacturing space in regards to digital transformation initiatives. This report cites that the three top benefits manufacturers are seeing are: improving worker productivity (3rd 2016), reducing costs (1st 2016) and optimizing asset utilization (2nd 2016). These goals are driving investments and showing actual results for manufacturers both large and small. However, the report also revealed that more than half of manufacturers cite workforce skills-gap issues as their largest roadblock and this is, I believe, why we saw improving worker productivity move to the top spot. We must bring efficiency and effectiveness to the people we have.

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3) Your Competitors are Investing in IIoT!

If you have a boss that worries about falling behind, this can be a motivating argument. Control Engineering recently published a study of manufacturers and how they are investing in IIoT technologies. The largest investments are coming with sensors, connectivity and data analytics. But what is most shocking is that on average IIoT budgets are $328,160, with 18% budgeting more than a half-million dollars. If you want to keep up with the rapid pace of change in the global market, an investment in IIoT is a requirement to remain competitive.

If you are looking for support and partnership on your IIoT projects, we are experienced at utilizing IO-Link, smart sensors and RFID to enable Industry 4.0 and Smart Manufacturing projects.