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    • Aging equipment: According to one study, almost $65B worth of equipment in the U.S. is outdated, but still in production.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

Security in the World of the Industrial Internet of Things

The Industrial Internet of Things (IIoT) is becoming an indispensable part of the manufacturing industry, leading to real-time monitoring and an increase in overall equipment effectiveness (OEE) and productivity. Since the machines are being connected to the intranet and sometimes to the Internet for remote monitoring, this brings a set of challenges and security concerns for these now-connected devices.

 What causes security to be so different between OT and IT?

Operational Technology (OT) manufacturing equipment is meant to run 24/7. So, if a bug is found that requires a machine to be shut down for an update, that stop causes a loss in productivity. So, manufacturers can’t rely on updating operational equipment as frequently as their Information Technology (IT) counterparts.

Additionally, the approach of security for OT machines has largely been “security through obscurity.” If, for example, a machine is not connected to the network, then the only way to access the hardware is to access it physically.

Another reason is that OT equipment can have a working lifetime that spans decades, compared to the typical 2-5-year service life of IT equipment. And when you add new technology, the old OT equipment becomes almost impossible to update to the latest security patches without the effort and expense of upgrading the hardware. Since OT equipment is in operation for such a long time, it makes sense that OT security focuses on keeping equipment working continuously as designed, where IT is more focused on keeping data available and protected.

These different purposes makes it hard to implement the IT standard on OT infrastructure. But that being said, according to Gartner’s 80/20 rule-of-thumb, 80 percent of security issues faced in the OT environment are the same faced by IT, while 20 percent are domain specific on critical assets, people, or environment. With so many security issues in common, and so many practical differences, what is the best approach?

The solution

The difference in operation philosophy and goals between IT and OT systems makes it necessary to consider IIoT security when implementing the systems carefully. Typical blanket IT security systems can’t be applied to OT systems, like PLCs or other control architecture, because these systems do not have built-in security features like firewalls.

We need the benefits of IIoT, but how do we overcome the security concerns?

The best solution practiced by the manufacturing industry is to separate these systems: The control side is left to the existing network infrastructure, and IT-focused work like monitoring is carried out on a newly added infrastructure.

The benefit of this method is that the control side is again secured by the method it was designed for – “security by obscurity” – and the new monitoring infrastructure can take advantage of the faster developments and updates of the IT lifecycle. This way, the operations and information technology operations don’t interfere with each other.

Choosing Between M18 and Flatpack Proxes

Both M18s and flatpacks are inductive or proximity sensors that are widely used in mechanical engineering and industrial automation applications. Generally, they are similar in that they produce an electromagnetic field that reacts to a metal target when it approaches the sensor head. And the coil in both sensors is roughly the same size, so they have the same sensing range – between 5 to 8 millimeters. They also both work well in harsh environments, such as welding.

There are, however, some specific differences between the M18 and flatpack sensors that are worth consideration when setting up production.

M18

One benefit of the M18 sensor is that it’s adjustable. It has threads around it that allow you to adjust it up or down one millimeter every time you turn it 360 degrees. The M18 can take up a lot of space in a fixture, however. It has a standard length of around two inches long and, when you add a connector, it can be a problem when space is an issue.

Flatpack

A flatpack, on the other hand, has a more compact style and format while offering the same sensing range. The mounting of the flatpack provides a fixed distance so it offers less adjustability of the M18, but its small size delivers flexibility in installation and allows use in much tighter fixes and positions.

The flatpack also comes with a ceramic face and a welding cable, especially suited for harsh and demanding applications. You can also get it with a special glass composite protective face, a stainless-steel face, or a steel face with special coatings on it.

Each housing has its place, based on your detection application, of course. But having them both in your portfolio can expand your ability to solve your applications with sensor specificity.

Check out this previous blog for more information on inductive sensors and their unlimited uses in automation.

Maximize the Benefits of Open-Source Code in Manufacturing Software

The rise of many players in manufacturing automation, along with factories’ growing adoption of Industrial Internet of Things (IIoT) and automation solutions, present a suitable environment for open-source software. This software is a value-adding solution for manufacturers, regardless of their operation technology and management requirements, due to the customization, resiliency, scalability, accessibility, cost-effectiveness, and quality it allows.

Customization

Software developers who use open-source code provide software with a core code that establishes specific features and allows users to access it and make changes as necessary. The process is much like being able to complete an author’s writing prompt or change the end of a story. Unlike a closed system that locks users in, open-source allows them to adapt and modify the code to meet a particular need or application.

This add-on coding system provides endless customization. It enables communities (i.e., users) to add or remove features beneficial in an integration phase, such as features for user testing or to find the best solution for a machine.

Customization is also valuable regarding data visualizations; users can develop dashboards and visuals that best describe their operations. Suppose a sensor provides real-time condition monitoring data over a particular machine. In that case, it’s possible to customize the code supporting the software that gathers and processes the data for specific parameters or to calculate specific values.

Resiliency

Additionally, open-source code is resilient to change because it can be modified quickly. The ability to quickly add or remove features and adapt to cyber environments or specific applications also makes it volatile. Like exposure to pathogens can help strengthen an immune response to said pathogens, so can an open-source code be made stronger by its exposure to different environments and applications to be ready to face cybersecurity threats. Implementing an open code isn’t any less risky (cybersecurity-wise) than closed codes due to the testing and enhancements made by so many coders or programmers. However, it is up to the implementer to use the same rules that apply to other closed source software. The implementer must be aware of the code’s source and avoid code from non-reputable sources who could have modified it with negative intentions. Overall, the code is resilient, adaptable, and agile to adapt given a new environment.

Scalability

The add-on and customization aspects of open-source also allow the code to be highly scalable. This scalable implementation happens in two dimensions: adoption timeline and application-based. Both are important to guarantee user acceptance and that it meets the operation and application requirements. Regarding the adoption timeline, scalability allows modification of the software and code to meet users’ expectations. Open-sourced code enables the implementation of features for user testing and feedback. The ultimate solution will include multiple iterations to meet the users’ needs and fulfill operation expectations.

On the other hand, this code is scalable based on the application(s), such as working on different machines, multiples of the same machine with different purposes, or adding/dropping features for specific uses. Say, for example, there are three of the same machine (A, B, and C), but they are in different environments. Machine A is in an environment that is 28°F , B is at room temperature, and C is exposed to constant wash-down. In this case, the condition monitoring software defines the acceptable parameters for each scenario, avoiding false alarms from erroneous triggers. In this example, the base code is adapted to include specific features based on the application.

Accessibility

In general, cost-effective and high-quality open-source code is available online. There are additional resources such as free coding tutorials that don’t require any licenses as well. Moreover, when programmers update an open code, they must make the new version available again, ensuring that the code is accessible and up to date.

Cost-effectiveness and quality

Regarding cost-effectiveness, using community open-source code significantly reduces the cost of developing, integrating, and testing software built in-house. It also reduces the implementation time and makes for better production operations. Essentially, it is high-quality, reliable code created by trusted sources for multiple coders and users.

“The application drives the technology” mantra is at the heart of open-source software development—a model where source code is available for community members to use, modify, and share. IIoT enablers and providers in the manufacturing industry own a particular solution that is then available for manufacturers to adapt to their specific operational requirements. With the increasing adoption of data-collecting technologies, it is in manufacturers’ best interest to seek software providers who grant them the flexibility to adjust software solutions to meet their specific needs. Automation is a catalyst for data-driven operation and maintenance.

5 Manufacturing Trends to Consider as You Plan for 2022

It’s that time of year again where we all start to forget the current year (maybe that’s OK) and start thinking of plans for the next — strategy and budget season! 2022 is only a few weeks away!

I thought I’d share 5 insights I’ve had about 2022 that you might benefit from as you start planning for next year.

    1. Electric Vehicles

      The electric vehicles manufacturing market is receiving major investments, machine builders are building up expertise, and consumers are trending towards more electric vehicles. According to PEW research, 7% of US adults say they currently own a hybrid or electric vehicle, but 39% say the next time they purchase a vehicle they are at least somewhat likely to seriously consider electric. Traditional automotive won’t go away any time soon, but I see this as a growth generator.

    1. Automation in Agriculture & Food

      Automation in the agriculture, food, beverage and packaging markets is also growing strong with more demand for packaged goods and more SKUs than ever before. Urbanization and shortages in agriculture labor markets are driving investments in automation technologies in manufacturing and on the farm. Robotic agriculture startups seem to be growing faster than weeds and are providing real value for those who are struggling to get product from the field to the factory.

    1. Supply Chain Disruption

      Several economists have said the chip shortage will be with us well into 2023, and now I hear rumors of plastics or other materials having disruptions. Disruption might be the new normal for the short to mid-term. I flew out of LAX a few weeks ago and there were dozens of container ships parked outside the port. We are also seeing a major breakdown of our “over-land” logistics infrastructure. Investment in automation and labor for this market will be vital to a strong recovery. Plan for these things and be willing to have open and honest discussions with your vendors and your customers. Untruths might get you by in the short term but could permanently damage your business relationships for years.

    1. Real not Hyped Sustainability

      As Generation Z (18-24year old) workers increasingly enter our economy, they are pushing us to truly work towards sustainability much more than Millennials did before them. What this means is other markets that I see as growth opportunities are ones where we can have major impact on this, like mining, waste/recycling, and agriculture.

    1. Technology as an HR tool

      All manufacturers will be impacted by the skills-gap and labor shortage if you aren’t already. Part of your strategy for 2022 must include automation and robotics as part of your labor strategy. We need to consider how can we use automation and robotics to do our dull, dirty, dangerous jobs or how can we use automation and robotics to extend the careers of our long-term experienced workers. What disruptive technology could you be investing in to make a real difference in your work processes — 3D printing, machine vision, AR/VR, exoskeletons, drones, virtual twin, AI, predictive maintenance, condition monitoring, smart sensors? Pick something you will do different in 2022. You have to.

What do you see for 2022 that will have a major impact on our businesses?

5 Steps to Make Troubleshooting Less Troublesome

There’s an old, not so funny joke about troubleshooting electrical devices with a punch line that ends with “is it plugged in?”

The reality is that it is easy to overlook basic or simple issues, especially when troubleshooting mechanical, electrical or software problems isn’t part of your regular routine. But following the basic troubleshooting steps listed below can prevent much frustration and lost time. (To be suggestive, many of these steps can be applied to our everyday lives, not just at work.)

There is a scientific and philosophical rule known more commonly as Occam’s razor that states that entities should not be multiplied unnecessarily. In layman’s terms, the simplest explanation is usually the best one. Occam’s razor is often stated as an injunction not to make more assumptions than you absolutely need to. In other words, do not over complicate things. This is especially important when beginning the troubleshooting process.

Here are five general steps to consider when troubleshooting in manufacturing (and in general):

  1. Identify the problem
    • Take the time to understand the malfunction. Look at the problem from where you believe it starts, not necessarily from the end effect you may be witnessing. Sometimes what you observe is a symptom of the problem but not the problem itself. This is the first critical step and usually dramatically reduces the steps required to diagnose the culprit causing the problem. This may also require checking even the simplest things like whether you have power. (Sorry, couldn’t resist.)
  2. Establish a theory of probable cause
    • This is where Occam’s razor should come in. Start by considering the most obvious things first, whether it be a power supply, a sensor, a cable(s) or even a connector, (especially field attachables). Then work your way to the more complex if needed, from network wiring in networks like Ethernet/IP or Profinet, to network traffic or ladder code sequencing. You shouldn’t start examining the more complex until you have eliminated the most obvious. Sometimes a poor performing sensor cable can mimic code problems. Be sure to make a list so you can easily remember your thoughts and probable causes to prevent covering things twice; that is a huge time waster.
  3. Establish an action plan and execute the plan
    • Start testing probable cause theories to try to determine the actual cause or root cause of the problem. Remember to always consider what you understand as the problem and your theories, then start executing your testing from the simplest possible cause to the more complex (if needed). Be careful not to get distracted by issues you find along the way, like something unrelated you remembered you wanted to take care of but is not related to the current problem. (This is where your written list really comes in handy.) Start examining methodically, don’t jump around and don’t repeat steps you’ve already eliminated.
      Hints: Try swapping components when possible and see if the problem corrects itself. And check that someone didn’t change something recently from the original design. This can many times manifest itself as the proverbial “ghost in the machine” syndrome. Consider this process a ladder you are climbing from the simple lower steps to the higher more complex steps. Using this analogy, why climb higher if you don’t need too.
  4. Verify full system functionality
    • Once you have found what you think may be the problem and corrected it, be sure to validate the system after the repair or replacement and make sure it is functioning as it should. In some rare cases, one root cause can cause other problems or damage, so it is important to ensure the system is functioning as it should before returning it back to service. This may lead to some pushback because of the additional time needed, but it could take the system off-line again even longer if unresolved problems are overlooked.
  5. Document the process.
    • Finally, be sure to document what you found and maybe even how you found it in a log or service documentation system. This is especially important if the problem was caused by a part wearing out from normal wear, as it is likely to happen again. If you can categorize the problem, this will make it easier for you and other staff to detect and remedy if it arises again. You may want to consider reviewing your findings at intervals to see if there are possible improvements or changes, like routine maintenance or more reliable components, that could minimize these problems in the future.

Establishing a good process like this will help you more quickly troubleshoot your application or machine, and even help with home projects. Critical thinking like this helps eliminated wasted time, frustration and most importantly, unplanned down time.

 

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!

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).

Chain of Support: The Link to Performance During Emergencies

What businesses do in the face of adversity can expose what they are at their core. Adversity is like a catalyst to an otherwise stable state. It forces a reaction. In a chemical reaction, we can predict how a known catalyst will affect a known solution. However, companies are much more unpredictable.

As automation takes center stage in a world of decreased human to human contact and tighter labor budgets, it is critical to understand who your automation partners really are. Who are the humans behind the brands, and what processes do they have in place to respond to emergencies? In manufacturing, downtime, whether planned or not, must be minimized.

One thing we know for certain about adversity is it will happen. Know how your automation partners will respond to a problem. Have them explain their plan to you before the problem occurs. Them having a plan, and you being aware of it, minimizes the impact on production. You can’t wait until a situation occurs during third shift on a Friday to have the discussion.

Knowing the answers to key questions ahead of time can advert a crisis. Who do you call when you need a replacement part? Are they local? How quickly can they respond? If that first person isn’t available what is my next step? When can someone be available? Can they come on site or will they support remotely? How long will it take to get a replacement part? Do you offer assistance with deployment?

The answers to these questions make up the chain of support for a product. Frankly, these answers are the things that truly delineate automation companies. You can always count on innovative technologies to be released to address quality, conformance and efficiency, but you have to make sure there is a secure chain of support behind those technologies. Companies that can clearly explain what this looks like are the ones who will be around for the long haul. Afterall, it’s what we do in the face of adversity that defines who we are.

Workers Wanted: Building a Team to Thrive in Industry 4.0

Manufacturers enjoy talking about the new technologies available as we speed ahead to Industry 4.0. And while it is true (very true) that improved technologies and the increase in data those new technologies provide are drivers for success, it is only with the right people in place that business can thrive.

Over the next decade, 4.6 million manufacturing jobs will likely be needed, and 2.4 million are expected to go unfilled due to the skills gap. Moreover, according to a recent report, the lack of qualified talent could take a significant bite out of economic growth, potentially costing as much as $454 billion from manufacturing GDP in 2028 alone. (Source: Deloitte and The Manufacturing Institute)

But this isn’t a future problem. It is today’s problem and it is already negatively impacting the bottom line for many businesses. During the first quarter of 2019, more than 25% of manufacturers had to turn down new business opportunities due to a lack of workers, according to a report from the National Association of Manufacturers (NAM).

Manufacturers need to respond to this issue. NOW. We need to start by changing the perception of what it means to work in smart manufacturing. We need to show potential workers what is happening inside our plants and what a career in manufacturing can look like — good pay, clean facilities, challenging work and advancement opportunities.

We can start this by taking simple steps like participating in Manufacturing Day activities, opening our doors to the public and letting them see what we do. Show them how manufacturing has changed. Manufacturing Day is held the first Friday of October each year to help dispel common misconceptions about manufacturing in a coordinated effort and while it is growing, still not enough businesses are involved.

We can’t solve our labor problems in a day. We also need to embrace new talent pipelines, work with schools to encourage students receive the basic training needed to join our teams, create co-op and intern opportunities, invest in training, and adapt our culture to better appeal to the younger generations we need to join us.

Our younger generations are highly technical. They don’t know of a world without technology and automation. Their ability isn’t the issue.  We need to convince them that they can find success and rewarding careers in manufacturing and then help then gain the skills to become productive members of our teams.