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.

Using MicroSpot LEDs for Precise Evaluations in Life Science

Handling microfluidics and evaluating samples based on light is a precise science. And that precision comes from the light source, not the actual detection method. But too many times we see standard LEDs being used in these sensing and evaluation applications. Standard LEDs are typically developed for lighting and illumination applications and require too many ancillary components to achieve a minimum level of acceptability. Fortunately, there is an alternate technology.

First, let’s look at a standard LED. Figure 1 shows a typical red LED. You can see the light emission surface is cluttered with the anode pad (square in the middle) and its bond wire. These elements are fine for applications like long-range sensing, lighting and indications, but for precise, up-close applications they cause disturbances.

Figure 1: Typical red LED showing the intrusion of the anode and bond wire into the light emission

Most notable is the square hole in the middle of the emission pattern. There are two typical methods to reduce the effect of the hole: lensing and apertures. An aperture essentially restricts the emitted light to a corner of the die, substantially reducing the light energy causing difficulties with low-contrast detections. Using a lens only will maintain the light energy, but the beam will have a fixed focused point that is not acceptable for many applications. But even the bond wire produces reflections and causes spurious emissions. These cannot be tolerated with microfluidics as adjacent channels will become involved in the measurement. An additional aperture is typically used to suppress the spurious emissions.

Fortunately, there is an alternative with MicroSpot LEDs. Basically, the anode and emission areas are inverted as shown in the Figure 2 comparison.

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Figure 2: Comparison of the typical LED with the MicroSpot’s clean, powerful and collimated emission

This eliminates the need for the anode and bond wire to interfere with the emitted light. This produces a clean, powerful and collimated emission that will produce consistent results without additional components. This level of beam control is typically reserved for lasers. However, lasers also require more components, are much larger and cost more. The MicroSpot LED is the best choice for demanding life science applications.

Try the MicroSpot for yourself in select Balluff MICROmote miniature photoelectric sensors.

Learn more at www.balluff.com.

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.

Sensor and Device Connectivity Solutions For Collaborative Robots

Sensors and peripheral devices are a critical part of any robot system, including collaborative applications. A wide variety of sensors and devices are used on and around robots along with actuation and signaling devices. Integrating these and connecting them to the robot control system and network can present challenges due to multiple/long cables, slip rings, many terminations, high costs to connect, inflexible configurations and difficult troubleshooting. But device level protocols, such as IO-Link, provide simpler, cost-effective and “open” ways to connect these sensors to the control system.

Just as the human body requires eyes, ears, skin, nose and tongue to sense the environment around it so that action can be taken, a collaborative robot needs sensors to complete its programmed tasks. We’ve discussed the four modes of collaborative operation in previous blogs, detailing how each mode has special safety/sensing needs, but they have common needs to detect work material, fixtures, gripper position, force, quality and other aspects of the manufacturing process. This is where sensors come in.

Typical collaborative robot sensors include inductive, photoelectric, capacitive, vision, magnetic, safety and other types of sensors. These sensors help the robot detect the position, orientation, type of objects, and it’s own position, and move accurately and safely within its surroundings. Other devices around a robot include valves, RFID readers/writers, indicator lights, actuators, power supplies and more.

The table, below, considers the four collaborative modes and the use of different types of sensors in these modes:

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But how can users easily and cost-effectively connect this many sensors and devices to the robot control system? One solution is IO-Link. In the past, robot users would run cables from each sensor to the control system, resulting in long cable runs, wiring difficulties (cutting, stripping, terminating, labeling) and challenges with troubleshooting. IO-Link solves these issues through simple point-to-point wiring using off-the-shelf cables.

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Collaborative (and traditional) robot users face many challenges when connecting sensors and peripheral devices to their control systems. IO-Link addresses many of these issues and can offer significant benefits:

  • Reduced wiring through a single field network connection to hubs
  • Simple connectivity using off-the-shelf cables with plug connectors
  • Compatible will all major industrial Ethernet-based protocols
  • Easy tool change with Inductive Couplers
  • Advanced data/diagnostics
  • Parametarization of field devices
  • Faster/simpler troubleshooting
  • Support for implementation of IIoT/Industry 4.0 solutions

IO-Link: an excellent solution for simple, easy, fast and cost-effective device connection to collaborative robots.

Inductive Coupling: A Simple Solution for Replacing Slip Rings

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Figure 1: Inductive coupling for power and data exchange

In the industrial automation space, inductive sensors have grown very popular , most commonly used for detecting the proximity of metal objects such as food cans, or machine parts. Inductive coupling, also known as non-contact connectors, uses magnetic induction to transfer power and data over an air gap.

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Figure 2: Slip ring example

While inductive couplers have many uses, one of the most beneficial is for replacing a traditional slip-ring mechanism. Slip-rings, also known as rotary connectors, are typically used in areas of a machine where one part rotates, and another part of the machine remains stationary, such as a turn table where stations on the indexing table need power and I/O, but the table rotates a full 360°. This set up makes standard cable solutions ineffective.

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Figure 3: Inductive coupling replacing the slip-ring

A slip ring could be installed at the base of the table, but since they are electromechanical devices, they are subject to wear out. And unfortunately, the signs for wearing are not evident and often it is only a lack of power that alerts workers to an issue.

An inductive coupling solution eliminates all the hassle of the mechanical parts. With non-contact inductive coupling, the base of a coupler could be mounted at the base of the table and the remote end could be mounted on the rotating part of the table.

Additionally, slip rings are susceptible to noise and vibration, but because inductive couplers do not have contact between the base and the remote, they do not have this problem.

Inductive couplers are typically IP67-rated, meaning they are not affected by dirt or water, or  vibrations, and most importantly, they are contact free so no maintenance is necessary.

Learn more about Balluff inductive couplers www.balluff.us.

IO-Link reduces waste due to sensor failures

In the last two blogs we discussed about Lean operations and reducing waste as well as Selecting right sensors for the job and the environment that the sensor will be placed. Anytime a sensor fails and needs a replacement, it is a major cause of downtime or waste (in Lean philosophy). One of the key benefits of IO-Link technology is drastically reducing this unplanned downtime and replacing sensors with ease, especially when it comes to measurement sensors or complex smart sensors such as flow sensors, continuous position monitoring sensors, pressure sensors, laser sensors and so on.

When we think about analog measurement sensor replacement, there are multiple steps involved. First, finding the right sensor. Second, calibrating the sensor for the application and configuring its setpoints. And third, hope that the sensor is functioning correctly.

Most often, the calibration and setpoint configuration is a manual process and if the 5S processes are implemented properly, there is a good chance that the procedures are written down and accessible somewhere. The process itself may take some time to be carried out, which would hold up the production line causing undesired downtime. Often these mission critical sensors are in areas of the machine that are difficult to access, making replacing then, let alone configuring, a challenge.

IO-Link offers an inherent feature to solve this problem and eliminates the uncertainty that the sensor is functioning correctly. The very first benefit that comes with sensors enabled with IO-Link is that measurement or readings are in engineering units straight from the sensor including bar, psi, microns, mm, liters/min, and gallons/min. This eliminated the need for measurements to be scaled and adjusted in the programming to engineering units.

Secondly, IO-Link masters offer the ability to automatically reconfigure the sensors. Many manufacturers call this out as automatic device replacement (ADR) or parameter server functionality of the master. In a nutshell, when enabled on a specific port of the multi-port IO-Link master, the master port reads current configuration from the sensor and locks them in. From that time forward, any changes made directly on the sensor are automatically overwritten by these locked parameters. The locked parameters can be accessed and changed only through authorized users. When the time comes to replace the sensor, there is only one step that needs to happen: Find the replacement sensor of the same model and plug it in. That’s it!

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When the new sensor is plugged-in, the IO-Link master automatically detects that the replacement sensor does not have the correct parameters and automatically updates them on the sensor. Since the readings are directly in the units desired, there is no magic of scaling to fiddle with.

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It is also important to note, that in addition to the ADR feature, there may be parameters or settings on the sensors that alert you to possible near-future failure of the sensor. This lets you avoid unplanned downtime due to sensor failure. A good example would be a pressure sensor that sends an alert (event) message indicating that the ambient temperature is too high or a photo-eye alerting the re-emitted light value is down close to threshold – implying that either the lens is cloudy, or alignment is off.

To learn more about IO-Link check out our other blogs.

Environmental Impacts – Choosing the Right Sensor for the Conditions

Last week’s blog spoke about reducing waste and downtime by implementing LEAN manufacturing procedures. This involves taking a proactive approach to improving efficiencies. This post will focus on selecting the right part for the job to reduce failure rates that lead to avoidable machine downtime and increased costs.

Hardly a day passes by where we are not contacted by a desperate end-user or equipment manufacturer seeking assistance with a situation of sensors failing at an unacceptably high rate.  Once we get down to the root cause of the failures, in most cases it’s a situation where the sensors are being applied in a manner which all but guarantees premature failure.

Not all sensors are created equal.  Some are intentionally designed for light-duty applications where the emphasis is more on economic cost rather than the ability to survive in rough service conditions.  Other sensors are specifically designed to meet the challenges of specific application environments, and as a result may carry a higher initial price.

Some things to think about when choosing a sensor for a new application:

  • What kind of environmental conditions will the sensor be exposed to?  For example:
    • Very low or very high temperatures
    • Constant exposure to or immersion in liquid
    • Continuous vibration
    • Extreme shock
    • Disruptive electrical noise (hand-held radios, welding fields, etc.)
    • Chemical contamination
    • Physical abuse or impact
    • Abrasion
    • High pressure washdown procedures
    • Exposure to outdoor conditions of UV sunlight, rain, ice, temperature swings, and condensing humidity
  • Is it possible to relocate the sensor to move it away from the difficult condition?
  • Is the sensor technology the best choice given the kind of application environment that it must operate in?
  • Is there a way to protect the sensor from exposure to the worst of the damaging effects?

When you reach for a catalog or jump on the internet to look for a sensor, it’s a good practice to just stop a moment first and make a list of the environmental challenges that the sensor could face.  Then you will be prepared to make an appropriate selection that best meets your expected application conditions.

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Heavy metal parts being loaded into a welding cell can damage specialty nut detection sensors designed to stick through a hole in a part.  Plunger probes are a better solution.

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Unprotected and non-bunkered sensors in damage prone areas result in premature sensor failure.

The goal is to reduce waste. Why, then, are we adding waste?

Becoming LEAN continues to be a popular topic for most companies, and the goal is simple; focus on value-add activities and eliminate waste. Value-add activities are processes that support what the customer is willing to pay for, also known as your product or service. Waste is anything that gets in the way of this. When you really think about it, a business is nothing more than a string of processes, and if a process exists, there is a cost to that process. Period. Therefore, the ultimate goal should be to eliminate any process, or reduce the process waste, that does not add value to the customer.

Think of ordering a product from Amazon. As an Amazon Prime member, you order the product and like black magic, your product is magically delivered two days later. But it isn’t magic. The path to achieving guaranteed 2-Day delivery from Amazon didn’t happen overnight. Their process was examined, value-add activities maximized, wastes eliminated, and the customer is positively and directly affected by these actions. We should look at our processes and take the same approach.

If the rule of 80/20 applies (which it always does), this means 80% of your daily work is non-value add. Let’s think about that. Is the customer paying you to read this blog on company time? Is the customer paying you to update that special KPI that doesn’t affect them?

What would happen if you instead focused your efforts directly on what directly impacts the customer, which essentially boils down to our products and lead time? What if you question yourself every day about every task, “Is the customer going to benefit from this change?”

Again, 80% of the time, the customer does not benefit, so why are we continually adding waste and how do we stop? The answer is simple. Stop contributing to non-value-add tasks. Literally, stop! And if you can’t stop, then challenge yourself to reduce the total amount of non value-add tasks (ie. waste) from your process. Reduce the DOWNTIME on every project.

D – Defects. The goal is to eliminate defects and create a disturbance-free or defect-free environment.

O – Over Production. Don’t produce more than the customer requires. Think of a professional football game and all of the food being made to serve fans. Now think about the end of the game and how much food was leftover (i.e. over produced). If 1pc flow was implemented, over producing is kept in check.

W – Waiting. Imagine driving 10 hours to your destination, only to be stuck waiting in traffic for an additional 4 hours. What a waste!

N – Non-Utilized Talent. As a manager or supervisor, it is your duty and privilege to coach employees and tap into your teammates’ talent. Find their passion, coach them to follow their passion, and help them reach their goals. The world needs more do-ers and people executing their abilities to their fullest potential. Talent that is not tapped into is undoubtedly a waste.

T – Transportation. Analyze distance traveled, count how many steps from point A to point B and create a spaghetti diagram to map out the back and forth of a process. Reduce and eliminate accordingly.

I –  Inventory: Inventory gets lost, stolen, breaks, is outdated, etc. Getting to JIT (Just in Time) is the ultimate goal. This means your inventory arrives “just in time” when it is needed by the customer instead of sitting on a shelf.

M – Motion: An Olympic sprinter has perfect form. Any wasted motion does not add value to help him/her win the race. Reduce and eliminate unnecessary motion, twisting, turning, etc.

E – Excessive Processing: Reduce the total touches a product or item is handled, read, etc. Avoid rework!

Now that you are equipped to identify waste in your process, I challenge you to be a change agent in your department to focus on what the customer pays for and reduce or eliminate the tasks the customer does not pay for. It’s difficult and it’s trying, but it’s worth it!

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.

Tracking and Traceability in Mobility: A Step Towards IIoT

In today’s highly competitive automotive environment, it is becoming increasingly important for companies to drive out operating costs in order to ensure their plants maintain a healthy operating profit.

Improved operational efficiency in manufacturing is a goal of numerous measures. For example, in Tier 1 automotive parts manufacturing it is common place to have equipment that is designed to run numerous assemblies through one piece of capital equipment (Flexible Manufacturing). In order to accommodate multiple assemblies, different tooling is designed to be placed in this capital equipment. This reduces required plant floor real-estate and the costs normally required for unidimensional manufacturing equipment. However, with this flexibility new risks are introduced, such as running the machine with incorrect tooling which can cause increased scrap levels, incorrect assembly of parts and/or destruction/damage of expensive tooling, expedited freight, outsourcing costs, increased manpower, sorting and rework costs, and more.

Having operators manually enter recipes or tooling change information introduces the Human Error of Probability (HEP).  “The typical failure rates in businesses using common work practices range from 10 to 30 errors per hundred opportunities. The best performance possible in well managed workplaces using normal quality management methods are failure rates of 5 to 10 in every hundred opportunities.” (Sondalini)

Knowing the frequency of product change-over rates, you can quickly calculate the costs of these potential errors. One means of addressing this issue is to create Smart Tooling whereby RFID tags are affixed on the tooling and read/write antennas are mounted on the machinery and integrated into the control architecture of the capital equipment. The door to a scalable solution has now been opened in which each tool is assigned a unique ID or “license plate” identifying that specific tooling. Through proper integration of the capital equipment, the plant can now identify what tooling is in place at which OP station and may only run if the correct tooling is confirmed in place. In addition, one can then move toward predictive maintenance by placing process data onto the tag itself such as run time, parts produced, and tooling rework data. Collection and monitoring of this data moves the plant towards IIoT and predictive maintenance capabilities to inform key personnel when tooling is near end of life or re-work requirement thus contributing to improved OEE (Overall Equipment Effectiveness) rates.

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For more information on RFID, visit www.balluff.com.

*Source: Mike Sondalini, Managing Director, Lifetime Reliability Solutions, Article: Unearth the answers and solve the causes of human error in your company by understanding the hidden truths in human error rate tables