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How IO-Link Sensors With Condition Monitoring Features Work With PLCs

As manufacturers continually look for ways to maximize productivity and eliminate waste, automation sensors are taking on a new role in the plant. Once, sensors were used only to provide detection or measurement data so the PLC could process it and run the machine. Today, sensors with IO-Link measure environmental conditions like temperature, humidity, ambient pressure, vibration, inclination, operating hours, and signal strength. By setting alarm thresholds, it’s possible to program the PLC to use the resulting condition monitoring data to keep machines running smoothly.

Real-time data for real-time response

A sensor with condition monitoring features allows a PLC to use real-time data with the same speed it uses a sensor’s primary process data. This typically requires setting an alarm threshold at the sensor and a response to those alarms at the PLC.

When a vibration threshold is set up on the sensor and vibration occurs, for example, the PLC can alert the machine operator to quickly check the area, or even stop the machine, to look for a product jam, incorrect part, or whatever may be causing the vibration. By reacting to the alarm immediately, workers can reduce product waste and scrap.

Inclination feedback can provide diagnostics in troubleshooting. Suppose a sensor gets bumped and no longer detects its target, for example. The inclination alarm set in the sensor will indicate after a certain degree of movement that the sensor will no longer detect the part. The inclination readout can also help realign the sensor to the correct position.

Detection of other environmental factors, including humidity and higher-than-normal internal temperatures, can also be set, providing feedback on issues such as the unwanted presence of water or the machine running hotter than normal. Knowing these things in real-time can stop the PLC from running, preventing the breakdown of other critical machine components, such as motors and gearboxes.

These alarm bits can come from the sensors individually or combined together inside the sensor. Simple logic, like OR and AND statements, can be set on the sensor in the case of vibration OR inclination OR temperature alarm OR humidity, output a discrete signal to pin 2 of the sensors. Then pin 2 can be fed back through the same sensor cable as a discrete alarm signal to the PLC. A single bit showing when an alarm occurs can alert the operator to look into the alarm condition before running the machine. Otherwise, a simple ladder rung can be added in the PLC to look at a single discrete alarm bit and put the machine into a safe mode if conditions require it.

In a way, the sensor monitors itself for environmental conditions and alerts the PLC when necessary. The PLC does not need to create extra logic to monitor the different variables.

Other critical data points, such as operating hours, boot cycle counters, and current and voltage consumption, can help establish a preventative and predictive maintenance schedule. These data sets are available internally on the sensors and can be read out to help develop maintenance schedules and cut down on surprise downtimes.

Beyond the immediate benefits of the data, it can be analyzed and trended over time to see the best use cases of each. Just as a PLC shouldn’t be monitoring each alarm condition individually, this data must not be gathered in the PLC, as there is typically only a limited amount of memory, and the job of the PLC is to control the machines.

This is where the IT world of high-level supervision of machines and processes comes into play. Part two of my blog will explore how to integrate this sensor data into the IT level for use alongside the PLC.

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Condition Monitoring & Predictive Maintenance: Addressing Key Topics in Packaging

A recent study by the Packaging Machinery Manufacturers Institute (PMMI) and Interact Analysis takes a close look at packaging industry interest and needs for Condition Monitoring and Predictive Maintenance. Customer feedback reveals interesting data on packaging process pain points and the types of machines and components which are best monitored, the data which should be gathered, current maintenance approaches, and the opportunity for a better way: Condition Monitoring and Predictive Maintenance.

What keeps customers awake at night?

The PMMI survey indicates that form, fill & seal machines are very critical to packaging processes and more likely to fail than many other machines. Also critical to the process and a common failure point are filling & dosing machines, and labeling machines.

These three categories of machines are in use in primary packaging and are often the key components in the production line; the downstream processes are usually less critical. They often process a lot of perishable products at high speeds, therefore, any downtime is a big problem for overall equipment effectiveness (OEE), quality, and profitability.

In terms of the components on these machines that are most likely to fail, the ones are pneumatic systems, gearboxes, motors/drives, and sensors.

How can customers reduce unplanned downtime and improve OEE?

Our data shows that the top customer issue is unplanned machine breakdowns, but many packaging firms use reactive or preventative maintenance approaches, which may not be effective for most failures. An ARC study found that only about 20% of failures are age-related. The 80% of failures that are non-age-related would likely not be addressed by reactive or preventative maintenance programs.

A better way to address these potential failures is to monitor the condition of critical machines and components. Condition monitoring can provide early detection of machine deterioration or impending failure and the data can be used for predictive maintenance. Many “smart sensors” can now measure vibration, temperature, humidity, pressure, flow, inclination, and many other attributes which may be helpful in notifying users of emerging problems. And some of these “smart sensors” can also “self-monitor” and help alert users to potential failures in the sensor itself.

What are packaging customers actually doing?

The good news is that the packaging industry is moving forward to find a better way and users understand that Condition Monitoring/Predictive Maintenance gives them the opportunity to prevent unplanned failures, reduce unplanned downtime, and improve OEE, quality and profitability. About 25% of customers have already implemented some sort of Condition Monitoring / Predictive Maintenance, while about 20% are piloting it and 30% plan to implement it. This means that 75% of customers are very interested in Condition Monitoring/Predictive Maintenance, by far the most interest in any technology discussed in the PMMI survey.

Where do you start?

    • Look for the machines which cause you the most frustration. PMMI identified form, fill & seal, filling & dosing, and labeling machines, but there are other machines, including bottling, cartoning, and case/tray handling, that could fail and cause production downtime or damaged product.
    • Consider where, when, and how equipment can fail. Look to your own experience, ask partners with similar machines or perhaps the equipment supplier to help you determine the most common failure points and modes.
    • Analyze which parts of the machine fail. Moving parts are usually the highest potential failure point. On packaging machines, these include motors, gearboxes, fans, pumps, bearings, conveyors, and shafts.
    • Consider what to measure. Vibration is common, and often assessed in combination with temperature and humidity. On some machines, pressure, flow, or amperage/voltage should be measured.
    • Determine the most appropriate maintenance program for each machine. Consider the costs/benefits of reactive, preventative, condition-based monitoring or predictive approaches. In some cases, it may be OK to let a non-critical, low-value asset “run-to-failure,” while in other cases it might be worth investing in Condition Monitoring or Predictive Maintenance to prevent a critical machine’s costly failure.
    • Start small by implementing condition monitoring on one or two machines, and then scaling up once you’ve learned what does and doesn’t work. Using a low-cost sensor, which can be easily integrated with existing controls architectures or added on externally, is also a great way to start.

Condition Monitoring and Predictive Maintenance offer packaging firms a “better way” to address key topics including machine downtime, failures, and OEE. Users can move from a reactive to a proactive maintenance approach by monitoring attributes such as vibration and temperature on critical machines and then analyzing the data. This will allow them to detect and predict potential failures before they become critical, and thereby, reduce unplanned downtime, improve OEE, and save money.

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Does Your Stamping Department Need a Checkup? Try a Die-Protection Risk Assessment

If you have ever walked through a stamping department at a metal forming facility, you have heard the rhythmic sound of the press stamping out parts, thump, thump. The stamping department is the heart manufacturing facility, and the noise you hear is the heartbeat of the plant. If it stops, the whole plant comes to a halt. With increasing demands for higher production rates, less downtime, and reduction in bad parts, stamping departments are under ever-increasing pressure to optimize the press department through die protection and error-proofing programs.

The die-protection risk assessment team

The first step in implementing or optimizing a die protection program is to perform a die-protection risk assessment. This is much like risk assessments conducted for safety applications, except they are done for each die set. To do this, build a team of people from various positions in the press department like tool makers, operators, and set-up teams.

Once this team is formed, they can help identify any incidents that could occur during the stamping operations for each die set and determine the likelihood and the severity of possible harm. With this information, they can identify which events have a higher risk/severity and determine what additional measures they should implement to prevent these incidents. An audit is possible even if there are already some die protection sensors in place to determine if there are more that should be added and verify the ones in place are appropriate and effective.

The top 4 die processes to check

The majority of quality and die protection problems occur in one of these three areas: material feed, material progression, and part- and slug-out detections. It’s important to monitor these areas carefully with various sensor technologies.

Material feed

Material feed is perhaps the most critical area to monitor. You need to ensure the material is in the press, in the correct location, and feeding properly before cycling the press. The material could be feeding as a steel blank, or it could come off a roll of steel. Several errors can prevent the material from advancing to the next stage or out of the press: the feed can slip, the stock material feeding in can buckle, or scrap can fail to drop and block the strip from advancing, to name a few. Inductive proximity sensors, which detect iron-based metals at short distances, are commonly used to check material feeds.

Material progression

Material progression is the next area to monitor. When using a progressive die, you will want to monitor the stripper to make sure it is functioning and the material is moving through the die properly. With a transfer die, you want to make sure the sheet of material is nesting correctly before cycling the press. Inductive proximity sensors are the most common sensor used in these applications, as well.

Here is an example of using two inductive proximity sensors to determine if the part is feeding properly or if there is a short or long feed. In this application, both proximity sensors must detect the edge of the metal. If the alignment is off by just a few millimeters, one sensor won’t detect the metal. You can use this information to prevent the press from cycling to the next step.

Short feed, long feed, perfect alignment

Part-out detection

The third critical area that stamping departments typically monitor is part-out detection, which makes sure the finished part has come out of the stamping

area after the cycle is complete. Cycling the press and closing the tooling on a formed part that failed to eject can result in a number of undesirable events, like blowing out an entire die section or sending metal shards flying into the room. Optical sensors are typically used to check for part-out, though the type of photoelectric needed depends on the situation. If the part consistently comes out of the press at the same position every time, a through-beam photo-eye would be a good choice. If the part is falling at different angles and locations, you might choose a non-safety rated light grid.

Slug-ejection detection

The last event to monitor is slug ejection. A slug is a piece of scrap metal punched out of the material. For example, if you needed to punch some holes in metal, the slug would be the center part that is knocked out. You need to verify that the scrap has exited the press before the next cycle. Sometimes the scrap will stick together and fail to exit the die with each stroke. Failure to make sure the scrap material leaves the die could affect product quality or cause significant damage to the press, die, or both. Various sensor types can ensure proper scrap ejection and prevent crashes. The picture below shows a die with inductive ring sensors mounted in it to detect slugs as they fall out of the die.

Just like it is important to get regular checkups at the doctor, performing regular die-protection assessments can help you make continuous improvements that can increase production rates and reduce downtime. Material feed, material progression, part-out and slug-out detection are the first steps to optimize, but you can expand your assessments to include areas like auxiliary equipment. You can also consider smart factory solutions like intelligent sensors, condition monitoring, and diagnostics over networks to give you more data for preventative maintenance or more advanced error-proofing. The key to a successful program is to assemble the right team, start with the critical areas listed above, and learn about new technologies and concepts that are becoming available to help you plan ways to improve your stamping processes.

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Condition Monitoring & Predictive Maintenance: Cost-Benefit Tradeoffs

In a previous blog post, we discussed the basics of the Potential-Failure (P-F) curve, which refers to the interval between the detection of a potential failure and occurrence of a functional failure. In this post we’ll discuss the cost-benefit tradeoffs of various maintenance approaches.

In general, the goal is to maximize the P-F interval, which is the time between the first symptoms of impending failure and the functional failure taking place. In other words, you want to become aware of an impending failure as soon as possible to allow more time for action. This, however, must be balanced with the cost of the methods of prevention, inspection, and detection.

There is a trade-off between the cost of systems to detect and predict the failures and how soon you might detect the condition. Generally, the earlier the detection/prediction, the more expensive it is. However, the longer it takes to detect an impending failure (i.e. the more the asset’s condition degrades), the more expensive it is to repair it.Every asset will have a unique trade-off between the cost of failure prevention (detection/prediction) and the cost of failure. This means some assets probably call for earlier detection methods that come with higher prevention costs like condition monitoring and analytics systems due to the high cost to repair (see the Prevention-1 and Repair-1 curves in the Cost-Failure/Time chart). And some assets may be better suited for more cost-efficient but delayed detection or even a “run-to-failure” model due to lower cost to repair (the Prevention-2 and Repair-2 curves in the Cost-Failure/Time chart).

 

There are four basic Maintenance approaches:

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Reactive

The Reactive approach has low or even no cost to implement but can result in a high repair/failure cost because no action is taken until the asset has reached a fault state. This approach might be appropriate when the cost of monitoring systems is very high compared to the cost of repairing or replacing the asset. As a general guideline, the Reactive approach is not a good strategy for any critical and/or high value assets due to their high cost of a failure.

Reactive approaches:

      • Offer no visibility
      • Fix only if it breaks – low overall equipment effectiveness (OEE)
      • High downtime
      • Uncertainty of failures

Preventative

The Preventative approach (maintenance at time-based intervals) may be appropriate when failures are age related and maintenance can be performed at regular intervals before anticipated failures occur. Two drawbacks to this approach are: 1) the cost and time of preventative maintenance can be high; and 2) studies show that only 18% of failures are age related (source: ARC Advisory Group). 82% of failures are “random” due to improper design/installation, operator error, quality issues, machine overuse, etc. This means that taking the Preventative approach may be spending time and money on unnecessary work, and it may not prevent expensive failures in critical or high value assets.

Preventative approaches:

      • Scheduled tune ups
      • Higher equipment longevity
      • Reduced downtime compared to reactive mode

Condition-Based

The Condition-Based approach attempts to address failures regardless of whether they are age-based or random. Assets are monitored for one or more potential failure indicators, such as vibration, temperature, current/voltage, pressure, etc. The data is often sent to a PLC, local HMI, special processor, or the cloud through an edge gateway. Predefined limits are set and alerts (alarm, operator message, maintenance/repair) are only sent when a limit is reached. This approach avoids unnecessary maintenance and can give warning before a failure occurs. Condition-based monitoring can be very cost-effective, though very sophisticated solutions can be expensive. It is a good solution when the cost of failure is medium or high and known indicators provide a reliable warning of impending failure.

Condition-based approaches:

      • Based on condition (PdM)
      • Enables predictive maintenance
      • Improves OEE, equipment longevity
      • Drastically reduces unplanned downtime

Predictive Analytics

Predictive Analytics is the most sophisticated approach and attempts to learn from machine performance to predict failures. It utilizes data gathered through Condition Monitoring, and then applies analysis or AI/Machine Learning to uncover patterns to predict failures before they occur. The hardware and software to implement Predictive Analytics can be expensive, and this method is best for high-value/critical assets and expensive potential failures.

Predictive Analytics approaches:

      • Based on patterns – stored information
      • Based on machine learning
      • Improves OEE, equipment longevity
      • Avoids downtime

Each user will need to evaluate the unique attributes of their assets and decide on the best approach and trade-offs of the cost of prevention (detection of potential failure) against the cost of repair/failure. In general, a Reactive approach is only best when the cost of failure is very low. Preventative maintenance may be appropriate when failures are clearly age-related. And advanced approaches such as Condition Based monitoring and Predictive Analytics are best when the cost of repair or failure is high.

Also note that technology providers are continually improving condition monitoring and predictive solutions. By lowering condition monitoring system costs and making them easier to set up and use,  users can cost-effectively move from Reactive or Preventative approaches to Condition-Based or Predictive approaches.

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Avoid Downtime in Metal Forming With Inductive & Photoelectric Sensors

Industrial sensor technology revolutionized how part placement and object detection are performed in metal forming applications. Inductive proximity sensors came into standard use in the industry in the 1960s as the first non-contact sensor that could detect ferrous and nonferrous metals. Photoelectric sensors detect objects at greater distances. Used together in a stamping environment, these sensors can decrease the possibility of missing material or incorrect placement that can result in a die crash and expensive downtime.

Inductive sensors

In an industrial die press, inductive sensors are placed on the bottom and top of the dies to detect the sheet metal for stamping. The small sensing range of inductive sensors allows operators to confirm that the sheet metal is correctly in place and aligned to ensure that the stamping process creates as little scrap as possible.

In addition, installing barrel-style proximity sensors so that their sensing face is flush with the die structure will confirm the creation of the proper shape. The sensors in place at the correct angles within the die will trigger when the die presses the sheet metal into place. The information these sensors gather within the press effectively make the process visible to operators. Inductive sensors can also detect the direction of scrap material as it is being removed and the movement of finished products.

Photoelectric sensors

Photoelectric sensors in metal forming have two main functions. The first function is part presence, such as confirming that only a single sheet of metal loads into the die, also known as double-blank detection. Doing this requires placing a distance-sensing photoelectric sensor at the entry-way to the die. By measuring the distance to the sheet metal, the sensor can detect the accidental entry of two or more sheets in the press. Running the press with multiple metal sheets can damage the die form and the sensors installed in the die, resulting in expensive downtime while repairing or replacing the damaged parts.

The second typical function of photoelectric sensors verifies the movement of the part out of the press. A photoelectric light grid in place just outside the exit of the press can confirm the movement of material out before the next sheet enters into the press. Additionally, an optical window in place where parts move out will count the parts as they drop into a dunnage bin. These automated verification steps help ensure that stamping processes can move at high speeds with high accuracy.

These examples offer a brief overview of the sensors you mostly commonly find in use in a die press. The exact sensors are specific to the presses and the processes in use by different manufacturers, and the technology the stamping industry uses is constantly changing as it advances. So, as with all industrial automation, selecting the most suitable sensor comes down to the requirements of the individual application.

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Reduce Packaging Downtime with Machine Vision

Packaging encompasses many different industries and typically has several stages in its process. Each industry uses packaging to accomplish specific tasks, well beyond just acting as a container for a product. The pharmaceutical industry for example, typically uses its packaging as a means of dispensing as well as containing. The food and beverage industry uses packaging as a means of preventing contamination and creating differentiation from similar products. Consumer goods typically require unique product containment methods and have a need for “eye-catching” differentiation.

The packaging process typically has several stages. For example, you have primary packaging where the product is first placed in a package, whether that is form-fill-seal bagging or bottle fill and capping. Then secondary packaging that the consumer may see on the shelf, like cereal boxes or display containers, and finally tertiary packaging or transport packaging where the primary or secondary packaging is put into shipping form. Each of these stages require verification or inspection to ensure the process is running properly, and products are properly packaged.

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Discrete vs. Vision-Based Error Proofing

With the use of machine vision technology, greater flexibility and more reliable operation of the packaging process can be achieved. Typically, in the past and still today, discrete sensors have been used to look for errors and manage product change-over detection. But with these simple discrete sensing solutions come limitations in flexibility, time consuming fixture change-overs and more potential for errors, costing thousands of dollars in lost product and production time. This can translate to more expensive and less competitively priced products on the store selves.

There are two ways implementing machine vision can have a benefit toward improving the scheduled line time. The first is reducing planned downtime by reducing product change over and fixturing change time. The other is to decrease unplanned downtime by catching errors right away and dynamically rejecting them or bringing attention to line issues requiring correction and preventing waste. The greatest benefit vision can have for production line time is in reducing the planned downtime for things like product changeovers. This is a repeatable benefit that can dramatically reduce operating costs and increase the planned runtime. The opportunities for vision to reduce unplanned downtime could include the elimination of line jams due to incorrectly fed packaging materials, misaligned packages or undetected open flaps on cartons. Others include improperly capped bottles causing jams or spills and improper adjustments or low ink causing illegible labeling and barcodes.

Cost and reliability of any technology that improves the packaging process should always be proportional to the benefit it provides. Vision technologies today, like smart cameras, offer the advantages of lower costs and simpler operation, especially compared to the older, more expensive and typically purpose-built vision system counterparts. These new vision technologies can also replace entire sensor arrays, and, in many cases, most of the fixturing at or even below the same costs, while providing significantly greater flexibility. They can greatly reduce or eliminate manual labor costs for inspection and enable automated changeovers. This reduces planned and unplanned downtime, providing longer actual runtime production with less waste during scheduled operation for greater product throughput.

Solve Today’s Packaging Challenges

Using machine vision in any stage of the packaging process can provide the flexibility to dramatically reduce planned downtime with a repeatable decrease in product changeover time, while also providing reliable and flexible error proofing that can significantly reduce unplanned downtime and waste with examples like in-line detection and rejection to eliminate jams and prevent product loss. This technology can also help reduce or eliminate product or shipment rejection by customers at delivery. In today’s competitive market with constant pressure to reduce operating costs, increase quality and minimize waste, look at your process today and see if machine vision can make that difference for your packaging process.

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RFID Minimizes Errors, Downtime During Format Change

Today’s consumer packaged goods (CPG) market is driving the need for greater agility and flexibility in packaging machinery. Shorter, more customized runs create more frequent machine changeover. Consequently, reducing planned and unplanned downtime at changeover is one of the key challenges CPG companies are working to improve.

In an earlier post, I discussed operator guided changeover for reducing time and errors associated with parts that must be repositioned during format change.

In this post, I will discuss how machine builders and end users are realizing the benefits of automated identification and validation of mechanical change parts.

In certain machines, there are parts that must be changed as part of a format change procedure. For example, cartoning machines could have 20-30 change parts that must be removed and replaced during this procedure.

This can be a time consuming and error-prone process. Operators can forget to change a part or install the wrong part, which causes downtime during the startup process while the error is located and corrected. In the worst scenarios, machines can crash if incorrect parts are left in the machine causing machine damage and significant additional downtime.

To prevent these mistakes, CPG companies have embraced RFID as a way to identify change parts and validate that the correct parts have been installed in the machine prior to startup. By doing so, these companies have reduced downtime that can be caused by mistakes. It has also helped them train new operators on changeover procedures as the risk of making a mistake is significantly reduced.

Selecting the correct system

When looking to add RFID for change part validation, the number of change parts that need to be identified and validated is a key consideration. RFID operating on the 13.56 MHz (HF) frequency has proven to be very reliable in these applications. The read range between a read head and tag is virtually guaranteed in a proper installation. However, a read head can read only a single tag, so an installation could need a high number of read heads on a machine with a lot of change parts.

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It is also possible to use the 900 MHz (UHF) frequency for change part ID. This allows a single head to read multiple tags at once. This can be more challenging to implement, as UHF is more susceptible to environmental factors when determining read range and guaranteeing consistent readability. With testing and planning, UHF has been successfully and reliably implemented on packaging machines.

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Available mounting space and environmental conditions should also be taken into consideration when selecting the correct devices. RFID readers and tags with enhanced IP ratings are available for washdown harsh environmental conditions. Additionally, there are a wide range of RFID read head and tag form factors and sizes to accommodate different sized machines and change parts.

 

 

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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!

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Project Uptime – Pay Me Now or Pay Me Later

Back when I worked in the tier 1 automotive industry we were always trying to find time to break into our production schedule to perform preventative maintenance. The idea for this task was to work on the assembly machines or weld cells to improve sensor position, sensor and cable protection and of course clean the machines. As you all know this is easier said than done due to unplanned downtime or production schedule changes, for example. As hard as it is to find time for PM’s (preventative maintenance) it is a must to stay ahead and on top of production. PM’s will not only increase the production time, but it will also help maintain better quality parts by producing less scrap and machine downtime due damaged sensors or cables.

If you have read any of my previous posts you have probably noticed that I refer to the “pay me now or pay me later” analogy. This subject would fall directly into this category, you have to take the time to prevent machine crashes and damaged sensors and cables on the front side rather than being reactive and repairing them when they go down. It has been proven that a properly bunkered or protected proximity sensor will outlast the machine tooling when best practices are executed. It’s important to take the time and look at the way a sensor is mounted or protected or acknowledge when a cable is routed in harm’s way.

Click to enlarge

PM’s should be an important task that is part of a schedule and followed through in any factory automation or tier 1 production facility. In some cases I have seen where there is a complete bill of material (BOM) or list of tasks to accomplish during the PM time. This list will help maintenance personnel and engineering know what to look for and what are the hot spots that create unplanned downtime.  This list could also indicate some key sensors, mounting brackets and high durability cables that can improve the process.

For more information on a full solution supplier or products that can improve and decrease downtime click here.

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3 Tips for Reducing Downtime

Whether it’s through preventative maintenance or during planned machine downtime, reducing downtime is a common goal for manufacturers. Difficult environments create challenges for not just machines, but also the components like sensors or cables. Below are three tips to help protect these components and reduce your downtime.

sacraficialcableCables don’t last forever. However, they are important for operations and keeping them functional is vital. An easy way to help reduce downtime and save money is by implementing a “sacrificial cable” in unforgiving environments. A sacrificial cable is any cable less than two meters in length and placed in situations where there is high turnover of cables.  This sacrificial cable does not have to be a specialty cable with a custom jacket. It can be a simple 1 meter PVC cable that will get changed out often. The idea is to place a sacrificial cable in a problematic area and connect it to a longer length cable, or a home-run cable. The benefits of this method include: less downtime for maintenance when changing out failures, reduced expenses since shorter cables are less expensive, and there is less travel for the cable around a cell.

hdc_cablesA second way to help reduce downtime is consider your application conditions up front. We discussed some of the application conditions to consider in a previous blog post, but how can we address these challenges? Not only is it important to choose the correct sensor for the environment, but remember, cables don’t last forever. Choosing the appropriate cable is also key to reducing downtime. Welding environments demand a cable that weld beads will not stick to and fuse the cable to the sensor. There are a variety of jacket types like silicone, silicone tube, or PTFE that prevent weld debris from accumulating on the cable. I’ve also seen applications where there is a lot of debris cutting through cables. In this case, a stainless steel braid cable would be a better solution than a traditional cable. Fitting the right protection to the right application is crucial..

gizmo4A third tip to help reduce your machine downtime is to simply add protection to your existing components. Adding protection, whether it is a protective bracket or a silicone product, will help keep components running longer. This type of protection can be added before or after the cell is operational.   One example of sensor protection is adding a ceramic cap to protect the face of a sensor. You can also protect the connection by adding tubing to the cable out version of the sensor to shield it from debris. Mounting sensors in a robust bracket helps protect the sensor from being hit, or having debris cover the sensor.  There are different degrees of changes that help prolong operations.

Metalforming expert, Dave Bird, explains some of these solutions in the video below. To learn more you can also visit our website at www.balluff.us.