I recently discovered a production and downtime tracker that solves a problem I’ve encountered numerous times in my career. Often, I have been faced with a production line or machine that needs to improve performance, but there is no reliable data on how well it runs. The Leap Production Counter and Downtime Timer system can be set up in minutes, is affordable and comes with built in data collection software that starts storing time-stamped data immediately and can accessed immediately and used flexibly in a number of ways depending on the user’s needs. Communication is wireless and the system can run independent of other controls systems or be integrated if desired.
For a demonstration, see this video from my good friend, Scott Dalgleish, CEO of Phase IV Engineering, that makes the Leap line-up of wireless sensors:
https://www.youtube.com/watch?v=m6wqnARdBJY
The Problem
In the past, I’ve set up downtime tracking systems on production lines many times. I’ve set up logic in Programable Logic Controllers (PLCs), the computer brains of modern production equipment. I’ve set up communication networks to talk to the equipment and IT systems to capture the data from the events captured by PLC logic. I’ve set up data historians in server databases to log the data. I’ve built queries and reports from the historians to analyze what has happened so it can be shared with operators and management. It is all very doable, but it takes a lot of time, and often considerable money. Even in factories where I worked and controlled all the elements of the process myself, it could take anywhere from several hours up to several days or even weeks to get all the elements of the system for a line to start getting data I could use, depending on the equipment and tasks required.
If I’m consulting in a factory where I don’t have control, I may have to work with several departments (electricians, mechanics, programmers, IT, Logistics, etc.) to get the work done, and this may be low on the priority list of many of the resources I need. I once had a 10-week assignment to improve production on a line, and even though it was a plant priority, it still took 5 weeks to start collecting data from the most critical piece of equipment. I was forced to use paper logs with tick marks that were far from accurate to assess progress while waiting for precise data. Some plants I’ve visited simply don’t have the capability to implement, the budget to afford outside resources to do the work or have restrictions on modifications to equipment preventing any data collection from being added.
And then there is production equipment that has no PLC. Some equipment simply runs on electrical relays and there is no “brain” to tap for data. Just installing a photoeye or some kind of counter that can be accessed can be a major wiring effort and still not provide much useful data for meaningful analysis and insight.
In a pinch, the alternative for immediate data is to ask the operators to complete a paper or computer log of their stops. This alternative is better than nothing, but my experience is that the data from these types of manual tracking systems is usually far from accurate. Logging precise times of downtime is simply not top priority for the operators- they want to focus on running the line and fixing stop issues, not watching the clock. Operator logs can be a helpful addition for understanding causes and many downtime tracking systems count on that data to fill in the details that automated systems simply can’t know, but as a primary system, they tend to have a lot of inaccuracies. For many reasons, manual logs aren’t a sustainable solution.
The Leap Solution
So, how is the Leap Production Counter and Downtime Timer a better solution? First, it is simple and easy to install. A sensor module with a choice of a photoeye or proximity switch is placed at a location to sense the output of a production machine. The module counts and timestamps each time the sensor is blocked. If the sensor stops seeing products pass by, the production is assumed to be stopped. The attached module stores this information and periodically sends a wireless message to a gateway module, positioned in a location with Ethernet access for distributing the data wherever needed. The gateway has a built-in web server, so users can simply log in with a PC and see the collected data and further configure how data is treated. For example, automated alerts can be triggered that send a text message to key persons after a pre-determined amount of downtime. Several built in reports are available directly from the server. Data can be downloaded from the server and further analyzed using Microsoft Excel, where the fun can really begin. And that’s what can be set up out of the box in minutes with one sensor and one gateway.
The system can be expanded with additional sensors to monitor production, or any number of process conditions like temperature, pressure, vibration, humidity, flooding, or any number of other conditions desired. All data can go into the same gateway and just build on the system’s capabilities. Each new sensor is a simple addition that can be configured in a few minutes. For factories that want to go further, the data from the gateway can be managed in a on premises server, mapped to a variety of data historians, or stored in the cloud for remote access. There are many other ways that the system can be set up for flexibility in unique situations with cellar communication and other protocols. The common theme is that sensor modules are battery powered wireless units that are designed to last up to 10 years without changing batteries. The production counter unit typically comes with a AC adapter, using the battery as a backup.
As a single sensor for production counts and downtime, the initial Leap system provides the most important data that a performance improvement analyst needs. Once data is moved into Excel, numerous calculations can be done to view the data whatever way matches the reporting requirements. Since we know down time, we can easily determine up time or run time. If we know up the production count and how long the equipment was running, we can calculate actual production rate. And with every event time-stamped, we can count stops. With stops, we can calculate Mean Time to Repair (MTTR), or the average amount of time we were down. We can also calculate Mean Time Between Stops (MTBS) or what some may call Mean Time Between Failures (MTBF). Most production lines suffer from extensive numbers of minor stops, and having an accurate count every shift allows for the creation of management practices to track, address and reduce them.
Finally, this simple combination of data allows operations to calculate reliability, utilization, or OEE (whatever your company wants to call it, and calculated however your standard requires. For example, if you want to use time only, take run time divided by total time. If you want to exclude certain times- breaks, maintenance, or other unscheduled time, just deduct it. If you want to calculate based on production counts as a percentage of possible production, you can calculate it that way. All this comes from a time-stamped count and a few Excel formulas.
One metric that many people ignore that comes from this data is the concept of rate loss and rate gain. Most production is set to run at an ideal rate, but often equipment runs slower or faster than the ideal or established centerline rate. By comparing actual rate from recorded data to the planned rate, a rate loss or rate gain can be calculated. Why does this matter? A number of possible issues can emerge.
If there is a rate loss, there is likely something preventing the equipment from running as fast as it has at a point in the past when the rate was established, and investigation is required to determine if this is a simple set-up issue that can be adjusted, or something that requires maintenance or repair to restore to ideal condition. Either way, this is likely a loss that can be eliminated with just a little follow up. But what about rate gain? What’s wrong with running faster? Often operators will try to make up for downtime by running faster. In many situations this may be at a sacrifice to quality- it just depends on why the ideal rate was established where it was. Running too fast may also make the equipment more unstable and actually cause more stops, a self-defeating situation. In any case, monitoring rate manages the most critical centerline setting of the equipment, its rate.
When lines are more complex
For lines with multiple unit operations, it may be helpful to count production at each machine. Another help can be to count incoming components at the input side of units where parts enter into the equipment to be filled, combined, packed, or unitized. These counters and timers can then help in the evaluation of each individual unit as already described, but also allows for analysis of the interaction between units. For example, a downstream piece of equipment can stop and trigger a blocked condition on the upstream unit feeding it. Likewise, an upstream stop will starve a downstream piece of equipment. By importing the data from each into Excel or using scripts in a data historian, these situations can be identified and quantified. Often the goal of analyzing performance is to optimize the output of the constraint unit, usually the most complex transformation on the line, and usually the slowest by rate.
But there is a lot more analysis that can take place when collecting data from multiple unit operations. By comparing counts, scrap losses between units can be determined. For example, if an upstream unit sends 1000 units downstream, but the downstream unit only has 970 come in, there is a 3% loss between units. For lines with lots of scrap, tracking these losses can be very helpful.
Another typical situation that can be studied is the impact of balancing the rate of the unit operations in a line. Often, equipment is set to run as fast as it can, even if it doesn’t need to. Depending on its position on the line, the equipment may frequently stop by being blocked or starved, running fast just to either fill up the surge ahead of it or empty its infeed. Running faster than needed can add to unplanned minor stops as many stops are induced by restarts after a pause in production, impacting equipment that is more critical. Ideally, the line runs in balance, with the constraint out-paced slightly by the equipment before and after. Each line requires a specific strategy based on the requirements of each unit operation, but ongoing management requires monitoring rate of each component to keep the line in optimal performance. Many factories run different rates for different products, so managing rate to product-based centerlines can be a challenge. Tracking rates to ensure compliance with established centerlines is a valuable tool for daily management of an operation.
Performance data can be used in many different time frames to help with the operation. Giving operators and maintenance crews access to data allows them to make better on the fly decisions about how to address developing issues during the production shift. Supervisors can use data to develop hand-off information to the next shift and identify developing issues for the next team to be aware of. Direction setting meetings each day, or each week allow management and supervisors to determine plans to intervene with activities to improve areas that aren’t performing to standards. Longer term maintenance planning can look at trends and see when certain machines need repair. Capital equipment planning can use data to decide when certain units simply aren’t capable of delivering needed results and determine requirements of new equipment.
Going beyond production counts and downtime data
With more equipment monitored for stops and counts, it might make sense to zero in on equipment conditions that impact minor stops, failures, or quality. Temperatures, pressures, moisture, vibration, and/or motor currents are a few of the process conditions that might be beneficial to monitor and record. Often these can be set up with a monitoring system that simply sets an alarm at a level that can alert key people days or weeks before a failure occurs, allowing time for a planned intervention instead of an emergency repair of an unplanned breakdown.
With the Leap sensor system from Phase IV Engineering all this is possible, affordable and easy to implement. A factory can start small with a single sensor and expand to cover the entire factory, with each new sensor simple and easy to add.
So, if you work in a Continuous Improvement or Operational Excellence role at a factory, or maybe have a role in Operations or Maintenance and have been challenged to get data to make improvements, or you are leading a Lean/Six-Sigma Focused Improvement blitz effort, these simple sensors may be just what is needed to get the data needed to get started.
For IT professionals managing a controls and information systems infrastructure, the Leap sensor and gateway may give you an easy way to pull factory data into a process data historian. No need to bring electricians or PLC programmers into the mix. The Leap gateway can provide collected information in a variety of standard protocols to a diverse universe of data consuming devices and databases.
Often, in certain industries that are highly regulated, collecting information like this becomes almost impossible due to the amount of testing and validation paperwork needed to add sensors or code to an existing automation and controls system. Adding a “second network” of information sensors and software, completely independent of the regulated equipment controls can be a practical work-around to get information without impacting the security of the regulated controls network. Sometimes, a simple solution that doesn’t require help from another department that doesn’t have time to be helpful can be the only way to get information. Either way, the Leap Sensor solution can be the work-around to get needed data.
Finally, for all those Smart Factory or IoT consultants out there, here is a product that can be installed quickly and generate quick returns compared to other less flexible systems.
The beauty of the system is its simplicity, affordability and flexibility. It can’t do everything. It can’t determine why a piece of equipment went down- you need a more holistic solution for that, but that takes much more time and effort to implement. For most situations, the production count and downtime tracker is enough to understand how well a line is running and if improvements are making a difference.
For more information, check out the Phase IV Engineering website, or request information on your specific situation from them. You can also reach out to me personally via my LinkedIn profile with questions or comments. Or leave comments on this webpage.
Collecting and reporting data doesn’t have to be hard. Sometimes you just need an easier way.
