JR Machine Makes More Informed Business Decisions Through Machine-Monitoring Data
JR Machine compares machine run hours to employee payroll hours to create a productivity index that enables it to make more informed decisions about a variety of aspects of its business.
An increasing number of shops are performing machine tool monitoring in some way. It isn’t uncommon to encounter large, flat-screen monitors in shops that display machines’ operational status in the form of bar graphs containing areas of green, yellow, red and black. In general, the more uninterrupted green, the better, because green time is chip-making time.
Such a monitor is found in JR Machine’s facility in Shawano, Wisconsin, enabling everyone on the shop floor to see, at a glance, the shop’s performance in real time. Plus, that information is accessible to managers via their computers, smartphones or tablet devices through the machine-monitoring software the shop uses. That way, they can remotely check in on a machine’s status at any given moment and receive alerts when a machine shuts down or an alarm is triggered.
Turning centers with sub-spindles for backworking enable parts to be machined complete. These machines have bar feeders and parts conveyors to enable long stretches of unattended operation or "green" time, too.
JR Machine uses the machine data it collects to develop a monthly productivity index: a ratio of machine green hours to the payroll hours of the person tending the machine. In essence, this metric demonstrates how well the shop uses its payroll hours compared to its machine hours.
This helps shape a number of key business decisions, such as what type of equipment the shop should buy (or sell), what job might be better suited for a machine with more automated capabilities, what job seems to require too much operator intervention, what type of work the shop should go after, what type of work it should avoid, if its effective billing rate is appropriate, if it needs to pursue additional business and so on.
Ultimately, it reveals true shop costs and profit.
This metric is also shared with all employees, but it’s not done with the intent to browbeat them when the index for their machine(s) isn’t optimal, Parker Tumanic, the contract machine's vice president, says. In fact, the transparency of sharing this with employees serves to motivate them to look for ways to boost the throughput of jobs (thereby reducing the green time for those jobs) so other jobs in queue can be processed sooner.
Why do they do that? It’s because they know that higher company profits mean the chance for higher take-home pay, thanks to the shop’s quarterly employee gain sharing bonus.
This monitor near the entrance to the shop floor displays the status and run history of all 20 machines in the shop. The server used for collecting the machine-monitoring data is separate from the shop’s main server. That way, data collection isn’t interrupted if the main server is down. Plus, this dedicated data server has battery backup, so data collection can resume right away if the power was to go out, without needing to be rebooted.
Machine, Production Index Monitoring
Parker Tumanic says the shop also values the data-collection software compatible with its common machine tool platforms, which facilitates calculating its productivity index, something it began tracking in 2015.
This starts with determining how much the machines are running over a given period, when they’re not producing because of part loading, when they are down for maintenance and so on. This data is automatically collected via DMG MORI Messenger data-collection software.
The collected machine data then is imported into a spreadsheet Mr. Tumanic developed to calculate the monthly productivity index. This index is simply a ratio of a machine’s run hours to its operator’s payroll hours. “We never had an effective way to measure how many payroll hours were tied to machine hours,” he says. “Our productivity index enables us to easily see the connection.”
The table below shows an example of this monthly report from 2015. At that time, the ratio of machine hours to payroll hours was low, with a four-month span ranging from 0.57 to 0.88. This spurred the shop to review the daily performance of individual machines to see why some had more green time than others. This in turn enabled JR Machine to direct low-hanging-fruit-type improvement efforts.
Shop managers can use the Messenger software to view the run history of individual machines, such as this NLX 2500 turning center, to get more detailed information about the machine’s activity. This type of information can be accessed remotely via smartphone, tablets or computers with internet access.
In some cases, large gaps between green time were due to manual machine loading. This is one reason why the shop purchased its first two sub-spindle lathes with bar feeders and parts conveyors to enable long stretches of unattended operation. Integrating these machines had an immediate impact for certain higher-volume jobs that could be processed from 3-inch-diameter bar stock or less, which is the capacity of the machines’ sub-spindles. In one case, a job ran over an entire weekend, only requiring an operator to come in two hours each day to check on the two machines, resulting in a productivity index of approximately 10.
The machine-monitoring data is imported into a spreadsheet to calculate the monthly productivity index for the entire shop. The productivity index compares the number of machine run hours to payroll hours. This ratio was low when the shop started collecting this data in 2015, but now typically ranges from 1.2 to 1.4 thanks to automating some processes and reducing cycle times by modifying programs and using new cutting tool technology. The addition of new equipment and other process improvements has pushed monthly machine hours over 5,000 today.
“Adding an automated process such as this to gain uninterrupted green time sounds like common sense, but when you’re encountering a flat-screen monitor each day that shows all this data, you become more apt to do something about the yellow interruptions,” Mr. Tumanic says. “It spurs you to make changes to minimize the gaps in machine uptime.”
Examining the index also served to balance cells. The turning centers in the shop are located in one aisle with identical machines facing each other, so one operator can more easily tend both machines. In fact, each time the shop purchases new turning centers, it purchases two at a time for that reason. For the cells with chucker turning centers running one part number, one turning center performs machining on side A of the part, and the other machines side B. By closely looking at the amount of interrupted production for each side due to part loading, the shop was able to better balance the cells. For example, if the cycle time for side A is 10 minutes and side B is 5 minutes, the shop might work to improve the performance of machine A; take features produced on machine A and have machine B produce them; set up both machines to run side A and then once completed, set up both to run side B; or, if the volume was sufficiently high, set up four machines with one pair machining side A and the other pair machining side B (each cell would start and end at a different time).
Badger Mill Supply Corp. in Oshkosh, Wisconsin, manages the shop’s SupplyPro tool vending system that Parker Tumanic shows here. This system tracks tool cost to job number, because simply tracking average tool cost isn’t terribly valuable.
The productivity index also helps determine what equipment to jettison. The indices for two of the shop’s current turning centers have been low. The problem isn’t that there are issues with programming, tooling or the machining process in general. Instead, it was determined that they aren’t capable of machining the type of complex parts the shop was and is pursuing. There simply hasn’t been enough work to feed them. As a result, these machines will soon be sold and replaced with better-suited equipment.
In reviewing the productivity index for specific machines, the shop asks itself a few questions when that value is low. Is there a process or programming issue? Were there machine alarms, and, if so, why? Are there enough sales for this machine, and does the machine match our core competency? Do the employees have all the hand tools, gages and related equipment they need to effectively run that particular job?
Typically, the result of identifying solutions to those types of issues shrinks the gaps in green time. However, the shop also looks to shrink the overall amount of green time for a job by spurring its machinists to try different cutting tools and/or make tweaks to part programs to reduce cycle times and, in turn, increase the effective billing rate for that machine and profit for those jobs because the machine is being utilized more effectively. This also enables jobs in queue to be completed sooner and/or spurs the shop’s sales department to pursue additional work.
The 4,000-Hour Challenge
Reducing overall green time is an ongoing effort at JR Machine. It was especially important in 2017, because the company’s backlog forced it to run 24/7 with two 12-hour shifts. In an effort to get away from that, the shop challenged its employees to reduce green time by 4,000 hours that year (which effectively equates to the cost to purchase one new machine). As of last December, it had shaved 3,628 hours with changes such as reduced setup time, as well as part program adjustments and new tooling to increase feed rates and reduce cycle times.
“With our company’s previous culture, employees spurred to help save 4,000 hours of green time might have led them to believe they were essentially working themselves out of a job,” Mr. Tumanic notes. “Now, employees know that saving 4,000 hours so we can complete more jobs in the same time frame means they’ll be paid a higher quarterly bonus.”
What Fun Would Stopping Be?
Today, JR Machine’s productivity index typically ranges from 1.2 to 1.4. Mr. Tumanic says this speaks to the value of having data that accurately depicts the rate of production on the shop floor in order to make sound, overall business decisions for the company.
JR Machine is also considering adding machine-loading robots between pairs of turning centers. In theory, this might make it possible for one machinist to tend four machines, resulting in four machine hours per one payroll hour. The operators are on board, because this, too, would result in higher quarterly bonuses.
“We’re a private company that’s profitable,” Mr. Tumanic notes. “We could easily shut down our improvement efforts based on tracking our productivity index and ride it out. However, it has become fun tracking the index and identifying ways to improve those ratios and grow the business at the same time. We see the real numbers and where even small process improvements can be impactful.”
Story retrieved from: https://www.mmsonline.com/articles/why-tie-payroll-hours-to-machine-tool-hoursKorn, Derek. “Why Tie Payroll Hours to Machine Tool Hours?” Modern Machine Shop, Feb. 2018, pp. 76–84