My article about practical labor rates prompted a number of readers to contact me. The question that kept appearing in my inbox was “How do you measure wrench time accurately?”
For the record, what I mean by wrench time is the time a maintenance technician spends performing work directly on equipment or systems. The idea is to look at that time as value-added direct equipment healthcare.
I look at wrench time measurement not as a single task, but as one data point that needs to be validated. Let’s say your workforce knows you’ll be doing a wrench-time study. Supervisors, managers or the workers themselves might attempt to select or prepare for certain tasks. They might have everything organized for that job to a much higher degree than normal. This skews the data and returns a much higher wrench-time value than when the study is conducted without forewarning.
When I say I prefer the use of a combination of sampling and measures, I’m referring to measures that can be used to paint a picture of whether or not the wrench-time numbers make sense. For instance, if your wrench-time study resulted in a wrench time of 55% (very high), but you’re at something like 70% unplanned maintenance, I’d say something is off.
If the organization’s maintenance management software system consistently collects information on planned and unplanned labor hours, my money would be on the wrench time — a subjective, approximate value — being off. Examples of measures I’d consider to be good cross references to wrench time observations include:
- Percent of planned and unplanned labor hours vs. total available labor hours
- Number of man-weeks of backlog maintenance that is planned and ready to schedule
- PM/PdM completion rates
- Production unplanned downtime
- Percent of rework (jobs repeated on the same equipment within a period of time, such as six months or a year)
So, the understanding of validating measures is a good foundation for conducting a wrench-time or barrier study. Caution: A barrier study can introduce problems if your organization lacks trust between the workforce and management.
Spend some time with labor leaders and those on the plant floor who have influence with the rest of the crew. Explain what you’re doing and why. It’s important to share the data with the worker being observed so they see what you’re writing. Better yet, provide them with a hardcopy. This allows them to be less anxious about the study.
I prefer to call these exercises “barrier studies” because the point you want to make with the leadership, foremen and workforce is that the study isn’t concerned with how each craftsman personally performs the job tasks. I don’t care if it takes a technician 20 minutes or two hours to remove a coupling between a motor and pump assembly. Rather, the study is conducted to identify the systemic barriers that keep the workforce from doing their jobs.
The idea behind improving wrench time is to work smarter, not harder. Most workers don’t like traveling across the refinery only to find that the job plan didn’t identify the actual work that needed to be done, that they didn’t bring the right tools and that the repair parts supplied were incorrect. They understand that not having the job well-planned leads to having to return to the shop or store counter repeatedly.
Identify the total time the technician spent in various categories of activities. Use five to eight categories. Examples include:
- Performing value-added work
- Getting instructions and clarifications
- Break or lunch
- Waiting for parts
- Waiting for tools
- Waiting for production to turn over equipment
Of course, you’ll want to carry a generally accepted definition of what each includes. That could derive from the conversations you had with the labor leaders. Graph the categories to see where the time goes. The total time spent on value-added work divided by the total hours available is the percent wrench time.
It’s important to have a plan for what you intend to do if you identify and resolve inefficiencies. In my experience working across refineries, chemical plants, aerospace manufacturing, mining, facilities and other industries, organizations reduced their headcount too much. I usually coach leadership teams to use the benefits from efficiency to reinvest in proactive reliability activities such as PM/PdM optimization, root cause analysis, FMECA or RCM. These continuous improvement activities have a much higher ROI than cutting head count.
Tom Moriarty, P.E., CMRP, is president of Alidade MER Inc. Contact him at firstname.lastname@example.org and (321) 773-3356.