Use data to turn problem assets into reliable production systems

Stanton McGroarty says gather a core team and perform RCA for perennial equipment problems.

By J. Stanton McGroarty, CMfgE, CMRP, senior technical editor

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Maintenance is truly data driven when the data are guiding us to the most significant maintenance work we could be doing in our plant and showing us how to solve it. This is the second in a three-installment series, “Ready, Aim, and Fire,” named after the time-honored sequence for permanent solutions.

We agreed in Part I to use data to guide us to a couple of the biggest, most costly recurring maintenance headaches in the plant. Further, we said we’re ready to solve these problems when we have identified them and quantified what they are costing the organization. The cost information should be adequate to fuel the discussion that will inspire the small, cross-functional team we will need to set the two remaining steps in motion.

In the aim step, we will gather a core team and perform a special root cause analysis (RCA) for perennial equipment problems. The core team will determine which corrections we must implement to convert our problem assets into reliable production systems. When large, perennial problems are examined, it is almost always true that they are really bundles of related problems with multiple causes. The multiple causes usually require multiple solutions. The multiple solutions usually require help from a variety of functions.

These solutions will require the usual maintenance work orders, but they won’t stop there. Solving big perennial problems may also call for a mix of improved production processes, new PdM procedures, engineering changes, training support, new gages or inspection procedures, and new shop floor discipline.

Management support is essential. A change management program and a communication plan may also be needed, depending on the size of the required effort. Occasionally the input from marketing or customer-contact people may be helpful. Clearly, a cross-functional team is needed to create and organize the work list for this kind of problem solving. The aim section is designed to bring the need into technical and financial focus and to propose the next steps to design and install the fix.

When building your core team, start with the owners of the data that will bring each failure mode into focus. Using the ready exercise as preparatory work to determine which information each one has, create and convene a team to develop the story of the problem equipment. If a fully populated CMMS is available, this is simply a printout. More likely you will want to gather the people who maintain the key data files on the equipment under investigation. This will include the production supervisors, perhaps with clerks, who can place production on a calendar, along with the reasons for lack of output on slow days. The group should also include maintenance planners or leaders who are responsible for corrective action in the area under discussion. If metering, controls, or electrical people are from a different group, you’ll need to have them represented, as well. Each group should be able to position its data on a calendar or time line so that area performance problems and the corrective action relating to them can be tied together and placed on the calendar. Whoever orders maintenance parts should also have a chair at this table.

In your organization there may be other players who should be present for discussions of failures. Add them. What you’re looking for is a group, facilitated by you or someone else you choose, who will go through the past year or two of your problem machine’s downtime history with a discussion that starts something like this:

“What happened on Jan. 12? We lost five hours.”

“The main pump spun a bearing and we had to pull one off the shelf to replace it. The rebuild was a big job; we couldn’t stay down for it.”

“Why did it spin a bearing? Isn’t there a PdM program to check ultrasound or vibration on a key piece of equipment like that?”

And the RCA starts. Maybe a 5-whys approach will be thorough enough for determining most failure causes, but watch for the subtle ones. They may need whatever your more precise and thorough reliability approach is.

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