As an auxiliary machinery supplier, I’ve spent the last 12 years on the factory floor and at client sites, staring down the same frustrating repeat problem: a hydraulic pump goes out on a packaging line at 2 a.m., a cooling fan seizes up on a marine auxiliary engine mid-voyage, or a gearbox in a food processing plant fails right before a major production run. For years, I rushed to replace the part, patched the system, and moved on—only to see the same failure pop up six months later. That’s when I stopped swapping parts and started digging for root causes. Root cause analysis (RCA) isn’t just a corporate buzzword; it’s the difference between a client calling you in a panic and a system running reliably for 10+ years. Over time, I’ve tested dozens of RCA methods for auxiliary machinery, and the ones that work best are the ones tailored to the unique, often overworked, auxiliary equipment that keep industrial operations moving. Auxiliary Machinery
First, let’s ground this: auxiliary machinery isn’t the main engine or production line itself, but the supporting equipment that makes it run. Think hydraulic pumps, cooling fans, gearboxes, control valves, and compressors. Their failures rarely happen for one obvious reason—most come from a chain of small, unaddressed issues that snowball. A cooling fan that’s 5 degrees too hot on a hot day? That’s not “bad fan” — it’s a clogged air filter that no one checked, paired with a misaligned belt that the maintenance team skipped during a routine tune-up. RCA methods for these assets need to cut through that complexity without requiring a team of PhDs or weeks of downtime.
One method I rely on more than any other for auxiliary machinery is the 5 Whys. It’s simple, it’s fast, and it doesn’t require fancy software—perfect for small to mid-sized maintenance teams that don’t have the bandwidth for complex analytics. I first learned this method from a client in the pharmaceutical industry, where we’d installed a set of auxiliary gearboxes for their tablet coating lines. Early on, those gearboxes were failing every 8 months, far below their 10-year expected lifespan. Instead of swapping parts, I brought the plant’s maintenance foreman, a line supervisor, and our own service tech into a room and started asking: Why did the gearbox fail? “The output shaft bearing seized.” Why did the bearing seize? “Lubrication was too low.” Why was lubrication low? “The sight glass on the gearbox was coated with dried coating powder, so no one could see it.” Why was the sight glass coated? “The plant had added a new air filtration system last quarter, and the excess powder from the tablets was blowing back onto the gearbox.” Why didn’t anyone adjust the sight glass cleaning routine? “No one was assigned to check it during weekly maintenance checks.” That’s five whys, and the fix was simple: we added a small shield over the sight glass and updated the maintenance checklist to include a quick wipe each shift. The gearboxes have run 5 years without a failure since then. The 5 Whys works so well for auxiliary machinery because their small, often overlooked parts (sight glasses, belt tensioners, filter drains) are where most failures start. It cuts through the noise of “bad equipment” to get to the actual breakdowns in routine checks.
But the 5 Whys isn’t enough for more complex auxiliary issues, like a set of refrigeration compressors for a cold storage warehouse that kept tripping circuit breakers. For that, I use Fishbone Diagrams (also called Ishikawa Diagrams). This method lets you map every possible cause of a failure across six categories: Man, Machine, Material, Method, Measurement, and Environment. Auxiliary machinery lives at the intersection of all these, so this method ensures you don’t miss something. Let’s break down that cold storage compressor failure: The fishbone would start with the problem “Compressor trips on overload.” Under Machine, you’d list compressor age, internal wear, wiring damage, overheating. Under Man, you’d list maintenance training, shift changeovers where no one logs issues. Under Method, you’d list startup procedures, maintenance intervals, refrigerant charging. Under Environment, you’d list warehouse temperature, humidity, dust levels around the compressor. For that cold storage site, we dug into the Environment category and found that the compressor was sitting in a bay with a broken exhaust fan, so summer heat pushed the ambient temp 10 degrees above the design limit. That was the root cause, not the compressors themselves—we could have replaced the compressors and been right back where we were. Fishbone Diagrams are ideal for auxiliary machinery failures because they force teams to look beyond the “equipment is old” excuse. As a supplier, I’ve used this method to train clients to spot issues I might not see from a sales invoice: for example, a food plant’s valves failing at high rates weren’t from bad valves, but from a Method category gap where the maintenance team used the wrong sealant for their high-acid product.
Next, for recurring failures that leave you with a data trail—like pumps that fail every 12 months, or fans that vibrate excessively after startup—FMEA (Failure Mode and Effects Analysis) is a game-changer. FMEA is a proactive RCA method, meaning you use it before a failure even happens, but it’s just as powerful for diagnosing past issues. It works by ranking each potential failure mode by its Severity (how bad would it be if this fails?), Occurrence (how likely is it to happen?), and Detection (how easy is it to catch before it fails?). For auxiliary machinery, which is often run hard and with minimal overcapacity, FMEA helps you prioritize the fixes that will give the most return. Last year, a client in the marine industry came to me with three auxiliary seawater pumps that were failing 18 months into operation—way below their 5-year rating. We pulled their maintenance logs, ran an FMEA, and found that the failure mode “impeller erosion” had a high occurrence (they run the pumps in saltwater with high sediment levels) and low detection (the erosion wasn’t visible until the pump seized). The fix wasn’t to sell them a new, more expensive pump—it was to add a monthly impeller inspection (raising detection) and adjust their pump scheduling to run two smaller pumps instead of one oversized one, reducing sediment buildup (lowering occurrence). FMEA turns reactive RCA into proactive steps, which is why I now offer FMEA workshops to all our clients as part of our after-sales support. Too many suppliers only sell the equipment, but the best auxiliary machinery support is helping clients prevent failures before they start—something that makes us different from the competition.
For more high-stakes auxiliary failures, like a control valve on a power plant’s emergency cooling system that failed during a test, I use Fault Tree Analysis (FTA). FTA is a top-down method where you start with the final failure and work backward to map every event that could cause it, using logical “if-then” gates. It’s more structured than the 5 Whys or Fishbone, which makes it ideal for safety-critical auxiliary equipment. I saw this in action a few years back when a client’s emergency lube oil pump failed to start during a routine test. The final failure was “Pump won’t start.” From there, we worked backward: If the pump won’t start, was there a power failure? If yes, was it a main power outage or a control power outage? Did the pump’s motor have a fault? Was the starter coil burned out? Did the pressure switch that triggers the pump trip on a false signal? Digging into that, we found that a small piece of metal shavings from a recent maintenance job had gotten stuck in the pressure switch, sending a false signal that there was already enough lube oil pressure, so the pump never activated. FTA is perfect for auxiliary machinery because it eliminates guesswork when a failure has multiple contributing factors. It’s easy to get lost in “we checked all the obvious parts,” but FTA forces you to trace every single possible trigger—even the tiny, one-time pieces of debris that end up causing big failures.
I’ve learned over the years that the worst mistake companies make with auxiliary machinery RCA is using a one-size-fits-all method. A single fan failure might be fixed with the 5 Whys in an hour, but a recurring set of pump failures needs FMEA, and a safety-critical valve needs FTA. What’s more, as an auxiliary machinery supplier, my role in RCA doesn’t stop at showing up to troubleshoot. I’ve found that the clients who have the least failures are the ones who don’t just get a new part—they get a RCA process tailored to their specific equipment. For example, a small beverage plant that can’t afford a full-time maintenance team will benefit from the 5 Whys and Fishbone Diagrams, while a large manufacturing plant with a dedicated maintenance team can leverage FMEA and FTA for their more complex assets.
One story that stuck with me was a client in the textile industry who had 12 auxiliary rollers on their weaving lines failing every 9 months. They’d replaced rollers three times without improvement, and I was called in to help. We started with the 5 Whys: Why did the roller seize? “Bearing failure.” Why? “Lack of lubrication.” Why? “The lubrication nozzle was clogged with lint.” Why? “No one cleans the nozzles during daily line checks.” Why? “The checklists didn’t include nozzle cleaning.” The fix was simple: add nozzle cleaning to the daily checklist, and the rollers have run 4 years without a failure. That’s the power of RCA for auxiliary machinery—it’s rarely a flaw in the equipment itself, but a gap in process or oversight that’s easy to fix.
If you’re reading this, chances are you’ve dealt with an auxiliary machinery failure that cost you downtime, revenue, or even safety risks. The good news is that you don’t have to guess at the root cause—you can use these methods to stop repeat failures from happening. As a supplier who’s worked with everything from small food processing lines to large marine fleets and power plants, I’ve seen firsthand that the best RCA isn’t just about finding why a part failed—it’s about building a system that keeps your auxiliary machinery running reliably. Whether you need help troubleshooting a current failure, implementing a proactive RCA process, or just want to make sure your auxiliary assets are performing as they should, we’re here to help.
Plastic Bucket Crate Injection Molding Machine References:
- Ishikawa, K. (1986). Guide to Quality Control. Asian Productivity Organization.
- Del Castillo, E. (2002). Statistical Process Adjustment for Quality Control. John Wiley & Sons.
- Gibson, D. H., & Pintel, D. J. (1999). Root Cause Analysis: A Guide to Effective Problem Solving. Productivity Press.
- American National Standards Institute. (2011). ANSI/ISA-18.2-2011: Root Cause Analysis for Industrial Process Systems. International Society of Automation.
- Besterfield, D. H. (2017). Quality Control (10th ed.). Pearson.
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