Failure analysis in collaboration with preventive maintenance, can help avoid future equipment failures from occurring and stop them from taking your productivity and profitability down with it.
You usually hear the phrase “failure analysis” used in conjunction with “machine condition monitoring” and “preventive maintenance.” Let’s put them all together.
Failure analysis involves the use of data to understand why a part failed or why it is in danger of failure. Machine condition monitoring gathers the data. Both processes result in more intelligent preventive maintenance.
The goal here is to collect operational data from machines in real-time, check them against benchmarks for normal operation and failure thresholds, analyze any aberrations in a machine’s operation and provide actionable recommendations (“alerts”) before questionable parts fail outright.
The phrase “real-time” is critical here. With the right approach to failure analysis, companies can receive warning of parts problems well in advance of total failure. This greatly reduces the likelihood of your most important assets going offline during peak hours or periods of seasonal demand and gives your maintenance staff the time they need to evaluate their options and come to ideal solutions.
These automated preventive maintenance alerts also make it easier to pinpoint the problem in a complex machine — including something like a conveyor belt, which has its parts distributed more widely — no more wasting human productivity on disassembly and diagnosis.
Failure analysis and condition monitoring essentially replace the “run to failure” model operators have been relying on for years. Besides preventing catastrophic machine failure, condition monitoring also helps slim down parts inventories and facilitates more strategic purchases, compared with trying to stay prepared for anything/everything at all times.
Preventive maintenance is a familiar concept, but pairing it with real-time machine condition monitoring is the next logical step. Before, preventive maintenance involved performing inspections manually at regular intervals and sometimes replacing parts preemptively. Failure analysis helps make sure companies can safely get as much life out of their parts and equipment purchases as possible.
As you’ve guessed, applying failure analysis and condition monitoring to a manufacturing plant involves deploying sensors strategically to create a stream of meaningful machine data. From there, database software performs analysis and delivers actionable suggestions.
But what’s actually being measured?
To get a sense of how this concept applies to a broad variety of industrial machines, here’s a rundown of some of the most common sensor and data types already seeing industrial-scale use:
Other data collection equipment includes voltage meters, moisture sensors, pressure sensors, and more. By testing components to their breaking point, manufacturers can confirm what stressors cause a material to corrode or fail. With this knowledge, they can improve the part’s performance and reliability. Applying failure analysis to preventive maintenance has implications in the manufacturing industry, as mentioned, but also in the offshore drilling, automotive, pipeline, and water processing industries, among many others.
Realistically, a few-hundred-dollar handheld vibration meter can be all it takes to get started with preventive maintenance. But to take full advantage of failure analysis and real-time condition monitoring, your company will need a bit more skin in the game. Data-logging devices and the software to run them, and organize their findings, will be a significant investment. But the savings could be enormous.
Failure monitoring can be part of a larger Industrial Internet of Things rollout and make use of the same cloud infrastructure you already rely on to coordinate customer orders, exchange documents with clients, and more. Once sensor data is gathered from the machines at the “edge” of your network, its next stop is either a database management system, for analysis, or to a graphical interface for use in enterprise planning. This is a whole different world when you compare it to intermittently checking your equipment with a vibration measuring pen.
Some software programs offer fairly basic functionality — your engineers will be able to view changes to a machine’s performance over time and set individual alarm points based on desired machine performance thresholds.
Other programs are more sophisticated. Computerized maintenance management software (CMMS), for example, helps make maintenance a bigger part of the financial planning process. It weighs the cost of repairs, spare parts and equipment replacement against the company’s financial “big picture.”
In short, giving your equipment eyes and ears so they can take some of the guesswork off your plate brings another branch of your operation into the digital fold. Knowing the health of your equipment at all times means you can make more accurate predictions downstream and have more warning to come up with a solution for external problems, such as material shortages, problems with vendors, trade disputes and more.
Article by —
Megan Ray Nichols
Freelance Science Writer
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