_________________________________________________________________________________________________________ AI
+ CBM
AI technology paired with condition-based maintenance can keep factory assets operating at peak performance. By Scott Campbell
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In the manufacturing sector, rapid change is the default. Manufacturers must contend with unpredictable supply chains, volatile market trends, and shifting regulations. Amid this change, there’ s one crucial constant: the importance of maintenance. How well a factory floor’ s assets perform impacts every other part of the business. If a welding machine or conveyor system goes down unexpectedly, everything from production and inventory management to sustainability progress can be thrown into disarray.
It is no surprise, then, that asset maintenance has become a science in manufacturing. There are a variety of maintenance tactics, tools, and technologies to choose from – all of which can be mixed and matched in countless permutations.
One of the most potent pairings available to manufacturers today is condition-based maintenance( CBM) and artificial intelligence( AI). Together, they create a 1 + 1 = 3 effect, deepening maintenance insights and accelerating productivity. Yet many manufacturers aren’ t fully leveraging this synergy, forfeiting coveted insights and productivity.
Understanding conditionbased maintenance( CBM)
CBM isn’ t a new maintenance strategy, but it is constantly being refined. At its core, CBM is about collecting asset data to determine when maintenance is necessary, rather than relying on predetermined maintenance defined by time or usage. Asset data might include temperature, vibration frequencies, oil acidity, pressure, or power quality.
This data informs metrics like p-f intervals and p-f curves, which allow technicians to determine if and how an issue will result in asset failure, and how long they have to perform maintenance.( The p stands for‘ performance’ and the f for‘ failure’).
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