When considering the growth and productivity of organizations in different fields, it doesn’t take too much time to see a pattern on how maintenance strategies are common throughout all consistently thriving operations.
Predictive maintenance is amongst the most impactful of strategy plans because it centers itself on forecasting issues before they actually occur. The name of the game is efficiency and preventing unnecessary costs.
This means having the ability to understand how machines are being used, make assessments, followed by the collection of clear data that informs the maintenance team, giving them enough time to perform corrective actions.
But which industries rely on predictive maintenance the most and how do they go about doing that? Let’s review five industries that are most impacted by the power of predictive maintenance.
1) Oil and Gas Industry
One of the earliest pioneers of predictive maintenance, the oil and gas industry’s main point of need revolves around lowering cost of maintenance while mitigating risks of environmental disasters.
What makes predictive maintenance in this field so fruitful is the ability companies now have to monitor the condition of their assets remotely, which lowers inspection expenses and gives them enough data to prevent dangerous equipment failures.
This is due to sensors that can now be installed into and onto machinery. These sensors feed the data into specially developed predictive algorithms that can warn them about potential failures.
2) Food and Beverage Industry
While food and beverage industry doesn’t represent a threat to the environment, it can definitely have an impact on people’s health. The only way to thwart those health risks is by having a completely controlled and stable environment for the storage and protection of food and drink.
Given the vastness of the Food and Beverage market in only 2018 being at a predicted $90.173 billion, it isn’t hard to imagine all the food storing equipment and tools that are responsible for keeping are every safe for consumption.
From complex equipment to strict regulatory standards, food and beverage industry has to tackle different maintenance challenges.
Broken equipment can lead to big health issues down the line. Not only can it destroy the reputation of an organization, but in the worst-case scenarios, equipment breakdowns can lead to the spoiling of foods, which might be mixed with fresh foods when sent out to consumers.
This is where predictive maintenance takes the stage. It is highly focused on its impact regarding operational efficiency and functional performance.
Complying the most stringent and severe of laws pertaining to food and beverage can be hard. But with proper monitoring of critical equipment, there’s a far lesser chance of something unexpected happening. Especially when you combine predictive technology with CMMS software and proactive maintenance methods.
3) Manufacturing Industry
Downtimes and machinery failures will happen no matter what strategy you take on. It’s true in the manufacturing industry as it is in any other. However, with enough research and data collected, unplanned downtime can be decreased significantly in all equipment failures.
Downtime can cost big manufacturers as much as $22k per minute. So what happens if your delay is even longer? You can take a guess.
Serving machines only when they break down has a surprisingly high cost. It is not easy to understand how much delays of time and production can affect an organization, so it’s better to not take the risk and plan ahead.
When done so using predictive maintenance, an average of three to five percent of a machine’s life is increased. If we are talking about an enterprise, these few percentage points can save manufacturers millions of dollars. On top of that, maintenance supported by sensors and predictive analytics also improves product quality and overall equipment effectiveness.
As you can see, there are plenty of reasons why manufacturers are excited about predictive maintenance.
4) IT Industry
Just as big machines show signs of damage and future breakdowns, so does computer hardware. Since the failure signs are usually much harder to notice than in your standard production assembly, sensitive tools are being used to analyze hardware in ways that make everything as transparent to the user as possible.
Using state of the art technology with a focus on data analytics, it is no longer impossible to see patterns and make reasonably accurate guesses as to when a piece of computer hardware needs to be repaired or replaced.
Why is this so important?
From government agencies and hospitals to data centers that power the financial sectors and IT hardware to controls navigation and telecommunications, almost every service we use today is dependent on some sort of computer hardware. It isn’t hard to imagine how a long service unavailability or data loss can lead to a major fallout that affects millions of people. Luckily, predictive maintenance is one of the ways to reduce the chance of that ever happening.
5) Power and Energy Industry
When dealing with power plants and the process of deriving energy through an operation that revolves around so many moving parts, having a tight grip on maintenance is the only way to stay on top of the ever-increasing costs.
Like other industries, detecting problems and acting on them ahead of time ensures the unlikelihood of failures or setbacks from happening. It also protects the company from enduring long stretches of repairs that can lead to huge losses of funds that sometimes leads to an organization’s bankruptcy. One of the benefits of predictive maintenance is that, when implemented properly, it increases asset efficiency, which is a nice bonus for the energy industry as it increases profitability. The research suggests that North America is the biggest market for predictive maintenance, with big players like Bosch, GE, Hitachi, and Honeywell.
Being proactive with respect to impending problems is even more important in an industry where everything is impacted by the power it produces.
Maintenance in the Future
With the 5G technology around the corner and looking at all available statistics, it doesn’t seem like there is anything that can slow down the growth of predictive maintenance. This is an excellent news for all data scientists. After all, installing predictive sensors on equipment is only one half of the story. To fully utilize predictive maintenance, organizations need the help of data scientists to develop predictive models which can be fed with the data coming from the installed sensors
