Predictive Maintenance And Service: The Proactive Approach To Asset Management

Srikanth Gopalakrishnan

You know the old saying: If it ain’t broke, don’t fix it.

Until recently, this was a philosophy the industrial asset management industry lived by. When a piece of equipment broke, you fixed it. When something malfunctioned, you replaced it. And service schedules were based on estimates rather than data.

The result of this reactive approach? Fluctuating costs, unreliable service, and unplanned downtime – not good for your reputation or your bottom line.

But what if you could track the health of your assets over time, then use that information to identify the optimal maintenance frequency for them? And what if you could predict exactly when a particular asset was going to break down so you could preemptively service or replace it?

Now, it’s possible. Thanks to data science, the Internet of Things (IoT), and machine learning, asset management is rapidly moving toward a predictive maintenance and service (PDMS) model – and this could lead to major benefits for your business.

How does PDMS work?

Let’s say you’re a wind farm operator in Montana. With 50 turbines to monitor, it can be tough to keep tabs on each one. And while your turbines are equipped with hundreds of sensors measuring things like rotation speed and temperature, that information is only relevant if you can use it to make better decisions.

With PDMS, your system will not only aggregate the sensor data, it will also analyze it, using machine learning algorithms. These insights empower you to home in on a specific turbine and get insights like how much wear and tear it was exposed to over the last year and how many times it broke down last month. From there, you can refine your service schedule, determine an optimal maintenance frequency, and predict when a problem’s likely to occur – helping you optimize costs and avoid headaches.

In fact, whether you’re a wind farmer in Montana or a utility company in Detroit, PDMS can enable your organization to:

  • Optimize maintenance costs for increased ROI: Reducing maintenance costs by even a few percentage points can result in hundreds of millions of dollars saved. With PDMS, you can figure out exactly when to service your machines to extend their useable life, optimizing spend and maximizing ROI.
  • Avoid unplanned downtime and schedule service to minimize disruption: The ability to predict and resolve issues before they become problems helps you avoid unplanned outages that burden your customers and adversely affect the bottom line.
  • Improve quality standards and deliver better service: With the help of real-time analytics, you can adjust and improve products and evolve your business model based on market and customer demands.

Unlocking the real-world value of PDMS

The benefits of PDMS aren’t going unnoticed. As new PDMS technologies enter the market, companies around the world are tapping in – and achieving measurable success.

Here are two organizations currently realizing tremendous value with PDMS:

  1. Trenitalia: Italy’s leading rail transport operator recently developed a dynamic maintenance model that combines sensor data, anomaly detection, and maintenance optimization to assess its trains’ batteries, brakes, and motors. With the help of data and the right PDMS system, Trenitalia has been able to define required maintenance actions, allowing the company to reduce errors, increase efficiency, and deliver better service. Ultimately, the organization expects an 8–10% reduction in maintenance costs – which is nothing to scoff at when its average maintenance spend is 1.3 billion Euros a year.
  1. Kaeser Kompressoren: By leveraging IoT and PDMS software, Kaeser – a German manufacturer of compressed air systems – can now monitor compressed air stations at customer sites around the clock and identify usage patterns. Not only has this enabled the company to predict when and what equipment needs service, it’s helped Kaeser decrease unplanned downtime, improve service, and optimize its supply chain.

Leveraging PDMS has also pushed Kaeser toward a new services-based business model. By studying its products in the field and analyzing the gathered data against market behavior and trends, Kaeser has shifted its focus to delivering solutions alongside products. This has helped the company secure its market position, improve margins, and develop new products.

Resolving issues is only the beginning

Staying ahead of problems pays off. By adopting PDMS technology, not only can you resolve issues before they occur, you can increase productivity, improve services, maximize ROI, and create new business models that ensure a bright future.

Eager to learn more about PDMS? Download our free report, Leverage the Internet of Things to Transform Maintenance and Service Operations.

The amount of repair and maintenance expenses have a huge impact on profitability. This is why in the past many companies have moved from a fixed-interval preventive maintenance strategy to a more agile approach based on condition data. In order to take the next maturity level, manufacturers and operator of assets are now moving towards a predictive maintenance strategy which also takes into account sensor data from machines. This will allow them to develop optimized maintenance and service schedules as well as more precise failure predictions.

Learn more and start your free trial of SAP Predictive Maintenance and Services for Cloud today by clicking here.

Srikanth Gopalakrishnan

About Srikanth Gopalakrishnan

Srikanth Gopalakrishnan is Vice President of the Internet of Things and Digital Connected Assets at SAP Labs India Private Ltd.