Making energy savings for a sustainable future with proactive maintenance

Sustainability insights

• A better approach to sustainability and efficiency is developing a proactive maintenance program that can make better judgments about actual energy and cost savings.
• There is a need for an edge computing platform that takes the abundance of data produced from modern manufacturing environments and turns it into real-time, actionable intelligence.

For those looking to reduce energy costs, one answer is to purchase new, more energy-efficient equipment. However, this also highlights one of the biggest barriers to energy efficiency – cost. If the cost of new machinery outweighs the potential energy savings or has a lengthy return on investment (ROI), then it might not be a viable solution, regardless of the environmental benefits.

A better approach is to maintain assets in their “as-new” efficient states with a proactive maintenance program that can make judgements about the relative savings – for example, replacing worn parts before they break.

Another method for energy cost reduction is also data-led. With industrial Internet of Things (IIoT) data coming from operational technology it is possible to track and manage usage accurately and make small but important decisions about when energy loads are largest compared to cost per unit of purchased energy. If, for example, energy hungry tasks such as switching on a production line could be undertaken when energy cost per unit is lower, then a cost saving can be achieved. Further, as part of a full digital transformation strategy, it is possible to compare operating conditions for similar equipment doing similar jobs over time and seek to recreate optimal operating conditions across different assets in an enterprise.

At the heart of both approaches is visibility into the operating performance and conditions at the application edge. To achieve such visibility, there is a need for an edge computing platform that takes the abundance of data produced from modern manufacturing environments and turns it into real-time, actionable intelligence for operators to make more informed maintenance and energy use decisions.

Proactive maintenance

To get older machinery working like new, maintenance professionals need a steady stream of information about asset health and performance, and not just periodically, but live, in-flight, as-it-happens data. This is where the challenge often lies.

Assets are often located far from the computing power needed to generate insight. Sending data for analysis to the cloud adds latency and could mean the difference between recovering from a maintenance issue that leads to unplanned downtime or preventing it from happening all together. This means improving energy efficiency and combatting unplanned downtime are two issues that go hand in hand and making gains in both leads to improvements on the bottom line.

Traditionally, this level of proactive maintenance has only been possible with a data link between the asset and the enterprise management software. Such a link can be difficult to achieve in a manufacturing setting with disparate assets and legacy equipment remaining in operation. Even with a cloud-only approach, it still requires data to be sent off site for analysis, adding latency that means operators have a lack of visibility into minor faults or deteriorating parts that can quickly develop into downtime events and poor energy efficiency. Without real-time access to information at equipment level operators cannot visualize data from all assets, compromising their ability to implement a proactive maintenance approach which has a direct impact on energy efficiency.

A fundamental step

Operators can overcome the distance between asset and enterprise by implementing edge computing and having the computing power they need, where they need it. Edge computing has become a fundamental step in any digital transformation journey, which in turn is an important process for any company looking to reduce energy use without the costly replacement of assets. With a simple, protected, and autonomous solution, the data visibility that underpins real-time energy management and proactive maintenance schemes is within reach for any industrial enterprise in almost any industrial environment.

These small and incremental changes to maintenance approaches can lead to notable improvements in energy efficiency. Not only does this save on the energy costs themselves but opens up further avenues to be profitable, with assets remaining in operation for a longer time and a significant reduction in unplanned downtime.

Original content can be found at Control Engineering Europe.

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