For many businesses looking to reduce energy costs, one answer is new equipment. After all, new shiny assets will always run more efficiently than legacy equipment. But this also highlights one of the biggest barriers to energy efficiency within industry – cost. If the cost of new machinery outweighs the potential energy savings, or has a lengthy ROI, then it might not be a viable solution, regardless of the environmental benefits. Moreover, that equipment will also age, and become less efficient, meaning that the ROI will decrease over time. A better approach is to maintain assets in their ‘as-new’ efficient states with a highly proactive maintenance programme that can make judgements about the relative savings for example, replacing worn parts before they break. Naturally, such a programme will benefit from no unplanned downtime because of high energy costs associated with the shut-down and start-up of power-hungry equipment.
Another key method for energy cost reduction is also data-led. With IIoT data coming from operational technology it is possible to track and manage usage very 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 starting up pumps and motors could be undertaken when energy cost per unit is lower (overnight, for instance), 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 industrial 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 lies for many industrial enterprises.
Assets are often located away from the data centre and thus 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 was only possible with a data link between the asset and the enterprise management software. Such a link can be difficult to achieve in an industrial setting with disparate assets, and, in some extreme cases like oil and gas offshore platforms, this distance cannot be traversed by cabling, but must be managed with satellite communications. As with the cloud-only approach however, sending data off site for analysis introduces latency that means operators would have a lack of visibility into minor faults or deteriorating parts that can quickly develop into downtime events. Without real-time access to this information at the equipment level, operators (and the entire enterprise) can’t visualise data from all assets, compromising their ability to implement a proactive maintenance approach.
Simple, protected & autonomous
Operators can overcome the distance by implementing Edge Computing and having the computing power they need, where they need it. By opting for a platform that is ruggedised especially for the harsh industrial environment, operators can converge the worlds of IT and OT without any drawbacks or added security concerns. The right edge platform will be simple to install and simple to use, saving time on installation and configuration with no added training needed for OT professionals. The automated platform will have the ability to run virtual machines with fault tolerance to eliminate unplanned downtime caused by IT failure, so visibility can be achieved with minimised risk and no new point of failure. A strong Edge Computing platform offers a simple, protected and autonomous solution that gives the tools to operators to pursue more energy efficient operations.
Edge Computing has rapidly 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 lead to an organisation making notable improvements in energy efficiency at every opportunity. 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.
