Maximising monitoring: three key ways to improve profitability

Phoenix Contact Pty Ltd

By Clinton Hommel, Product Marketing Specialist, Phoenix Contact USA
Tuesday, 17 July, 2018

Maximising monitoring: three key ways to improve profitability

Smart instrumentation, monitoring and the connected factory represent an exciting new era in industrial automation known as the Industrial Internet of Things (IIoT). The IIoT is transforming the way we design and operate all kinds of equipment. It even influences plant design as a whole. The promises of smart factories that can reduce energy consumption and boost uptime are firmly rooted in monitoring and collecting data on equipment of all types.

The emphasis on monitoring within the IIoT is by design, as monitoring is one of the single-best mechanisms for improving operational efficiencies. It is not uncommon for energy monitoring to be overlooked as nothing more than an energy-efficiency product. Energy savings are great, with benefits for the wallet and the planet alike, but looking at energy monitoring only as a tool to reduce consumption leaves a lot of additional cost-saving opportunities on the table. Simply put, monitoring enables operational improvements from a number of angles.

The goals of this article are to introduce the three basic ways monitoring can help achieve savings. It will conclude with some insight on system scaling and a few applications.

Meet RAE

There are three major ways that energy monitoring can improve profitability: RAE (reliability, accountability and efficiency).

Though all three concepts are related, they each have unique benefits and cost-saving mechanisms. Taking advantage of RAE as a whole substantially increases the return on investment (ROI) in monitoring equipment, especially when compared to implementing energy-efficiency improvements alone.


The single-most important benefit of energy monitoring in the industrial world is not energy savings, but rather, uptime and reliability improvement. Energy signatures and power quality within systems play large roles in unlocking predictive maintenance, also known as just-in-time maintenance (JITm). Unlike run-to-fail or preventive maintenance programs, downtime or excessive spending on interval-based equipment replacement can be minimised or avoided altogether.

JITm at its core involves monitoring energy usage, utilisation and quality, comparing it to historical baselines, and then flagging anomalies as action items to investigate before a failure occurs. These types of anomalies can be the result of typical wear and tear, the need for periodic maintenance or equipment end-of-life, to name a few. Monitoring can also be used to detect other conditions that would require regular maintenance typically associated with a certain amount of runtime. By accurately detecting things like tooling wear, filter contamination or consumable materials depletion, maintenance personnel can schedule time windows to optimally balance maintenance needs with production uptime.


There are also some benefits to maintaining monitoring and logging equipment that are independent of utility metering. Operating energy meters independent of the utility allows facility managers to verify billed energy quantities, as well as time-of-day and usage rate data. It also allows them to have logs of all of this data and the quality of service delivered. Logs and independent data points can be a significant help in cases of utility failures or billing disputes. These logs are frequently used to hold utilities accountable for remediation if a customer is overcharged or if there is a utility-side issue that results in damage to equipment or lost production time.

A significant side benefit of maintaining logs is the ability to conduct a more thorough failure analysis in the event of sudden failures. These types of failures are different than those prevented by JITm because they typically occur as a result of issues with the quality of the power delivered and are not a function of machine wear. Much like IT departments use event logs to determine what was happening before, during and after an unexpected outage, maintenance departments can use energy logs as tools to assess power system conditions surrounding a failure. This may reveal a root cause or it could expose equipment vulnerability issues. Accordingly, the maintenance personnel can take necessary corrective actions to avoid future downtime.


Efficiency, specifically energy efficiency, is often seen as savings through reduced consumption by switching to high efficiency electrical devices — think NEMA premium efficiency motors and transformers or LED lighting upgrades, for example. While these types of upgrades do indeed improve efficiency, overall efficiency improvement is a broad topic that also includes the often overlooked element of optimisation.

Efficiency optimisation involves correcting inefficiencies in processes and machine cycles alike. Some of these inefficiencies are the result of machine malfunction and other inefficiencies are present simply because certain machines or processes have never been optimised. The most common types of inefficiencies would primarily include wasteful machine cycles, equipment failures resulting in excessive energy consumption and parasitic loads.

Monitoring plays a critical role in optimisation by providing a clear picture of how much energy is used and how it is being used. Data collected by monitoring is compared to historical consumption, utilisation and machine throughput trends. Once usage baselines are established and performance metrics are defined, undesirable conditions can be identified and eliminated.

Data is king, but only if it’s used

Broadly speaking, there are three sets of monitoring data that can be analysed to achieve all of the benefits of RAE — instantaneous data, current versus historic data and logged data. Each has its own place in the toolbox of process optimisation, and each one can vary in both the story it tells and the complexity of that story. There is an entire industry dedicated to the analytics of these datasets, because the knowledge gleaned is very powerful, and sometimes very specialised. While some of the upper echelons of monitoring benefits can only be realised by using powerful software algorithms catered to a specific industry or application, the basic benefits of RAE are easily attained using some simple intuition and a basic controller or data logger.

While a statistical or calculus-based approach can predict failures and action items with a high level of precision, there is a trade-off between the costs of such services and the realised savings of knowing precisely when something will fail. Those types of services and platforms are beyond the scope of this article, but their importance should not be discounted, especially for mission-critical applications.

Measured energy parameters as tools of insight

Each point of measurement provides a unique insight into system or machine health. By applying some critical analysis to the data that is measured, RAE becomes easily achievable. Key parameters — such as voltage, current, power, energy, power factor and harmonics — can tell the system’s story.

A word on scale

Scaling a system to the user’s needs and goals is a form of efficiency in itself. To avoid excessive spending and poor ROI, it is necessary to scale the capabilities of the monitoring devices to the needs of the machine or process. It is also necessary to consider the overall impact of any one particular component on uptime. While some motors or heater elements may be redundant within a process, others may represent a critical failure point — the appropriate amount of monitoring, analytics and maintenance should be prescribed accordingly.

For example, downtime of a simple conveyer belt application might not greatly impact overall production because it can be bypassed by manual labour. Spending thousands of dollars on a dedicated energy meter might not make financial sense when a $100 voltage monitoring relay suffices to protect the motor.

Conversely, the intake pumps at a wastewater treatment facility are considered mission-critical to the operation of the plant. Should one of the pumps fail unexpectedly, water treatment could be adversely impacted. The motor may cost $10,000 and it could be connected to a pump that costs tens of thousands of dollars. It is fairly obvious that the water treatment plant operator would want to know everything they can about the pump’s state of health so that they can plan maintenance as needed, so that they have an advanced warning before any failures should occur, and so that they can protect their investment in the pump itself. Run-to-fail is simply not an option in this application. As another cost-saving benefit, once monitoring is incorporated, it can also be used to switch the pumping station to an as-needed maintenance schedule instead of a periodic routine maintenance plan. Such plans typically involve rebuilding or replacement of critical components on a fixed schedule regardless of equipment health.

Selecting monitoring equipment without overspending or underspecifying can be done by calculating how often a failure occurs, how much the downtime costs you and then comparing it to the cost of the monitoring device. For lower-end devices such as voltage/phase monitoring relays and basic current transducers, monitoring almost always pays for itself on the first outage it prevents. More advanced platforms that incorporate energy meters, power quality meters and analytics can cost well over $10,000. Such a solution is not fitting for every application, and it might not ever pay for itself if it is inappropriately applied. There are, however, processes where just one outage prevention would pay for the system several times over. It can often be tricky to strike the perfect cost-benefit ratio no matter the investment, but having specific needs and goals in mind can help ground the selection of monitoring equipment in reality.


The decision to invest in energy-monitoring technology is often grounded in the somewhat vague promises of what the IIoT will bring to the modern plant and its bottom line. Energy monitoring is generally sold as a money-saving technology, marketed as devices or platforms that can help users reduce energy consumption or costs. However, some issues continue to plague the industry in its quest to unlock the promised savings.

Many organisations invest in monitoring equipment but then fail to follow through on analysing the data it returns. This reduces the equipment’s ROI, and it greatly limits the realisation of the promised benefits. It is an issue that stems from the fact that, in many cases, little is done to help customers, operators and engineers realise the benefits of monitoring once the systems are in place and the integrators have gone home.

However, engineers and operators shouldn’t settle for underperforming or underutilised monitoring systems. By applying the RAE principles and implementing a JITm program, those promised benefits can be suddenly realised, and an exciting new reality — one filled with uptime and cost savings — displaces the underwhelming realities of systems that do not make use of the data they collect.

Ultimately, when care is taken to properly implement monitoring, it can significantly reduce operational costs. It results in a better bottom line for everyone — maintenance costs and utility bills are reduced, uptime is improved and profitability is enhanced. To paraphrase Benjamin Franklin, where there is money to be saved, there is money to be made.

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