Finding the key to greater profitability

16 May 2023

Chris Evans looks at the techniques and technologies available to monitor energy usage and develop strategies that help improve production plant energy consumption.

Dramatically rising energy costs mean that, more than ever, manufacturing plants need to identify their energy hot spots and develop strategies to take remedial action to help reduce rising costs.

For many years, control engineers have been fitting energy efficient devices to plant assets to reduce energy consumption. One obvious example is the deployment of variable speed drives (VSDs) to fans and pumps. They have also deployed metering at each asset to display the power consumption locally. 

However, this energy information often remains at the local asset, or maybe it is gathered manually and then entered into a spreadsheet. In any case, making sense of this data and rationalising it into hard facts about how much energy is being used, has been at best, cumbersome.

Advances in technology
Today’s control engineers have many more options available to them and while fitting VSDs to energy hungry motors is still a valid move, technology has advanced to the point that it is now possible to gather data from each asset, aggregate that data, perform analytics and change it into useful information for production managers and energy managers alike.

Plant level devices, such as VSDs, servo amplifiers and intelligent sensors, now have built-in features that provide information, not only about energy usage but also predictive maintenance data and feedback information about the status of the connected asset.

It should be remembered that reducing the plant’s energy consumption is not just about measuring the energy used by each production asset, it is also about making the plant run at optimum efficiency, ensuring asset availability and utilisation to a high level and generally have an active picture of how the plant is performing.

To achieve this it is first necessary to take a step back and look at the plant as a whole. Many assets may already be measuring energy and production data but maybe at this moment in time, the data is not being gathered. Some assets may have nothing in terms of this data, so the question is, does this asset have a big effect on the total plant energy usage or not? If the answer is yes, then some investment in that asset will be necessary.

What plant level networking exists? If there is little, then further investment in the network architecture is required. If you cannot gather the information, then you won’t know what’s going on and so cannot take remedial action to make improvements.

It may well be that the control engineering team has to make a case for these investments and the plant might be hitting all of its production targets, so why should money be spent?

The answer to this dilemma is to identify an area which is a known energy hotspot but at present offers no real granulated data to quantify just how much energy is being used.

Looking at this system and initially deploying a local operator display of the energy usage to identify what is currently being used, is the first phase. The local display will have the ability to log this data so that a trend can be monitored. The next stage would be to take remedial steps to improve the energy consumption of the asset and monitor the improvements locally.

Once this proof of concept has delivered results, it will be easier to make an argument for budget to be released for similar projects across the plant.

Total plant solutions
The control engineering team today has many options to create a ‘total plant solution’.

The plant can be visualised in three distinct layers – the plant level containing all the production assets; the middle or data gathering level, now referred to as the edge computing level; and the enterprise level, where the business systems sit.

It is very likely that plant assets will already be controlled by systems incorporating a combination of PLCs, VSDs, servos and operator displays.

It may well be that these assets are controlled by different automation vendor’s equipment, unless a site specification exists and this, in the past, would have been the first hurdle. However, with the adoption of open network technologies, it should no longer be an issue to allow a ‘head of line’ controller to be deployed as a data gatherer from disparate systems.

Moving to the edge computing level – where the greatest level of technology advances have been seen over the last few years – it should be possible to gather data from the plant, aggregate it and perform analytics, operating in real time with the plant. This means that operations such as machine learning (ML) and artificial intelligence (AI) can be realised. Thinking of this in terms of energy monitoring, energy hotspots can now easily be identified and trends monitored.

The edge computing level is also a gateway to the enterprise level and the ability to aggregate data means that traffic to the top is minimised, which will offer cost savings.

At the enterprise level it is also now possible to introduce further analytical and visualisation modules which can look at energy usage, plant performance and predictive maintenance requirements. Here we can generate management reports and develop strategies to improve energy usage and overall plant performance.

It is clear, once the architecture is put in place that connects the plant to the enterprise level, it becomes a common bus for all plant data and can deliver many benefits to the operation.

Getting started
The key to improving plant performance, whether that is reducing energy costs, improving efficiency, or by increasing asset availability and utilisation, is knowing what the current situation is, analysing that picture and developing strategies to improve it.

As discussed, the tools in the control engineer’s bag today are comprehensive, however the blocker is often available budget, so a staged approach is a sensible way to start that journey but always have an eye on the ultimate goal. Improving current hot spots will usually involve relatively modest investment but can realise big returns and serve as a proof of concept to allow this path to be followed.

Chris Evans is Vertical Industry Group Manager at Mitsubishi Electric.

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