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Emily Newton

Lean

What Are Energy-Aware Manufacturing Operations?

Three challenges to reducing energy consumption while maintaining productivity

Published: Wednesday, May 11, 2022 - 11:03

There’s no better time than now. As a species, we need to mitigate the effect we have on our planet. There are many ways to do this—namely, through green and eco-friendly initiatives—but one sector is having the biggest impact of all: the industrial and manufacturing sector. In the 2010s, the industrial sector accounted for nearly 50 percent of the world’s total energy consumption, and during the last 60 years, that has almost doubled.

Manufacturing isn’t just energy-intensive, however. It’s also responsible for harmful emissions and is a huge producer of waste. Establishing more energy-aware manufacturing processes and systems would be a massive step in the right direction. It could mean the difference between slowing climate change or stepping over our fast-approaching tipping point.

A report, titled “Energy-Aware Manufacturing Operations,” by Vittaldas V. Prabhu, Damien Trentesaux, and Marco Taisch, takes a deep dive into this idea and also reveals how manufacturing has failed to keep up with modern standards. The assessment was done by reviewing and dissecting 12 high-quality research papers in the field of energy-aware manufacturing.

So, what can we do to make manufacturing more energy-aware?

Addressing the challenges

According to the report, there are three broad and major challenges. Not only are they the key to making energy-aware manufacturing more feasible, but they’ll also have a powerful influence on the viability of said improvements. We need to be making the right upgrades and improvements to strategically decrease impact. Otherwise, we could see even more setbacks.

The challenges are:

1. Energy efficiency vs. manufacturing-system effectiveness in optimization
2. Volatility in energy availability, supply, and cost
3. Modeling energy consumption at varying scales across different subsystems

Many of these challenges stretch far beyond core systems, including more than just machinery or automated hardware.

Challenge 1: Efficiency vs. effectiveness

Trying to find the balance between energy-efficient solutions and manufacturing system effectiveness is no easy feat. Yet it can have a reductive effect on output. For example, reducing energy consumption may be associated with a loss in performance, as the systems are often cut down or reduced in power to offset the consumption levels. Understandably, this leads manufacturers to avoid more efficient power solutions in the interest of greater performance. However, it is possible to simultaneously manage both elements.

Interestingly enough, the use of modern technologies can help improve and streamline this balance. But it must be implemented appropriately so as not to consume more power. Information technology tools are a viable way forward when used in a knowledge-based system approach.

Some businesses that shifted to digital processes and adopted industrial IoT have seen efficiency improvements as high as 82 percent with 49 percent fewer operational defects. Major companies such as General Electric are able to introduce IoT into their processes to manage, boost, and streamline operations. By improving production accuracy, manufacturers can reduce waste and improve product quality.

Challenge 2: Energy volatility

Due to environmental conditions and events, energy availability has become increasingly volatile, with a reduced supply alongside significantly rising costs. It means energy and power management systems must be more reactive to adapt to surrounding conditions.

When swapping between renewable energy sources and traditional ones, it makes sense to reduce consumption as much as possible since the latter is more expensive and more taxing on the environment. At the same time, introducing renewable energy sources can also affect the behavior of the supply, making things much more complicated.

The solution is to deploy and optimize data analysis tools that can leverage risk management insights, simulations, algorithmic solutions, and beyond. The modeling will be difficult to create and build upon, but it’s a challenge that can be overcome.

Johnson Controls achieves this using a multifaceted strategy resulting in a combination of energy productivity improvements. First is a focus on reducing waste and cutting down on energy consumption. With that reduced energy footprint, renewable energy is implemented. This not only keeps production and consumption at manageable levels without compromising productivity, but it also further reduces the impact on the greater power grid once the renewable energy solutions come into play.

Challenge 3: Modeling energy consumption

To build accurate models of a system, or for use in simulations, you first need an energy profile of all power-based technologies and hardware, from robots to conveyors. The challenge comes from accessing these energy data, especially in legacy hardware, where it was never the intent to monitor and collect this information in the first place. Altering designs to improve energy efficiency is often achieved on a foundational level, not through retroactive measures.

The report discusses generating “internal micro-models” and “external micro-models” as a response, with specific forms of knowledge and experience required of each. These models can be used to better understand and react to various conditions and to plan for eventual complications that may appear in the future.

Supply chain and demand problems, fluctuations in power availability, and shifting energy costs are all events that affect general operations. Energy modeling tools and energy modeling software can empower this process. There are both free and web-based software tools that can help assess, plan, and restructure facilities.

With direct access to predictive and modeling tools, organizations are less likely to be bogged down by unexpected changes in the market or industry. What’s more, they can adjust more appropriately without drumming up higher levels of waste and consumption.

Parsing the contributions

Although incredibly simplified here, the study also makes a point about active contributions that aim to minimize or solve the related problems.

For example, one solution to volatility could be creating a detailed analytical model that captures distinct insights. Those data points, which include variations in energy consumption, fluctuating energy unit prices, and carbon offsets, employ a probabilistic approach to addressing risk management and environmental considerations. Eventually, manufacturers can estimate the power fluctuations and consumption of business interactions.

Whether a contribution misses its mark or not isn’t the right question to be asking. Instead, how can these contributions be expanded to address each challenge? The report briefly explores alternatives.

The conclusion

Right now, we’re at a critical point for clean and renewable energy adoption. To reverse some of the damage our society has done to the environment, we need to act fast and accelerate all efforts, including a concerted effort to reduce energy consumption. Crucial to that idea is the effective reduction of power consumption in those areas that have been the most influential for decades: manufacturing and industrial operations. Energy-aware manufacturing is the next logical step.

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About The Author

Emily Newton’s picture

Emily Newton

Emily Newton is the editor-in-chief of Revolutionized, an online magazine exploring the innovations disrupting the scientific and industrial sectors.