By Dr. Paige Marie Morse, Industry Marketing Director, Aspen Technology, Inc. an asset optimization software company.
Sustainability is a hot topic these days, even as countries continue to address the challenges of the global pandemic. The long-term implications of the impact of company operations on the local environment and communities cannot be ignored.
While the word sustainability typically leads to thoughts around curbing CO2 emissions and the corresponding targets and goals, there are other aspects of industrial environments that contribute to energy waste and require greater consideration.
Technology is an enabling solution for organizations looking to enhance overall energy management and address sustainability targets. Advancements in industry 4.0 technologies certainly offer significant improvement opportunities for the industrial world, enabling new efficiencies and more streamlined operations.
Digital simulation of process operations—often referred to as digital twins—provide visibility into energy use. Digital twins identify opportunities to reshape processes to make them more efficient, uncovering new configurations and process routes. These simulation tools also give organizations the ability to account for more energy savings in the design phase when scaling up an industrial plant, ensuring that sustainability is built into the entire plant lifecycle. And they also enable better energy choices in later revamps and expansion projects.
Simulation can also help companies identify opportunities to improve energy use at a site, such as applying heat integration to reduce steam consumption, and develop optimal plans for purchase, generation and distribution of utilities for existing and new facilities. For example, Korean chemical producer YNCC used simulation to reduce energy use by 12% and cut carbon emissions, saving $19.2 million per year.
In addition, process control solutions can help boost efficiency while also optimizing energy consumption. Brazilian chemical company Braskem used process control to stabilize production of an ethylene unit and lower energy consumption per ton of product by 20%.
Digital twins allow companies to track release of pollutants and greenhouse gases (methane, nitrogen oxides, etc.) in process design and possibly plan an alternate route with less emissions.
In addition, artificial intelligence (AI) technology can identify patterns in process and operational data that lead to equipment failure that can cause a surge in emissions. AI gives plant personnel time to address and fix the issues in advance, before they ever become a problem or impact the production process.
A European polymer producer used AI-enabled prescriptive maintenance to gain 27 days advance warning of a failure and avoided an unplanned shutdown and probable emissions release.
Innovations that lead to energy savings often result in other emissions reductions also, as efficiencies are improved throughout production. In addition to curbing energy waste, organizations can design plant processes that are specifically structured to reduce emissions and track progress while optimizing. In fact, the International Energy Agency highlights that industrial operations have the opportunity to reduce CO2 emissions by nearly a third by implementing process and energy simulations.
Reducing production waste is another important target for companies. However, much of material waste comes from poor quality end-product. When a product is flawed, often it cannot be sold and is categorized as waste material. The challenge with off-spec product is that there are so many different variables (many uncontrolled) that occur within any production process, that waste material is an inevitable output for many plants.
Multi-variate analysis technologies can change this reality. They can identify irregularities in production, in real-time, that might impact the end-product. Instead of trial and error, plant operators now have so much more control over processes as they happen. Advanced technologies give operators the ability correct irregularities before they impact (or ruin) the end-product. Ultimately, more quality end-product leads to less waste.
Mitsubishi Chemicals used multi-variate analyses of a batch process to eliminate off-specification production, which had been running at as much as 15% of production.
Historically, it has been challenging to effectively address issues of energy, emissions and material waste in the industrial world. However, modern technologies and innovations are finally being targeted at this important effort and finding significant success.
As successes are shared and companies gain confidence – and see the competitive advantage – technology and innovation will become critical tools for future success.