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COP28: Racing Toward Net Zero Operations with Data-Driven Insights

Improving process performance also leads to carbon footprint reduction.

BLOG POST

COP28: Racing Toward Net Zero Operations with Data-Driven Insights

Improving process performance also leads to carbon footprint reduction.

In preparation for the COP28 climate summit, a dialogue on reducing the global carbon footprint is taking shape. Scheduled for Nov. 30 through Dec. 12, 2023, this summit represents a turning point in the race to achieving net zero operations. It will be the first time since the Paris Agreement in 2015 that member countries will evaluate how well they are doing. According to the agreement, countries must reduce their carbon emissions by 45% within the next six years—and achieve net zero by 2050.

Manufacturers can be a lap ahead in the race to net zero by using operational data to improve process performance. Generated from sensors located throughout the plant, this data contains information that can help engineers optimize production and simultaneously achieve a reduction in carbon emissions. Examples include reducing batch cycle times, managing energy-intensive processes, and improving product quality to eliminate waste.

The Data-Driven Path to Net Zero

The number of companies pledging to reach net zero targets nearly doubled between 2019 and 2020. However, a survey in October 2023 revealed that only 4% of publicly listed companies worldwide are on track to meet the global temperature goals set by the Paris Agreement.

Despite progress in clean energy, the global reliance on fossil fuels remains a significant barrier. The chemical industry, for example, accounts for 2% of global greenhouse gases because of its need for feedstock fuel. Still, the United Nations Framework Convention on Climate Change has been unambiguous about the urgency of this mission. Achieving net zero global greenhouse gas emissions by mid-century is non-negotiable.

To align with these objectives, companies must take definitive action, such as:

Setting emission reduction targets consistent with global temperature goals

Implementing strategies across operations and supply chains focusing on renewable energy and energy efficiency

Maintaining transparency through regular reporting and reviews

Countries and industries are encouraged to take even more actions to keep global warming below 1.5 degrees Celsius. Many are already making progress with the help of operational data.

Sustainability Success Stories

Engineers who use operational data to optimize process behavior find they also reduce carbon emissions by as much as 20%. The improvements also help them reduce consumption of water, air, gas, and steam (WAGES), which further strengthens a commitment to sustainability. Examples include:

REDUCING ENERGY USAGE BY OPTIMIZING A CONVEYOR BELT

Conveyor belts are the lifeline of a coal mining operation, but they are heavy consumers of energy. Cleaning them at regular intervals improves their performance, which reduces their fossil fuels reliance. Engineers at one mine decided to change from fixed cleaning intervals to performance-based cleanings. First, they established the belt’s throughput and its energy consumption in relation to that throughput. Then, they created a new operating zone. When the belt operated outside this zone, engineers knew it was time for cleaning. Energy usage of the conveyor belt fell by 6% while the average time between maintenance periods increased by 11%.

DEVELOPING ENERGY BALANCE MODELS FOR CONDITION-BASED MONITORING

The normal production of 17 bar steam was not enough to cover demand at a chemical company that produced it in an aftercooler. This was the case even when both chambers operated simultaneously. Engineers wanted to monitor for periods when 17 bar steam consumption was excessive. After calculating the steam balance as a new formula that summarized the average steam consumption, they developed soft sensors with a monitor that sent notifications when 17 bar steam consumption was above average. This allowed them to change the process in time to prevent a shutdown.

MONITORING THE RELATIONSHIP BETWEEN WIND SPEED AND POWER GENERATION

Energy companies that operate wind farms must ensure they are generating the most power they possibly can in relation to the wind. This requires using operational data to find the good operating zone from the cut-in speed to the cut-out speed of wind turbines that produce electricity when they turn. The operating zone then needs to be monitored. When an anomaly does occur, engineers receive an alert that lets them know they have lost correlation between the wind speed and turbine production. This allows them to find the anomaly or reboot the system to improve performance.

CREATING ANOMALY DETECTION MODELS

Some anomalies are much more difficult to detect and predict. An anomaly might happen even when a process appears to be functioning normally. For these more involved cases, data scientists can apply a machine learning (ML) technique known as an anomaly detection model. In one case, fluid from a chemical process occasionally leaked into a compressor and damaged it. This led to a full-plant shutdown and significant loss of production. To resolve the problem, engineers first attached vibration sensors to the compressor. They then collaborated with data scientists to use the soft sensor data to train the model with different types of vibrations. They also were able to create an ML tag that acts as a monitor for irregular vibrations. When the anomaly was detected, operational experts received an alert with enough time to make changes before the compressor was damaged and a complete shutdown occurred.

The Race to Net Zero Starts with Operational Data

As the world converges for the COP28 climate summit, the role of operational data in reducing the carbon footprint across industries is more important than ever. From helping engineers set predictive maintenance schedules to aiding in the development of advanced anomaly detection models, operational data is helping companies stay ahead in the race to achieve net zero emissions. With the help of advanced industrial analytics, engineers and data scientists are using operational data to create a healthier and more sustainable planet.

BLOG POST

COP28: Racing Toward Net Zero Operations with Data-Driven Insights

BLOG POST

COP28: Racing Toward Net Zero Operations with Data-Driven Insights

The Data-Driven Path to Net Zero

Sustainability Success Stories

REDUCING ENERGY USAGE BY OPTIMIZING A CONVEYOR BELT

DEVELOPING ENERGY BALANCE MODELS FOR CONDITION-BASED MONITORING

MONITORING THE RELATIONSHIP BETWEEN WIND SPEED AND POWER GENERATION

CREATING ANOMALY DETECTION MODELS

The Race to Net Zero Starts with Operational Data

Achieve Better Operational Storytelling with a Connected Factory

Navigating the IT/OT Convergence in Pursuit of a Smart Factory

Reap the Benefits of Operational Insights in a Data-Driven Factory

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BLOG POST

COP28: Racing Toward Net Zero Operations with Data-Driven Insights

BLOG POST

COP28: Racing Toward Net Zero Operations with Data-Driven Insights

The Data-Driven Path to Net Zero

Sustainability Success Stories

REDUCING ENERGY USAGE BY OPTIMIZING A CONVEYOR BELT

DEVELOPING ENERGY BALANCE MODELS FOR CONDITION-BASED MONITORING

MONITORING THE RELATIONSHIP BETWEEN WIND SPEED AND POWER GENERATION

CREATING ANOMALY DETECTION MODELS

The Race to Net Zero Starts with Operational Data

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