How to Achieve Today’s Sustainability Goals While Improving Operational Performance
By 
Brittany Ebaugh
3131-AugAugAug-2121
Striving for improved sustainability goals with advanced analytics can have multiple benefits to your operation.

In today’s world, virtually no industry is operating without consideration of their impact on the environment. It’s no secret that process manufacturers have been scrutinized for contributing to greenhouse gas emissions and excessive energy consumption, so striving for sustainability can sometimes be seen as a forced hassle. In contrast, however; achieving enhanced sustainability at a process manufacturing organization can actually result in better operational performance and efficiency, saving time and money for the manufacturer. Two birds, one stone.

Defining our Goals: United Nations SDGs

In recent years, the UN created a set of seventeen Sustainable Development Goals (SDGs) to reach by 2030 in an effort to universally protect the planet. Of these are four that pertain particularly to process manufacturing companies and how they can contribute to the global effort:

  • SDG 6: Clean Water and Sanitation. Ensure availability and sustainable management of water and sanitation for all.
  • SDG 7: Affordable and Clean Energy. Ensure access to affordable, reliable, sustainable and modern energy for all.
  • SDG 12: Responsible Consumption and Production. Ensure sustainable consumption and production patterns.
  • SDG13: Climate Action. Take urgent action to combat climate change and its impact.

These four goals have become a guideline for the industry as a whole to craft corporate sustainability goals, and it’s evident that these have become a top priority. Besides the obligations that require companies to invest in sustainable processes, it’s also become known that changing operations to better align with these goals results in many other positive impacts.

Sustainability Doesn’t Happen in Spreadsheets

There are many challenges that process manufacturing teams face today in terms of meeting these sustainability goals. The first stems from the lack of tangible and actionable direction provided to team members at the plant, with broad guidelines set at a corporate level. Subject matter experts (SMEs) often do not have the resources within traditional data technology and methods to analyze their process data and make insight-based decisions to push their operation towards KPIs for improved sustainability.

The reality is that spreadsheets don’t provide any tools for efficiently contextualizing, cleansing, and analyzing data. Many teams spend numerous hours inside of spreadsheets trying to organize data for insight, leaving no time for actually making connections between the data that can lead to a reduction in waste, materials, or money spent.

Additionally, this method does not empower process manufacturers to make reliable predictions based on rapid and historical data. If an environmental violation happens, actions taken to correct it can only happen after it has occurred, and the opportunity to see what caused the problem can be missed.

Enter: Advanced Analytics

With advanced analytics applications, process manufacturing operations can generate compliance reports automatically, with up-to-date data from disparate sources, freeing up time to focus on environmental impact.

Beyond monitoring of data as it’s happening and opening a world of insight during incident investigation, the accessibility, presentation, and correlation of data contributes to effective predictive analytics. This can give teams insight into when unproductive downtime may occur and lead to wasted resources.

Advanced analytics can also provide SMEs with a better understanding of how process changes will affect the environment by reporting on KPIs geared towards specific sustainability measures and creating models to compare process performance and operating conditions to ideal levels.

Beyond this, advanced analytics makes it easy to share insight across an entire team—leaving the days of spreadsheet-sharing in the past. Results are error-free and accessible for the whole organization to maintain the same mindset, so regardless of level, everyone knows the company’s progress towards improved sustainability.

Applying Specific SDG Measures

Here are a few examples of ways that process manufacturers are utilizing advanced analytics to strive towards a better sustainability goals with lower impact on the environment, while also improving their operational performance.

The term “sustainability” can mean a lot of things, such as monitoring and controlling green house gas emissions, optimizing energy efficiency, implementing alternative energy sources, reducing waste and so on. These examples highlight the flexibility of Seeq; wherever you have environmental process data and would like to optimize your environmental performance, Seeq can be used.

SDG 6: Clean Water and Sanitation

Operations can avoid over-cleaning in clean-in-place (CIP) processes where sanitation materials can be unnecessarily used.

SDG 7: Affordable and Clean Energy

Process manufacturers are currently using advanced analytics to develop energy models and decrease total energy consumption, with minimal required capital expense.

  • Minimize Consumption during Downtime
  • Aggregate data to quantify the amount of electricity and water consumed while the process is not running
  • Identify when the consumption is high
  • Display results on a dashboard for continuous monitoring

SDG 12: Responsible Consumption and Production

Mass balance equations can be run continuously to track historical changes, providing an opportunity to find points where material is wasted.

  • Identify periods of Ideal Operation
  • Create a Model of Power Production that can be used to reference system degradation
  • Increase production and minimize costs by maintaining equipment when it becomes cost-justified

SDG13: Climate Action

Many organizations are increasing generation of renewables and adopting smart grid technologies to mitigate carbon emissions through advanced analytics. Aggregation of methane emissions from various data sources through the use of advanced analytics can identify or predict places where methane is leaked, down to detailed micro-levels within the operation.

  • Improved Emissions Reporting
  • Automatically identify pollutant detector excursion events
  • Model signal behavior during those events to calculate KPIs like max pollutant concentration or total pollutant released
  • Automate report generation, improve calculation consistency and reporting timelines

A Sustainable Future

It’s simple: Investing in a sustainability goals strategy is good for business. The efficient use of raw materials, less waste, and lower energy consumption both directly lead to an improved environment and your bottom-line. In addition, sustainable practices such as these can boost your reputation above the competitors in your industry. See how advanced analytics can work for your operation today.

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