Sustainability is critical to the health and survival of our planet, and now, more than ever, companies are prioritizing it as part of corporate social responsibility initiatives. According to a recent McKinsey survey, more than 50 percent of executives believe sustainability is very or extremely important for brand reputation and overarching corporate strategies. Unfortunately, only 30 percent of those executives believe their companies actively invest in sustainability or have implemented measures to reach goals. While many companies set goals, the ability to affect change often fails to trickle down the front-line employees who can make the most difference.
While demonstrating how data can enable sustainability efforts is critical, actually achieving those goals, particularly in process manufacturing, requires engagement of the entire workforce. Many process manufactures are investing in things like carbon capture, alternative energy, or other sustainability initiatives. This often results in specialized and siloed teams, with process engineers left out of the equation, typically because engineers and subject matter experts lack easy access to process data, resulting in outdated insights. Therefore, by the time they review reports, it’s too late to use that information to create a more sustainable operation.
The Limitations of Traditional Data Analysis Methods
Instead, these engineers and subject matter experts are often mired in compliance efforts. They spend multiple days per month aggregating data in Excel for monthly and quarterly compliance reports. Compliance is certainly important, but organizations must do more than just comply to go net zero. Focusing solely on compliance results in the organization reacting to environmental excursions only after they are identified during the monthly or quarterly reporting.
It’s clear that organizations care about sustainability, but goals must be backed by tools and resources to have a lasting impact. To get the most out of alternative energy, carbon capture, and more, companies must improve efficiencies by analyzing the data that’s already being collected, and by empowering employees at all levels to drive sustainable manufacturing.
Top Technology for Sustainable Data Analysis
Seeq enables process manufacturers across industries to gain contextualized insights from existing data and to share those insights with the broader organization so teams can take action and reach sustainability goals. Whether it’s electricity and water consumption monitoring, carbon capture, or air quality monitoring, Seeq customers are making big changes that net sustainable results.
Recently, Seeq was a co-sponsoring partner for a Microsoft Hackathon that focused on sustainability in manufacturing. Run by Microsoft Energy Core, participants used Seeq to integrate satellite, weather, and process operating data to identify and quantify methane emissions events and to characterize plume dispersion.
First, participants used Seeq’s contextualization tools to identify methane emissions events. Due to the sparseness of satellite emissions data, it was difficult to determine the exact length of an event, or the total mass emitted. To get this granularity and perform more precise calculations, participants used Seeq to analyze process operating data at the time of the events. This enabled them to determine the duration and mass emitted, identify early indicators, and characterize process disturbances causing the event. Lastly, once the events were identified and quantified, weather data was used to characterize plume dispersion (stable, unstable, neutral) at the time of the events.
Beyond the Hackathon use case, many of the world’s top oil and gas companies use Seeq to monitor and mitigate emissions, monitor chlorination systems, and decrease flaring emissions. In addition, some oil and gas companies have automated compliance reporting using Seeq, empowering process engineers to move beyond ‘after the fact’ analysis and take preventative action.
Making the Power Generation Industry Sustainable
Another example is power generation companies also use Seeq to gain access to timely insights to maintain critical assets. Alternative energy generation requires deployment of large-scale assets, including turbines and solar panels. Over time, environmental conditions, such as dust and rain, can soil solar panels and lead to generation losses. For one customer, quantifying these losses was difficult. To determine daily revenue, the customer used Seeq to build a model for solar panel tracker angles during a time when panels were clean and operating efficiently. The customer now uses Seeq to monitor degradation. Once performance drops below a set revenue threshold, maintenance is performed.
Seeq’s browser-based, self-service solution is specifically designed to create insights for time series data. Seeq connects to data sources, regardless of where data is stored, and does not duplicate or move data. With Seeq, engineers and subject matter experts can quickly cleanse and contextualize time series data to create insights, helping organizations reach sustainability goals.
To see the technology in action, schedule your demo today.