AWS Partner Network (APN) Blog
Seeq’s Advanced Analytics on AWS boosts Manufacturing Sustainability
By Anton Beskhodarnyi, Ecosystems and GTM Director – Seeq
By Joey Meucci, Technology Partner Manager – Seeq
By Marco Masciola, Sr. Partner Solutions Architect, Sustainability – AWS
By Preet Virk, Principal Partner Solutions Architect, Industrial Solutions – AWS
![]() |
![]() |
More than 80% of manufacturing companies have sustainability targets as part of their corporate strategies. Despite commitments, manufacturing companies find it difficult to prioritize and justify hundred-million dollars investments in sustainability activities when compared to projects with an immediate return on investment.
Tracking carbon intensity (CI) in industrial processes is an important step to curb greenhouse gas (GHG) emissions, optimizing energy efficiency, ensuring regulatory compliance, and reducing corporate risk. These actions are vital to ensure sustainable operations and long-term environmental responsibility. Measuring Scope 1 (company-controlled CO2 equivalent emissions) and Scope 2 (CO2 equivalent emissions from energy use) requires data collection, real-time monitoring, and harmonizing standards across facilities. However, the carbon measurement process is challenging due to the varying disconnected operations and fluctuating energy intensity involved manufacturing products.
Life cycle assessment (LCA), following ISO 14040 standards, measures the environmental impact of a product or service throughout its lifecycle. In this blog, we explore three manufacturing use cases, showcasing how Seeq aids in reducing the manufacturing process’s LCA reporting workloads by 90% through real-time carbon tracking and analysis.
Seeq’s approach to carbon intensity tracking and reporting
Seeq is an industrial analytics platform built on AWS, enabling engineers and operation teams to improve efficiency and emissions reduction using time series data. Seeq’s secure cloud-based solution empowers real-time insights for sustainability-driven operational improvements by optimizing industrial processes.
A carbon intensity calculation engine provides organizations with digital resources they need to track their GHG performance against baseline and desired target trajectories. Seeq can builds complex and scalable CI calculation models with additional contextual information on assets, operating modes, products or materials to report energy consumption variations. Near real-time carbon intensity tracking provides manufactures the ability to monitor emissions directly based on activities taking place inside the manufacturing facility.
Manufacturing customers have adopted Seeq to solve the following sustainability use cases:
- Live access to process and energy consumption at manufacturing sites to calculate carbon intensity in near-real-time.
- Link supplier and customers to obtain a complete view of supply chain carbon emissions.
- Audit carbon intensity calculations to track and report emissions across an enterprise, down to the source data.
- Providing validated operations and sustainability data to other tools for streamlined environmental and life cycle assessment (LCA) reporting.
As shown in Figure 1, LCA is a scientific process used to measure the environmental impact of a product, service, or activity across its life cycle.
Figure 1: Cradle-to-gate life cycle assessment
Impact categories include global warming potential (CO2e emissions), ozone depletion, land use, and water acidification. Seeq’s advanced analytics offering can be applied to measure all of these LCA impact categories.
Due to corporate reporting and trade regulations, more industrial companies favor working with software vendors reporting LCA with precise and accurate primary data scores. Additionally, the EU’s Cross Boarder Adjustment Mechanism will require emissions tracking for a subset of heavy industries.
The next sections describe how Seeq’s analytics planform is applied solve three customer challenges.
Use Case 1: Accelerate LCA for a global chemical company
A multinational speciality chemicals company uses Seeq SaaS to build complex and scalable carbon intensity models to report energy consumption based on the manufacturing process. These models provide near real-time carbon intensity data from the plant floor, integrating time-varying process information into LCA models for automated analysis and environmental impact assessment. By integrating Seeq with LCA models, they reduced the time to perform LCA assessments by 90%, saving hundreds of staff-hours.
The customer uses Seeq to get access to primary emissions data (scope 1 & 2) like raw material use, water use, electricity and steam consumption. Customers compile individual data points from the manufacturing process to define the product’s environmental impact footprint. Seeq-processed primary emissions data is added by the customer into an LCA model defined using Sphera GaBi to finalize the overall product environmental impact following the methodology specified in ISO 14040. Seeq provides customers a way to measure emissions of their operations directly and relies less on secondary data to estimate emissions/environmental impact.
As a result, multinational speciality chemicals company closes the loop with Seeq to provide sustainability metrics such as ammonia, natural gas, steam or electricity usage. Seeq offers a tailored of carbon footprint for specific products and their components, both providing an overall outlook on resources usage.
This Seeq application helped the customer in their strategy of abating carbon emissions by 50%. Additions of contextual information into the analysis showed the customer how an energy consumption varied with operating mode or product type made. Near-real-time tracking against established targets provides the optimization insights required for continuous progress towards the future goal.
Use Case 2: Carbon Footprint Assessment with Open Hydrogen Initiative
In our second use case example, customer use Seeq to track the carbon intensity in accordance with the Open Hydrogen Initiative (OHI) protocols. Seeq, in partnership with Capgemini, developed a toolkit to automatically configure calculations and analysis using plant-specific historian tags and data for green hydrogen production. Site personnel use customizable Seeq Workbench and Seeq Organizer to monitor data from plant operations in near real-time. This allows engineers and analysts in energy producers to categorize hydrogen production as “green” or “blue” hydrogen based on the carbon intensity required for processing.
Using an OHI add-on supplied from Seeq, customers built a carbon intensity calculation workflow. The calculations apply to the facility’s time series data to identify underutilized resources to improve hydrogen production efficiency and create metrics dashboards. Manufacturers use these dashboards at multiple levels in the organization, from daily production meetings to monthly and quarterly reviews with operations managers and executives. Figure 2 shows example of the dashboard built in Seeq — with the tax credit amounts breakdown depending on the carbon intensity index of the production. This Seeq add-on configures the OHI calculation framework for a facility, based on a specific hydrogen production technology, using the facility’s data.
Figure 2: Carbon intensity dashboard in Seeq, OHI add-on
Use Case 3: Integrate AWS Sustainability Insights Framework with Seeq
Seeq offers customers the ability to track emissions in their manufacturing operations using the AWS Sustainability Insights Framework (SIF). SIF is carbon calculation guidance developed and maintained by AWS to help customers automate their emissions tracking workload using AWS services. Below figure shows how customers combining SIF with Seeq to automate carbon tracking of manufacturing processes.
Figure 3: Carbon intensity tracking using the AWS Sustainability Insights Framework
Seeq connects directly to the operational data stored on-premises (process historians, laboratory data, sensor data, etc) to include additional context based on from the emissions source for regulatory auditing purposes. This architecture permits Seeq to share carbon emissions information with authorized customers to support emission regulatory reporting, auditing, and traceability.
Pairing Seeq with Amazon SageMaker through SIF enables machine learning models to predict forward looking carbon trends based on scenarios, such as machinery upgrades or energy demand.
Conclusion
Seeq’s analytics platform, built on AWS, addresses critical sustainability challenges in manufacturing. With Seeq, manufacturers track carbon intensity in real time, streamline LCA analysis, and meet regulatory requirements. Through three customer use cases, we explain how Seeq reduce LCA reporting workloads by 90% for a global chemical company, implement carbon footprint assessment for green hydrogen production, and integrate with AWS SIF for emissions tracking.
Seeq empowers manufacturers to make data-driven decisions, optimize processes, and accelerate their sustainability transformation. This allows manufacturers to monitor, analyze, and report on their environmental impact, promoting their sustainable operations. Seeq SaaS on AWS can save thousands of man-hours for manufacturers that are looking to build the life cycle assessment and track carbon intensity with the direct primary data access. This solution enables process manufacturers to use industrial analytics with the combination of the machine learning and cloud data storage systems. Schedule a demo to see Seeq’s capabilities firsthand. Explore Seeq’s offering on AWS Marketplace.
.
Seeq – AWS Partner Spotlight
Seeq is a differentiated AWS Software Partner and holder of 3 AWS Competencies. Seeq is an advanced analytics solution for process manufacturing data that enables organizations to rapidly investigate and share insights from data in historians, IIoT platforms, and Amazon Web Services as well as contextual data in manufacturing and business systems.