IT/OT Convergence for Sustainability in Manufacturing

We are living in the Net-Zero era, where companies and countries are running against time to achieve their decarbonization commitments. Achieving carbon neutrality across factories and industrial operations is imperative for the planet to meet the Paris Agreement’s goal of limiting global warming to 1.5°C and 2 °C above pre-industrial levels. According to the United Nations Industrial Development Organization, industrial emissions account for 30% of global GHG emissions.

To achieve this, digital solutions are merging information technology (IT) with operations technology (OT) to not only drive factory efficiencies but also to advance sustainability efforts.

Organizations need to implement technologies that converge their IT and OT data as they move closer to sustainable factories of the future.

Unlocking the Value of OT Data

The convergence of OT data from the factory floor with IT data in the cloud combines the traditionally separate data stacks with advanced analytics. This leads to data-driven decision-making that can impact the entire value chain.

However, integrating OT systems with IT platforms can be complex. OT data is often unstructured, fragmented, proprietary, and not easily integrated with IT architectures. OT devices generate vast amounts of data, requiring significant and scalable real-time data management and analytics to provide insights for critical decision-making. Integration must support robust security protocols to protect operations from disruptions.

When these challenges are overcome, we can drive optimization with improved operational efficiency, enhanced data analytics and better decision-making.

The same data and artificial intelligence capabilities leveraged for production optimization can be applied to sustainability. As regulations and ESG reporting increase in importance, the IT/OT convergence provides the data necessary for compliance and progress on corporate sustainability goals.

Additionally, advanced applications of Machine Learning Control (MLC) and AI models allow for real-time optimization of machines. These models continually fine-tune systems, seeking optimal performance in energy efficiency, emissions reduction, production output, and product quality.

IT/OT convergence can be achieved with various technologies—IoT, edge computing, automation, cybersecurity, interoperability standards, cloud computing and data analytics. Organizations worldwide have demonstrated the resulting real-world impact of combining digital technologies with advanced automation solutions.

Case Study: Data-Driven Decisions Improve Sustainability

Microsoft and Rockwell worked with a global tire producer to implement a MLC model to drive new approaches to a key energy- and material-intensive process. A MLC model is a control system that uses machine learning algorithms to generate models that are more complex than a traditional linear system. The model continually improves as it ingests more data. The company wanted to balance production and quality variables across the entire line to see where the overall process—from raw materials to the final tire—could be optimized, whilst also achieving energy savings.

The redesigned process exceeded the original goals of streamlining without impacting product quality. The company achieved a 5 to 10% improvement in material retention and a 15 to 20% increase in scrap recovery along with a drastic reduction in energy needed per tire. These optimized processes and sustainable outcomes could be scaled across the enterprise, driving down costs and improving decarbonization results globally.

Case Study: End-to-End Visibility Supports Sustainability

IT/OT convergence can provide end-to-end visibility and traceability across the supply chain. Microsoft and Rockwell worked with an organization managing wastewater removal from oil and gas extraction. They operate more than 1100 miles (about 1770 km) of pipelines that move nearly 2,000,000 barrels of hazardous wastewater daily. Control room operators spent at least 30% of their shift viewing continuous video feed streams to monitor the pipelines for potential leaks.

The company wanted to implement fast, high-accuracy models that could detect anomalies down to the difference between rainwater and wastewater across the pipeline and trigger real-time action alerts. They deployed a solution based on high-accuracy vision AI models using data gathered via cameras with thermal, FLIR, and motion detection abilities.

By automating the detection and notification process, control room operators switched from manually viewing video feeds to efficiently responding to more high-value leaks. This not only saved time spent on these manual activities, but it also mitigated serious environmental damage and regulatory fines that impact business reputation.

Case Study: Smart Facilities Management Automates and Reduces Energy Consumption

Through IT/OT convergence, smart building systems can optimize energy systems more efficiently to reduce energy costs. To help save energy costs, a large steel manufacturer worked with Microsoft and Rockwell to optimize their utility system and reduce strain on their energy grid.

Gathering data was traditionally a manual, backward-looking process of downloading data from meters and the utility company constructing correlations with historical data and hypotheses based on past research.

By moving to a smart facilities management solution, the company deployed a real-time energy management system that tracked their water, air, gas, electricity, and steam (WAGES) generation and consumption across the plant. A redesigned metering infrastructure provided real-time insights to optimize energy usage, reduce costs, and ensure production line assets worked efficiently and at full capacity. The company attributed the improved performance to monetary benefits and a positive ROI.

Link the Factory Floor with the Cloud to Unlock Sustainability Results

As Rockwell’s digital services arm, we continue to drive innovation with Rockwell and partners like Microsoft in the use of IT/OT convergence to move manufacturers closer to a sustainable factory of the future.