ML Journal

Industrial leaders are turning to digital technologies to drive profits and cut emissions. 

 

TAKEAWAYS:
● Advanced technologies enable manufacturers to make informed, data-driven decisions that promote sustainability and energy savings.
● Sustainability in manufacturing involves reducing emissions and waste while creating business models that ensure long-term resilience.
● Manufacturers that embed sustainability into their business growth strategies will surpass their competitors.  

 

The mandate is clear: manufacturers must become more efficient, resilient, and sustainable—all at once. This challenge collides with new opportunities as emerging technologies provide the means to transform operations, reduce waste, and gain visibility across the value chain that was not possible in the past. As a result, sustainability is becoming a priority in industrial operations and digital transformation agendas.

In a recent Kalypso survey of sustainability executives, 96 percent indicated that digital transformation is essential for meeting their environmental goals, with nearly half describing it as business-critical.

Technology as a Catalyst for Sustainability

Technologies such as artificial intelligence (AI), machine learning, and advanced analytics are enabling manufacturers to optimize resource use, increase throughput, and reduce emissions—all while enhancing operational performance.

Implementing these technologies can yield several improvements:

• Streamlined production processes
• Increased volume with less energy
• Retention of more raw materials
• Gained insights on consumption and output

These advancements not only lead to significant energy savings but also create a pathway for achieving greater sustainability through smarter, data-driven decisions.

Demystifying Net Zero

Net zero refers to the balance between the amount of greenhouse gases (GHGs) produced and the amount removed from the atmosphere (Figure 1).

Figure 1: What are Scope 1, 2, and 3 Emissions?

The Greenhouse Gas Protocol categorizes GHG emissions into three categories:

• Scope 1: Direct emissions from owned or controlled sources such as fuel combustion and company vehicles.
• Scope 2: Indirect emissions from the generation of purchased electricity, steam, heating, and cooling consumed by the reporting company.
• Scope 3: Indirect emissions from purchased services and materials, including raw materials, components, and consumables.

Reducing emissions across all three categories requires end-to-end traceability, real-time data, and system-wide optimization—capabilities that only advanced digital technologies can deliver at scale.

Sustainability and the Digital Thread

A powerful enabler of this transformation is the digital thread, which provides a continuous flow of data connecting every stage of the product life cycle. By embedding sustainability into this thread, manufacturers can enhance visibility, traceability, and control throughout the value chain. This integration facilitates effective decarbonization across Scopes 1, 2, and 3.

Although the concept of the digital thread is not new, the technologies that support it—such as cloud computing, edge computing, and AI—make energy savings more attainable and scalable than ever before. Several key sustainability use cases enabled by these technologies are illustrated (Figure 2).

Figure 2: Digital Thread Powering Sustainability

Case Study: Impactful Smart Facilities Management

In the quest for more efficient energy management, integrating IT and OT systems has proven to be a game changer. Smart building technologies optimize energy usage, leading to significant reductions in energy costs. Let’s examine an example from our collaboration with a major steel manufacturer to enhance its utility system and relieve pressure on its energy grid.

Previously, the company’s data collection method was tedious and manual. It involved downloading information from meters and the utility company, then correlating it with historical data and hypotheses based on past research. This backward-looking approach was not only time-consuming but also limited the company’s ability to derive actionable insights.

Recognizing the need for a more dynamic solution, we assisted the steel manufacturer in transitioning to a smart facilities management system. This new approach involved deploying a real-time energy management system that meticulously tracked the generation and consumption of water, air, gas, electricity, and steam (WAGES) across the plant. The redesigned infrastructure provided real-time insights that enabled the company to optimize energy usage, reduce costs, and ensure that production line assets operated efficiently and at full capacity.

The steel manufacturer realized several benefits:

• The real-time data allowed for immediate adjustments and optimizations, leading to a more responsive and efficient energy management process.
• It was able to identify and address inefficiencies promptly, resulting in substantial cost savings.
• The improved performance of production line assets contributed to a smoother and more reliable operations, further enhancing overall productivity.

The manufacturer attributed its improved performance to financial benefits and a positive return on investment. This case study underscores the transformative impact of smart facilities management and the critical role of IT/OT convergence in driving energy efficiency and cost savings.

Creating Sustainable Business Models and Ecosystems

The push for sustainability in manufacturing and across the value chain is not just about reducing emissions or waste; it’s also about creating business models that support long-term resilience and growth. A sustainable business model requires a holistic approach that considers environmental impact alongside economic and social factors.

Circular business models design products and operations for reuse, recycling, and remanufacturing, with the goal of keeping materials in circulation for as long as possible.

Digital technologies play a central role in this transition. AI and data analytics can pinpoint inefficiencies, predict maintenance needs, and guide product design for easier disassembly or reuse. Machine learning can help identify new opportunities for circular innovation.

Digital Transformation and Sustainability

Digital transformation and sustainability are no longer separate agendas; together, they are reshaping how industrial businesses create value. The convergence of AI, cloud computing, edge computing, and data analytics allows manufacturers to optimize production, reduce emissions, and improve margins.

Sustainability isn’t just about compliance or brand reputation; it’s about cost optimization, operational agility, and growth.

In the critical pursuit of net-zero goals, the technology integration is transforming industrial operations, improving efficiency, and reducing waste and emissions. By using tools like machine learning and data analytics, manufacturers can optimize resource use and streamline production, leading to energy savings and better material retention. Advanced digital technologies also enhance visibility throughout the supply chain, helping organizations decarbonize across Scopes 1, 2, and 3, and attain compliance with emerging regulations such as the Digital Product Passport.

The time to get started is now. Companies that address sustainability’s role in their business growth will outpace the competition.  M

About the authors:

 

Rodrigo Alves is senior manager and lead of Kalypso’s Energy Management and Sustainability services.

 

 

 

Austin Locke is principal and global lead of Kalypso’s Data Science practice.