2Q - Can you give us some practical examples of Analytics and AI in manufacturing?
The recent advent of technologies, computing, and networking innovations, such as the Industrial Internet of Things (IIoT), is fueling new ways to address industrial complexities and better use the power of data. This phenomenon allows us to apply AI to industries by combining it with specific industrial domain expertise (for example, in cement, food & beverage, metals, mining, pulp & paper, etc.) for safer, smarter, more efficient, and sustainable industrial operations. Using the potent combination of specific industrial domain expertise, contextual data, advanced technologies, and AI algorithms, one can extract far greater value than the individual silos would ever be able to generate.
For example, the cement industry faces various challenges in its day-to-day operations around profitability/cost control, quality vs. throughput, emissions, and environmental Sustainability, etc. Advanced data analytics and smart optimization powered by AI will allow cement producers to hit key performance indicators around Sustainability, process performance, asset performance, connected workers, and operational excellence. Let's look at Sustainability. AI can be vital in reaching environmental sustainability targets, reducing emissions, and optimizing energy and management.
For instance, ABB's AI-based system anomaly detection app learns about the plant and equipment's "normal" states and uses adaptive setpoints to detect unusual patterns and anomalous behaviors. By triggering alerts, it reduces the effort to identify and rectify energy consumption deviations—no more hassle of setting manual setpoints or alarms, no more notification overload.
Let's take the Mining Industry for example. ABB is installing its enterprise-grade digital platform ABB Ability Genix Industrial Analytics and AI Suite to enable Gold Fields' Salares Norte project in Chile to drive efficient, sustainable, remote operations. With the technology, Gold Fields will gain data insights that will help them to increase industrial productivity and operational excellence while reducing costs. Remote connectivity will help reduce the number of people needed at the actual mine location, thus improving safety.
3Q) What is the role of industrial software solutions in reducing energy costs and emissions?
Designing, deploying and maintaining the optimal site-wide or enterprise-wide energy management and emission control strategy is a significant engineering and operational challenge, one that requires a wide span of competencies, engineering tools, architecture approaches, and service capabilities to identify the most performing and cost-effective solution for each process area and site.
The whole energy system is evolving, enabled by Digital. Harnessing digital solutions is fundamental to decarbonizing industry while still delivering on traditional priorities like agility, safety, and overall equipment effectiveness.
Industrial software solutions enable a modular approach for deploying a solution for energy management that typically includes monitoring energy usage at plant and process levels with real-time visual displays and data, identifying the best performance of process areas and opportunities for improvement, reporting energy consumption patterns of process areas and production lines, analyzing inefficiencies in plant and process areas, forecasting energy consumption schedules for process areas based on production plans and measured consumption and solving economic real-time optimization problems consisting of own generation, trading and using of energy in industrial plants and power plants