Watts Up? Leveraging AI & Data for Energy Management

"Energy Management is key to building resilience in the manufacturing industry. The main drivers are increasing energy costs and regulations such as the Energy Efficiency Directive. However, the old management wisdom applies: You can’t manage what you can’t measure.

Organizations need to have unified, granular, vendor-agnostic and real-time data insights on their energy costs, energy consumption and carbon footprint, not just for reporting but for optimization at scale.

In this session you will learn about an award-winning, real-life AI & data-driven project to build resilience by reducing energy costs, increasing energy efficiency and improving the carbon footprint for Bosch Rexroth’s model factory in Ulm, implemented by Splunk/Cisco and Consist. For this project, Bosch Rexroth won the Industry Innovator Award.

In a first step, the project team focused on the most energy intensive machine in the production and provided visibility on key energy metrics.

In the second step, the team enabled optimizations at scale by tackling three key levers involving AI/ML models with prediction, forecasting and alerting elements: Pricing (peak management), availability (standby) and timing (operations scheduling).

In a third step, the flywheel interaction between Splunk/Cisco’s energy management solution and Bosch Rexroth’s Factory Orchestration Platform (FOP) is going to be established for continuous optimizations.

As a result, the following savings were achieved - without compromising performance, quality and time requirements:

• Energy cost (EUR): 20-30 %

• Energy consumption (kWh): 10-15 %

• Carbon footprint (CO2e kg): 25-30 %