Danfoss
Canvas Category OEM : Electrical Equipment
Danfoss engineers solutions that increase machine productivity, reduce emissions, lower energy consumption, and enable electrification. Our solutions are used in such areas as refrigeration, air conditioning, heating, power conversion, motor control, industrial machinery, automotive, marine, and off- and on-highway equipment. We also provide solutions for renewable energy, such as solar and wind power, as well as district-energy infrastructure for cities. Our innovative engineering dates back to 1933. Danfoss is family-owned, employing more than 42,000 people, serving customers in more than 100 countries through a global footprint of 95 factories.
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Why Convergence of IT/OT Needs to Include ET
The increased sophistication of intelligent devices and associated software drive the need for tighter integration of the IT and OT domains to gain new insight from known information. However, in the digital data environment of IIoT, engineering technology, those technologies that create virtual models must be included in the convergence conversation. While inclusion of ET may have been implied in the past, its use in the current and future work environment cannot be underestimated as modeling tools become essential to managerial or technical decision making.
He shared a real-world example of IT/OT/ET converging at Lilly. An HMI graphics card needed replacement due to a defective component. The replacement card required a driver that was incompatible with the existing version of Windows in that operation. A Windows upgrade would affect other applications. In this case, the obsolescence of a single component on a graphics card cascaded into a project to upgrade the HMI and all other affected applications and interfaces. This seemingly simple issue required extensive IT/OT/ET collaboration to solve.
In his presentation, Mr. Ruth shared an IT/OT/ET convergence story that has spawned a whole new service business Convergence of IT/OT Needs ETfor Danfoss, the Smart Store. Per Ruth, it’s all about Big Data and a new way of doing business enabled by IIoT technology to increase operational effectiveness and control, and reduce costs. This supplier of refrigeration equipment, compressors, and controllers for supermarkets required an integrated solution to help customers view operational data at a more granular level.
Danfoss completes acquisition of ENFOR’s district energy efficiency software
Danfoss has acquired ENFOR’s district energy software and will bring the solutions to the global market under the Danfoss Leanheat® suite of sustainable heating and cooling solutions. The Danfoss Leanheat® solution combines cutting-edge technology, data analytics, and artificial intelligence to optimize energy consumption and improve operational efficiency of district energy and buildings. Danfoss had been a minority shareholder in ENFOR since 2020. By fully acquiring ENFOR’s district heating software business, Danfoss enhances the capabilities and accuracy of its Leanheat network suite for district energy utilities to include data-driven temperature optimization, intelligent load forecasting and micro weather forecasting, which support district energy utilities and energy companies with their green transitions.
ENFOR is an innovative spin-off from the Danish Technical University and delivers solutions for forecasting and optimization of energy production and demand, incl. optimization of district energy systems. The potential of using data and machine learning in the energy sector is massive. The latest Danfoss Impact White Paper reveals that an ambitious but realistic roll out of demand-side flexibility technology in the EU and UK can save 40 million tons of CO2 emissions each year by 2030, more than Denmark’s domestic climate footprint.
Unlocking the Value Potential of Additive Manufacturing
Transitioning to AM requires not only a change in mindset but more importantly, the ability to quickly and easily identify which parts are best suited for the additive manufacturing process. This is where AI and machine learning are now bridging the gap between traditional AM –where most of its value materializes in the form of functional prototypes – and more advanced additive manufacturing operations. “We have upwards of a million part numbers,” said Werner Stapela, head of global additive design and manufacturing at Danfoss – an international leader in drives, HVAC and power management systems. “So, it would be impossible for us to manually analyze each one to determine whether additive manufacturing would either add value or reduce costs.”
“We have been utilizing 3D printing for decades, mostly for prototyping, but the Castor3D software allows us to focus on our end components and more specifically the costs associated with that,” added Stapela. The software’s algorithm and machine learning can scan thousands of parts at once by analyzing CAD files. It evaluates five factors: materials, CAD geometry, costs, lead time and strength testing to identify suitable parts for AM. The software can also make design for additive manufacturing (DfAM) suggestions regarding part consolidation and weight reduction opportunities.