E-LLUM INDUCTION TECHNOLOGY
E-llum Technology is patented by E-Wenco and is based on the principles of electromagnetic induction applied also to non-ferromagnetic metals such as stainless steel, aluminium, titanium, copper, etc...
After years and years of both basic and applied research, we have been able to apply a still little-known physical principle and create a system of rules to make any metallic, non-ferromagnetic material suitable for heating by electromagnetic induction with efficiencies of over 90%. We call this great achievement the COMPATIBILITY PACK and it contains the 3 major physical, chemical and mechanical rules, which constitute E-Wenco’s exclusive know-how.
E-LLUM RULES
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Rapid Heating: Thanks to its lightweight design and careful study of the thermal process variables, E-llum Technology offers unprecedented rapid heating up.
Thermal Shift: Moving from the electric axis to the thermal axis ensures efficient performance.
Lightweight and Thin: E-llum Technology is both lightweight and thin, making it ideal for various applications.
Wireless Control: E-llum Technology features wireless capabilities, providing perfect thermal control and feedback integration.
Optimal Thermal Footprint: Its precisely engineered thermal footprint ensures perfect performance.
Durability: With no wear and simple maintenance, E-LLUM guarantees long-lasting and reliable operation.
KEY CONCEPT
- The advantages of E-llum technology are: speed of response, heat generation over large surfaces, controllability, greater homogeneity, possibility of tracking heat demand, fewer limitations in the choice of heat generator shapes, modularity, high heat exchange.
- The disadvantages of electromagnetic induction are the cost of the electronic control unit, emission of electromagnetic waves and the requirement for EMC certification.
ARTIFICIAL INTELLIGENCE (AI) PLUS
E-llum Technology is suitable for artificial intelligence because it is equipped with numerous sensors that provide feedback. E-llum Technology itself offers feedback, allowing integration with neural networks in the process. Unlike electric resistances, E-LLUM responds to process changes.