System Monitoring

In the era of Industry 4.0, manufacturers are embracing data-driven insights to enhance their compressed air performance. With Gardner Denver’s iConn, a cloud-based air management platform under the CompAir brand, operators gain the ability to manage, optimize, and improve their compressed air-based services. Discover how iConn is meeting the demands for intelligent insights and revolutionizing the industry.

Advanced Analytics for Proactive Control

iConn delivers advanced analytics that put operators firmly in control of their compressed air installation. With access to historic, real-time, predictive, and cognitive analytics, users can identify potential issues before they occur. Learn how iConn’s powerful analytics provide the proactive control needed to rectify problems and improve overall performance.

Secure Data Transfer

Explore the secure data transfer options available with iConn. Whether it’s GSM, Ethernet, or Wi-Fi, your compressor and ancillary asset data remain protected. Access real-time analytics and valuable data through open APIs, putting you in control of your compressed air system like never before. And with the expertise of CompAir professionals, make informed choices about compressor air optimization, maintenance schedules, and energy performance.

Learn how iConn is seamlessly integrated into new CompAir machines and can also be retrofitted to existing compressor installations. Moreover, the system extends its support to ancillary and non-Gardner Denver products, offering a comprehensive digital experience for managing your compressed air system. Experience the convenience of real-time email and text notifications, keeping you informed about machine fault codes.

Go beyond monitoring with iConn’s machine performance insights. Continuous data analysis reveals predictive and prescriptive performance improvement opportunities to meet your air production needs. The visually appealing data presentation offers a snapshot of your compressor’s health, enabling quick decision-making.