Asset Performance Management
INGENERO’s Innovative Solutions for overall Asset Performance Management and Reliability using Applied AI
In today’s industrial landscape, the reliability of critical assets such as exchangers, compressors, and pumps is paramount for ensuring uninterrupted operations and maximizing productivity.
Traditional methods of monitoring and managing these assets often fall short in providing timely insights and predictive capabilities, leading to costly downtimes and inefficiencies. However, with the use of its Applied AI solutions, INGENERO is revolutionizing asset performance monitoring and management, offering unprecedented levels of reliability and efficiency.
These solutions help manufacturing units operate more efficiently, maximize their capacities and production rates, lower maintenance and operating cost, reduce plant down times, improve safety and sustainability metrics and increase ROI (i.e.Return On Investment). These solutions can be applied at a single unit or across multiple plants and provide an overview of equipment health.
Features of INGENERO’s Asset Performance Management Solution:
Enhancing Exchanger Performance
Exchangers play a crucial role in various industrial processes, facilitating heat exchange between fluids. However, issues such as fouling, corrosion, and inefficiencies can significantly impact their performance. INGENERO with its HMS-X soluton for exchangers employs advanced AI algorithms to continuously monitor exchanger operations, detecting anomalies and predicting potential failures well in advance. By analyzing real-time data streams, including temperature, pressure, and flow rates, their AI-based solutions enable proactive maintenance interventions, optimizing performance and extending the lifespan of exchangers.
Optimizing Compressor Operations
Compressors are vital components in industries ranging from oil and gas to manufacturing, responsible for maintaining optimal pressure levels in various processes. However, factors like wear and tear, fluctuating demand, and suboptimal operating conditions can compromise their reliability. INGENERO's with its HMC-C solution employs an AI-driven approach and leverages machine learning models trained on historical and real-time data to forecast compressor performance and identify inefficiencies. By monitoring key parameters such as vibration patterns, discharge pressure, and energy consumption, their solutions enable pre-emptive actions to mitigate potential issues, ensuring continuous operation and reducing maintenance costs.
Maximizing Furnace Efficiency
INGENERO’s HMS-F solution employs latest ML/AI analytical techniques for enhancing furnace operations. Operations can monitor and track furnace health in real time and detect health/performance degradation such as coke formation during thermal cracking. HMS-F solution provides insights and intelligence for operators to take action to arrest further deterioration and extend furnace run length.
The solution defines threshold limits for an furnace representing its end of run limit and provides notifications accordingly on time remaining, thereby improving scheduling, maintenance, and operations.
Use Cases
Oil and Gas
Oil and Gas
Petrochemical
Petrochemical
Refining
Refining
Power And Utilities