Atlas Prediction Control (APC) has introduced a groundbreaking suite of process control solutions crafted to tackle specific challenges in control loop stability. These offerings are tailored to enhance performance in industrial chemical plants through three distinct engagement models: Atlas Advisor™, Remote Resident™, and Project-Based Engagements.
Tailored Engagement Models for Diverse Needs
Recognizing the varying operational challenges and resource capacities of different facilities, APC has structured its services to cater to a broad range of requirements.
The Atlas Advisor™ model provides continuous advisory services, offering real-time monitoring and performance assessments through Control Loop Performance Monitoring (CLPM). This subscription-based service is ideal for facilities seeking ongoing insights into their control systems without committing to a long-term project.
In contrast, the Remote Resident™ model involves a dedicated control engineer who acts as an embedded resource for the client. This engineer works remotely, overseeing Distributed Control System (DCS) integration and ensuring optimal controller performance. This model replicates the benefits of an on-site engineer while minimizing overhead costs.
Lastly, Project-Based Engagements focus on specific implementation needs with clearly defined objectives. These engagements can range from developing an Advanced Process Control strategy for a particular unit to conducting a comprehensive PID tuning and CLPM campaign for a segment of a plant facing persistent issues. The structured nature of these projects aligns well with capital project frameworks.
The Role of Atlas Advisor™ in Process Control
At the heart of APC’s offerings is Atlas Advisor™, an AI-powered tool designed to streamline the diagnostic process for engineers. Traditionally, plant engineers have spent significant time piecing together data from various sources to understand process changes. Atlas Advisor™ simplifies this by continuously monitoring plant conditions, correlating signals from APC, CLPM, and historical data to identify issues efficiently.
This AI-native application is engineered for deployment on the plant floor, ensuring reliability and speed in diagnostics. It integrates seamlessly with existing DCS, APC, and CLPM systems, providing valuable insights such as drift detection, root-cause identification, and corrective-action suggestions—all without reliance on internet access, which is crucial for facilities requiring isolated operations.
Initiating Engagements with Structured Diagnostics
Before establishing a specific engagement model, facilities typically undergo a structured diagnostic process. The Plant Performance Scan is a one-day assessment that evaluates a facility across several operational dimensions, providing plant leadership with a clear understanding of their control performance status.
For a more comprehensive evaluation, the Plant Audit offers an in-depth analysis. This includes a pre-visit data assessment, followed by a full day on-site to observe operations, conduct equipment inspections, and engage with personnel. The findings are then presented to the client, highlighting operational implications and a prioritized list of recommended actions.
These diagnostic evaluations guide facilities in selecting the most suitable engagement model, whether that be ongoing support through Atlas Advisor™, the Remote Resident™ engineer, or a targeted Project-Based engagement.
Comprehensive Technical Capabilities
APC’s engagement models share a consistent set of technical capabilities, ensuring that all clients receive high-quality support. PID tuning services address common issues such as controller detuning and oscillatory behavior, which can significantly impact product quality and operational efficiency.
Control Loop Performance Monitoring (CLPM) plays a critical role as it continuously assesses loop health, alerting operators to potential issues before they escalate. APC’s Advanced Process Control services go beyond basic functions, offering dynamic constraint management and coordinated control strategies for complex processes.
Moreover, the integration of machine learning and AI-driven diagnostics, particularly through Atlas Advisor™, enhances the ability of engineers to interpret data effectively. This technological support aids in identifying the root causes of variability—be it mechanical, procedural, or control-related—ensuring that corrective measures target the underlying issues.
Tackling Control Loop Degradation
Control loop degradation remains a significant challenge in continuous process industries, with studies indicating that many control loops operate below their designed intent, leading to unnecessary variability and off-specification production.
Madhur Bedre, the Founder and President of APC, emphasizes that the engagement models aim to provide practical solutions for plant teams, enabling them to eliminate variability effectively. Whether through ongoing advisory support, a remote engineer, or a focused project, the ultimate goal is to ensure that control systems perform as required and maintain that performance over time.
Conclusion
Atlas Prediction Control’s suite of process control solutions offers a versatile approach to resolving control loop instability in industrial settings. By understanding the unique needs of each facility and providing tailored engagement models, APC empowers plant operators to enhance performance and maintain operational excellence. This innovative strategy not only addresses immediate challenges but also fosters a culture of continuous improvement in process control.
- Tailored Solutions: APC provides distinct engagement models to meet diverse operational needs.
- AI Integration: Atlas Advisor™ streamlines diagnostics, making data interpretation faster and more reliable.
- Structured Approach: Comprehensive diagnostic offerings guide facilities in selecting the right engagement strategy.
- Technical Excellence: Consistent capabilities across models ensure high-quality support for PID tuning and control monitoring.
- Focus on Stability: APC aims to eliminate variability in control loops, enhancing overall plant performance.
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