Process diagnostic platform targets plant performance and profitability
PlantESP from Control Station actively monitors regulatory controllers and simplifies root-cause analysis.
Control Station has announced the addition of new and advanced process diagnostic capabilities to the Company’s PlantESP solution platform. The enhancements expand PlantESP’s existing root-cause analysis capabilities and targets the 5% of production lost by process manufacturers due to poorly performing regulatory control systems.
Advanced diagnostics were recently extended with the introduction of an intuitive cross-correlation analysis capability. The new feature characterizes the interaction among and between PID control loops within a production facility’s regulatory control environment. Analysis is presented in an interactive matrix and it characterizes loop relationships as either leading or lagging. Combined with spectral analysis and other diagnostic tools, PlantESP provides users with a comprehensive toolkit for quickly and systematically correcting control-related issues that impact plant profitability.
“Process manufacturers lose 5% of their production value annually due to correctable control and asset reliability issues,” noted Rick Bontatibus, Control Station’s vice president of global sales. “That represents nearly $500 billion on a global basis. Whether in terms of controller performance or asset reliability, PlantESP is making it easier for manufacturers to realize their full potential.”
PlantESP helps process manufacturers reclaim significant economic losses associated with underperforming control systems and unplanned equipment failures. The platform’s loop performance monitoring module isolates the root-cause of controller performance issues which result in unnecessary energy consumption, production waste, and reduced output.
The company contends that with hundreds or even thousands of PID controllers at a typical production facility, the task of maintaining effective and efficient control can be overwhelming. Maintaining control has become increasingly challenging due to reduced plant staffing levels.
PlantESP addresses the challenges of diminished staffing levels and increased market expectations. Specifically, the platform’s loop performance monitoring module actively monitors control loops on a plant-wide basis and identifies PIDs that require service. PlantESP provides timely alerts and reports that target the unique information needs of operations staff and plant management. With advanced diagnostic tools such as cross-correlation and recommendations for corrective action, PlantESP equips users with guidance for resolving control-related issues quickly and for maintaining optimal production levels.
The PlantESP platform was originally launched in 2010 with a focus on PID controller performance. The loop performance monitoring module has been noted both for its intuitive design and for its contributions to improved plant-wide control. PlantESP was extended in 2011 with the introduction of the predictive analytics model, an innovative asset management tool that provides advance warning of equipment failure. Combined, the loop performance monitoring and predictive analytics capabilities address the growing need among process manufacturers for technologies that deliver reliable and actionable information.
Edited by Peter Welander, email@example.com
Case Study Database
Get more exposure for your case study by uploading it to the Control Engineering case study database, where end-users can identify relevant solutions and explore what the experts are doing to effectively implement a variety of technology and productivity related projects.
These case studies provide examples of how knowledgeable solution providers have used technology, processes and people to create effective and successful implementations in real-world situations. Case studies can be completed by filling out a simple online form where you can outline the project title, abstract, and full story in 1500 words or less; upload photos, videos and a logo.
Click here to visit the Case Study Database and upload your case study.