v COVID-19 and the Necessity of Remote Plant Management - Tignis

COVID-19 and the Necessity of Remote Plant Management

Author: Jon Herlocker

Category:

Remote plant monitoring

Companies around the world have called for their workforce to work remotely during these uncertain times. This new, pandemic-affected reality adds urgency to the need for remote machine monitoring and diagnostics. On top of ongoing industrial challenges such as ever-tightening budgets and an aging workforce, manufacturers and operators are now dealing with social distancing and sheltering in place to avoid the spread of a novel coronavirus.

These times require a more flexible approach to plant management – including remote work. A key next step for industry leaders in addressing this challenge is to become familiar with the tools and technologies that can support these operational and cultural changes. Fortunately, the options are improving every day – literally – thanks to machine learning (ML). Applying ML and digital twins to automate condition monitoring of assets and whole processes can enable better process management from any location. Service-centered solutions allow you to work closely with subject matter experts (SMEs) no matter where you are at the time.

Heightened intelligence and visibility

In these challenging times, the Tignis team is here to help. We can enable modeling and remote monitoring of complete mechanical systems – not just the individual assets. A digital twin or replica of your system can be quickly constructed based on your existing historian sensor data and piping and instrumentation diagrams (P&IDs).

ML algorithms use the physics of flow to study patterns and anomalies in your system, whether it’s fluid, electricity, mechanical energy, or heat flow. ML and digital twins can help automate the prediction, identification, and notification of risks to reliability and efficiency, and formulate recommended diagnoses and corrective actions. System and component statuses, problem areas, and problem causes are presented in the dynamic, searchable digital twin, helping reliability engineers to validate and act on the diagnostics, which are continuously improved by ML.

Optimized for on-site and remote workers

Authorized users can login to Tignis’ cloud-based solution anytime from anywhere with an internet connection and browser. They are alerted to conditions requiring attention, shown only relevant information, and can easily access deeper layers of data when needed.

At a glance, they can visualize the flow, pressure, connectivity, and status of the sensors and systems, how they are performing live with current sensor data overlaid, and the lead-up to problems with a P&ID time slider. Decisions can be made within minutes – even by those with minimal training. This approach is far faster than researching disparate P&ID schematics, historians, and trend charts, and nothing is paper based.

Expertise on tap

Paired with the ready-to-use ML solution is access to Tignis’ SMEs and data scientists. Our team can answer industry or technology questions, provide software guidance, and implement suggested improvements. We understand plants are dynamic with ever-evolving technologies, systems, personnel, and production objectives, so we not only provide immediate value, but also actively enhance the solution based on valued customer feedback.

With COVID-19 catapulting the need for remote work into the spotlight, it is important for business leaders to plan for a safe, efficient, and productive future. On behalf of the Tignis team, we would be honored to help.