“Do more with less” – the age-old mantra of the industrial world – is even more urgent now with the pandemic straining plants to unprecedented limits. Financial resources are tight, supply chains are disrupted, uptime expectations remain high, and the challenge of recruiting and retaining skilled maintenance talent continues to grow. Though it is harder than ever to remain productive and profitable, the demand for new efficiencies is relentless.
Plants can work smarter, not harder, with the right solution sets. The Tignis condition monitoring and analytics solution augments existing intelligence about connected mechanical systems, providing the ability to visualize emerging issues, resolve problems faster, and do more with less. Our physics-based approach melds the cloud, digital twins, modeling, and machine learning (ML) to automate and simplify otherwise labor-intensive processes.
Efficiencies by design
Tignis’ efficiencies are built into the solution at multiple levels:
Automated monitoring: Tignis continuously monitors massive quantities of incoming IIoT sensor data to automatically detect and report on anomalies, trends, and impending asset failures. It reduces dependence on plant floor personnel to watch and test for symptoms.
Remote analytics: The cloud-based platform enables remote access to high-speed analytics and high-fidelity diagnostics, providing crucial insights to authorized users wherever they are located. Unnecessary trips to the plant are avoided when decisions and actions can be handled remotely.
Intuitive intelligence: Tignis automatically brings attention to degradation, operational impacts, and root cause evidence, and provides access to multiple layers of supporting detail through an interactive, responsive user interface. Problem areas are visually narrowed to the affected components, piping, instruments, and process flows using a 2D digital twin of the mechanical system with overlaid sensor data. Compared to relying on traditional historians and HMIs, decisions made with Tignis are more informed and resolutions are timelier and more effective.
Work prioritization: Maintenance planners and schedulers can confidently prioritize work orders based on risk and asset criticality due to earlier warning of issues, higher-quality alerts, fewer false positives, and informed diagnostics. The ability to focus attention where it is most needed avoids mission-critical asset failure and the need for emergency maintenance.
Continuous improvement: Using ML and adaptive modeling capabilities, Tignis constantly learns your mechanical systems, adapts to evolving conditions and changing systems, and improves the identification, analytics, and diagnostics of condition anomalies.
Outsourced expertise: Tignis is a software-as-a-service (SaaS) solution, meaning all the expertise needed for optimal results is included. You can rely on our IT professionals, data scientists, and domain experts instead of staffing the roles internally. We facilitate real-time collaboration between your plant personnel and our subject-matter experts in order to accelerate and extend your return on investment.
Best-practice maintenance: By enabling preemptive actions for detected issues, Tignis helps plants to apply cost-effective, condition-based predictive maintenance (PdM) to improve asset reliability and performance. Costly run-to-failure and time- or usage-based preventive maintenance strategies can be limited to the least critical, disconnected mechanical systems or eliminated altogether.