Process KPI calculations and data validation
Checks process values and turns telemetry into usable engineering metrics for dashboard review.
Research Internship · Thermal Systems · 2026
POTTERS — Smart Monitoring for a Modular Sludge Dryer
A simulation-backed engineering prototype for monitoring a proposed portable thermal sludge-drying system. Built to support future plant instrumentation, performance analysis, alarm logic, and operator decision-making.
Problem framing
Engineering Challenge
The POTTERS physical system is conceptual and proposed, so the software work focused on preparing the future system for disciplined data acquisition, KPI tracking, abnormal-condition detection, and decision support before field hardware is available. The prototype treats simulated and sample data as an engineering proving ground: telemetry can be validated, drying-zone behavior can be compared, and future sensor/control requirements can be tested against realistic operating scenarios.
- Data readiness Validate incoming process signals before they drive decisions.
- Performance tracking Calculate KPIs tied to drying effectiveness and thermal behavior.
- Abnormal conditions Flag patterns that may indicate sensor, flow, or process issues.
- Operator support Convert findings into clear engineering recommendations.
Prototype scope
What I Built
6-zone × 5-probe dryer analysis
Compares spatial behavior across dryer zones and probe locations to surface uneven performance.
Rule-based findings and engineering recommendations
Translates modeled conditions into practical findings for instrumentation and control planning.
Synthetic/hybrid data workflow for testable dashboard development
Uses controlled sample scenarios so monitoring logic can be developed before live plant data exists.
Visual walkthrough
Project Gallery
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Next step
Interested in the engineering behind it?
Connect with me about monitoring, instrumentation, controls, or thermal systems work.