The digital furnace model will be used throughout the project to guide placement of sensors, analyze radar data, and report the condition of your refractory block by block. If you would like to see an example of the the interactive report that you will receive, visit the sample report link below.
Thank you for submitting the Pre-project Questionnaire. Here’s what to expect next:
Digital Furnace Model
Project Kick-off Call
Before on-site work begins, we will create an inspection plan that designates specific areas of the furnace for data collection each day. We will also schedule a project kick-off call with your team to review and confirm details of the project.
Your project will begin with data collection on-site.
Furnace Labeling
Our team will guide plant personnel through labeling each section of the furnace to correlate with the digital furnace model.
Training
We will train your personnel how to use SmartMelter® sensors. We will also send you a final request for operational details, called the Furnace Passport, that is required for your final report.
Radar Signal Acquisition
Data will be collected by acquiring a signal on each block of the furnace according to the inspection plan, guided by a handheld device.
Our Data Analysis Team will provide quality control and analysis.
Data Validation
The advanced radar algorithms will be received and validated by a team of Furnace Radar Experts for quality control. The team may request daily “retakes” of radar signals at specific points.
Analysis and Interpretation
Furnace Radar Experts will interpret the radar algorithms to produce measurements for each block in the virtual furnace model. The final data will be reviewed and approved by a team of advanced engineers with PhD degrees.
Deliverables
We will send you an interactive report utilizing the digital furnace model.
We will meet with your team to review results.
Teleconference
Teleconference is scheduled for all stakeholders. Inspection results are presented visually using the digital furnace model.
Recommendations
We will make maintenance and repair recommendations based on data and human expertise.