22 Steel Industry Onboarding Questionnaire – Kav AI Document Portfolio

22.1 Organization Information

Company / Operator Name: _____________________________________________
Division / Business Unit: _____________________________________________
Primary Contact Name & Title: ________________________________________
Primary Contact Email & Phone: _______________________________________
Secondary Contact Name & Email: _____________________________________
Plant Address: _______________________________________________________

22.2 Mill & Facility Overview

22.2.1 Industry Segment

Select all segments that apply to your steelmaking operations:

Integrated Steelmaking: Coke ovens, sinter plant, blast furnace, basic oxygen furnace (BOF).
Mini-Mill (EAF): Scrap yard, Electric Arc Furnace, ladle metallurgy furnace (LMF), vacuum degasser.
Continuous Casting: Slabs, billets, blooms, beam blanks, thin-slab casters.
Rolling & Finishing: Hot rolling mill, cold rolling mill, annealing, pickle lines, galvanizing/coating lines.
Foundry & Special Alloys: Specialized melting furnaces, sand/die casting, heat treatment.

22.2.2 Plant & Production Details

Mill / Facility Name & Site ID: ________________________________________
Physical Location (City, State/Province, Country): _____________________
Annual Production Capacity (Tons/Year): _________________________________
Average Daily Output (Tons): __________________________________________
Year Built & Major Equipment Upgrades: __________________________________
Operating Hours & Staffing (e.g., 24/7 continuous, shifts, maintenance days): __________________
Number of Major Production Lines or Shops: _____________________________

22.2.3 Asset Inventory

Check all asset types that will be monitored by the Kav AI platform:

Raw Materials & Handling: Conveyor networks, stacker-reclaimers, scrap yards, overhead scrap cranes.
Ironmaking & Coke Production: Coke battery walls, sinter lines, blast furnace shell, tap holes, stove networks.
Primary Steelmaking: Electric Arc Furnaces (EAF electrodes, shell), Basic Oxygen Furnaces (BOF vessels).
Secondary Metallurgy: Ladles (torpedo/transfer cars), LMF, vacuum degassing hoods.
Casting Machines: Tundishes, mold copper plates, mold level sensors, spray cooling chambers, roller segments.
Reheating & Forging: Reheating furnaces, walking-beam furnaces, soak pits, forge presses.
Rolling Mills: Roughing stands, finishing stands, backup/work rollers, runout tables, coilers, shearers.
Environmental & Safety: Baghouses (filter compartments), dust collectors, gas recovery holders, flare stacks.
Critical Auxiliaries: Cooling water pumping stations, air separation units (oxygen/nitrogen), electrical substation transformers, main hydraulic power packs.

22.3 Large Plant Scale and Remote Yards

Steel mills span vast physical areas. Please describe your spatial and campus-wide asset monitoring landscape:

Total Plant Footprint (Acreage/Sq. Miles): ____________________________
Number of Active Overhead / Gantry Cranes: ____________________________
How are raw material yards (scrap, iron ore, coal) currently monitored? _________________
What are the primary communication backhauls across the campus? (e.g., fiber loops, industrial Wi-Fi, private LTE) _________________

22.3.1 Mill-Scale Challenges

Check all campus-wide and spatial challenges you face in steel production:

Unmonitored crane collision risks or tracking issues in scrap/coil yards.
Severe environmental conditions (vibration, dust, extreme heat, magnetic interference) destroying field sensors.
Blind spots in remote stockyards, slag handling zones, and water basins.
Hazardous gas accumulation (e.g., Carbon Monoxide) in confined basement or piping corridors.
Hard-to-reach structural components, including elevated baghouse roofs and crane run-tracks.
High downtime costs for running diagnostic cables to remote campus areas.
Maintenance coordination difficulties across separate, massive departments (Blast Furnace vs. Rolling).

22.4 Thermal Stress and High-Energy Operations

Steelmaking represents one of the most energy-intensive, thermally extreme manufacturing processes. Kav AI helps monitor refractory integrity, cooling basins, and power load-shedding events.

What thermal limits trigger a “red alert” or emergency tap-hole/ladle inspection? (e.g., refractory hotspot temperature) __________________________________________________________________________
How are peak-power demand-response (power shedding) events managed for your EAFs? __________________________________________________________________________
What data sources do operators correlate to verify cooling water integrity for high-heat assets? __________________________________________________________________________

22.4.1 Thermal & Energy Pain Points

Check all operational pain points that impact your high-heat operations:

Ladle Breakouts: Undetected ladle refractory wear leading to catastrophic molten metal breakouts.
EAF/Furnace Refractory Hotspots: Difficulty predicting furnace shell or roof panel failures due to sensor lag.
Cooling Water Failures: Blocked cooling lines or failed pumps on water-cooled panels leading to rapid steam explosions.
Roll Wear & Thermal Shock: Rapid temperature fluctuations causing rollers in hot rolling mills to crack or wear unevenly.
Siloed Energy Data: Difficulty correlating electrical load logs (MW) with real-time furnace temperature and ladle status.
Post-Failure Audits: Hours spent attempting to reconstruct thermal degradation profiles after a furnace or mold failure.

22.5 Control Systems & OT Infrastructure

22.5.1 DCS, SCADA, & Historian

DCS/SCADA Vendor & Product Name (e.g., Siemens PCS 7, ABB Ability, Honeywell Experion, Rockwell FactoryTalk): ___________________________________________
DCS/SCADA Software Version & Year: ___________________________________
Historian in Use (e.g., OSISoft PI, Siemens Process Historian, ABB History): ______________
Data Polling & Archival Frequency (e.g., 500ms, 1s, 5s): ______________

22.5.2 PLC & Controller Inventory

List primary controller types (e.g., Siemens S7-400 / S7-1500, Allen-Bradley ControlLogix, GE/Emerson RX3i):

Controller Vendor & Model: ___________________________________________
Approximate Quantity: _______________________________________________
Age Range: ___________________________________________________________

22.6 Alarm Management & Operator Workflows

22.6.1 Alarm Volume & Fatigue

Approximate Number of Configured Alarms: ______________________________
Average Alarms per Day (Normal Operations): ___________________________
Average Alarms per Day (Upset / Tap / Roll Change Events): _______________
Estimated Percentage of “Nuisance” Alarms: ________%

22.6.2 Operator Workflow Challenges

Check all issues that impact your control room operators:

Operators routinely ignore temperature/vibration alarms due to high default limits.
Alarm floods during furnace tapping or mill roll adjustments, blinding operators to unrelated issues.
No automated correlation between motor current trends (amps), bearing vibration, and roller temperature.
High turnover in control rooms leading to reliance on junior operators during complex furnace heats.
Lacking integrated views of physical thermal cameras and SCADA temperature points on the same screen.

22.7 Security, Network Architecture & Compliance

Kav AI utilizes a read-only, security-first integration architecture to guarantee that no control actions can be back-propagated into your OT environment.

22.7.1 Security Posture

Is there physical and logical OT/IT network segmentation? [ ] Yes [ ] No
Is there a Demilitarized Zone (DMZ) with firewalls between OT and IT? [ ] Yes [ ] No
Firewall Vendor(s) in Use: ____________________________________________
Do you allow outbound-only connections to secure cloud platforms? [ ] Yes [ ] No

22.7.2 Cybersecurity & Industry Standards

Check all standards that apply to your facility’s cybersecurity review:

NIST CSF (Cybersecurity Framework)
NIST SP 800-82 (Industrial Control Systems Security)
IEC 62443 (Parts 2-4 / 3-3)
SOC 2 Type II Vendor Compliance
Corporate IT/OT Security Policy
High-Value Process Recipe Confidentiality Policy

22.8 Data Governance & Process Confidentiality

Are there geographical residency requirements for your operational data? __________________________________________________________________________
How do you safeguard proprietary steel metallurgy recipes (e.g., alloy formulas, temperature profiles)? __________________________________________________________________________
What is your mandatory data retention period for production logs and inspection records? __________________________________________________________________________

22.9 Operational Metrics (ROI Baseline)

To measure the ROI of the Kav AI platform, we establish a baseline using your historical metrics. Estimates are acceptable where precise figures are unavailable.

Unplanned Production Line Shutdowns / Outages per Year: ______________
Average Duration of a Mill Stoppage Event (Hours): ___________________
Estimated Cost per Hour of Mill Downtime (Hot Rolling / Casting): _____
Number of Ladle Refractory Failures / Hotspots in past 3 years: _________
Percentage of Maintenance Budget Spent on Reactive / Emergency Repairs: _____%
Annual Cost of Premium Energy Charges due to Unplanned Peaks: __________
Estimated Annual Cost of Mill Roll Thermal cracking / premature wear: _____

22.10 Inspection Practices & Sensor Capabilities

22.10.1 Inspection Methods

Check all methods currently used to assess asset integrity:

Manual visual walk-arounds / operator rounds (high risk near liquid steel).
Drone-based structural inspections of mill roofs, cranes, and baghouses.
Continuous thermal imaging / IR cameras (for ladle shell & furnace refractory monitoring).
Handheld thermal cameras used during periodic manual rounds.
Ultrasonic testing (UT) for ladle thickness and mill roll cracks.
Vibration analysis (continuous or periodic) on main rolling stand motor gearboxes.
Motor current signature analysis (MCSA) on rolling mill drives.
Continuous gas detection (CO, CO2, H2, O2) in basement tunnels and gas lines.
Baghouse broken bag detector systems (triboelectric dust monitors).

22.10.2 Inspection Equipment Inventory

Please list equipment owned or contracted:

Thermal / IR Cameras (Permanent): ______________________________________
Handheld / Portable Thermal Cameras: _________________________________
Vibration Data Collectors / Continuous Sensors: _______________________
Ultrasonic Thickness / NDT Equipment: _________________________________

22.11 Goals & Strategic Objectives

Rank your top priorities for implementing Kav AI (1 = highest priority, 12 = lowest):

Objective	Priority (1-12)
Prevent ladle breakouts and furnace refractory failures
Reduce unplanned downtime on continuous casters and hot strip mills
Detect mill stand gearbox and bearing degradation before catastrophic failures
Automated early warning of cooling water blockages on furnace panels
Reduce operator alarm fatigue and streamline control room workflow
Prevent environmental particulate compliance violations in baghouses
Optimize reheating furnace combustion and fuel consumption
Monitor overhead ladle crane mechanical/structural health
Enhance workplace safety in hazardous gas zone areas
Centralize monitoring across multiple steel shops and rolling mills
Move from manual dangerous rounds to automated exception-based AI rounds
Integrate 3D thermal digital twins for ladles and EAF panels

22.12 Regulatory Compliance

Check all applicable environmental, health, and safety regulatory requirements:

OSHA 1910.179 / 1910.180: Overhead and Gantry Crane safety standards.
OSHA 1910.119: Process Safety Management (where applicable to gas recovery).
EPA Clean Air Act - Title V Operating Permits: Particulate Matter (PM) emissions from baghouses.
EPA Greenhouse Gas Reporting Rule (Subpart C & Q): Iron and steel production GHG.
State Environmental Protection Regulations: (e.g., Indiana IDEM, Ohio EPA, Michigan EGLE).
NPDES Water Discharge Permits: For cooling water blowdown basins.

22.13 IT, MES & Enterprise Integration

Manufacturing Execution System (MES) (e.g., PSImetals, Primetals, QuinLogic): __________________________________________________________________________
Enterprise Asset Management (EAM) / CMMS (e.g., SAP PM, IBM Maximo): __________________________________________________________________________
Laboratory Information Management System (LIMS) (for chemistry/tensile tests): __________________________________________________________________________
Do you require Single Sign-On (SSO) integration (SAML 2.0 / OIDC)? __________________________________________________________________________

22.14 Proposed Pilot Scope

Help us define a highly focused pilot deployment to demonstrate immediate value:

Target Pilot Department / Area (e.g., Torpedo Ladles, Hot Strip Mill Coilers): __________________________________________________________________________
Primary Asset(s) to Monitor (e.g., 2 Torpedo Ladles, 1 Continuous Caster Segment): __________________________________________________________________________
Specific Problem to Solve in the Pilot: (e.g., “Automated thermal hotspot alarm triggered on ladle shell 12 hours before thickness drops below safety limit”) __________________________________________________________________________
Target Start Date & Proposed Pilot Duration (e.g., 90 days): __________________________________________________________________________
Key Stakeholders for Pilot Evaluation: __________________________________________________________________________

22.15 Submission & Sign-off

By submitting this onboarding questionnaire, I confirm that the information provided represents our operational goals and infrastructure to the best of my knowledge.

Printed Name & Title: __________________________________________________
Authorized Signature: __________________________________________________
Date: __________________________

Please return the completed document to your Kav AI Solutions Architect at info@kavai.com.