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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66415
Volume:
10 |
7 |
Jul 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
FIRE TECHNOLOGY & SAFETY ENGINEERING
VIKRANT UNIVERSITY, GWALIOR
FIRE TECHNOLOGY & SAFETY ENGINEERING
VIKRANT UNIVERSITY, GWALIOR
Rolling mill manufacturing is one of the most critical operations in the steel industry due to the presence of heavy rotating equipment, high-temperature materials, hydraulic systems, cranes, electrical installations, and continuous production processes. Workers are exposed to hazards such as entanglement, crushing, burns, explosions, falling materials, electrical shock, excessive noise, and ergonomic stress. Traditional safety practices often focus on incident response rather than proactive hazard identification and systematic risk control. This study proposes a Hazard Identification and Risk Control Framework (HIRCF) for rolling mill manufacturing processes that integrates Hazard Identification and Risk Assessment (HIRA), Failure Mode and Effects Analysis (FMEA), Bow-Tie Analysis, Job Safety Analysis (JSA), and the Hierarchy of Controls within the ISO 45001 Occupational Health and Safety Management System. The framework identifies major operational hazards, evaluates their associated risks using a risk matrix, prioritizes corrective actions, and establishes engineering, administrative, and behavioral controls. The proposed framework supports continuous monitoring through key safety performance indicators and digital technologies, enabling steel industries to reduce accidents, improve operational reliability, and strengthen regulatory compliance.
KEYWORDS
Rolling mill manufacturing involves complex mechanical, thermal, electrical, and material handling hazards that require a structured and proactive approach to risk management. The proposed Hazard Identification and Risk Control Framework integrates established risk assessment techniques with engineering controls, behavioral safety, and digital technologies to improve occupational safety and operational performance. By systematically identifying hazards, prioritizing risks, implementing effective controls, and monitoring performance through measurable indicators, steel plants can significantly reduce accident potential and enhance sustainable manufacturing. Future research should validate this framework across multiple rolling mill facilities and explore advanced predictive analytics for dynamic risk assessment.
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Publication Date
7/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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