Classification scheme and prevention measures for caught-in-between occupational fatalities.

Area of Science:

• Occupational Safety and Health
• Industrial Accident Analysis
• Mechanical Engineering Safety

Background:

• Caught-in-between (CIB) incidents involving machinery and vehicles represent a significant cause of workplace fatalities.
• Previous analyses often lack a systematic approach to identify the root causes across diverse industrial sectors.
• Understanding specific accident patterns is crucial for developing effective, targeted safety interventions.

Purpose of the Study:

• To systematically analyze 312 CIB fatalities to identify common contributing factors and accident patterns.
• To apply Boolean algebra and minimal cut set (MCS) analysis to determine the primary causes of CIB fatalities across various machinery and vehicle types.
• To provide a data-driven basis for developing precise and effective prevention strategies.

Main Methods:

• Development of a comprehensive, mutually exclusive coding scheme for analyzing CIB fatalities.
• Inclusion of victim demographics, industry type, injury source, and accident causes in the analysis.
• Application of Boolean algebra and MCS analysis to identify critical causal factors for each injury source.

Main Results:

• Fatalities were categorized based on injury sources including special process machinery, metal/woodworking machinery, conveyors, vehicles, cranes, construction machinery, and elevators.
• MCS analysis revealed shared primary causes for CIB fatalities across special process machinery, metal/woodworking machinery, and conveyors.
• Identified key contributing factors: lack of safeguards, working on running machinery, unintentional activation, unsafe posture/position, unsafe clothing, and defective safeguards.

Conclusions:

• CIB fatalities can be significantly reduced by addressing identified common causes such as inadequate safeguards and unsafe work practices.
• The study provides a framework for grouping accident causes, enabling the development of sector-specific and generalizable prevention measures.
• Targeted interventions focusing on the identified critical factors can lead to a substantial decrease in machinery and vehicle-related workplace deaths.