Risk prevention and policy-making in automatic systems.

Area of Science:

• Robotics and Automation
• Occupational Safety and Health
• Risk Management

Background:

• Accidents in automatic production systems occur with a frequency of 1 in 100-1000 robot-years, with fatal accidents being significantly rarer.
• Traditional occupational safety aims for zero severe accidents in automated systems, necessitating robust risk assessment.
• Decision-making for safety requires balancing risk reduction measures, costs, and the company's cultural context.

Purpose of the Study:

• To present a simplified procedure as a decision tool for risk assessment in automatic production systems.
• To develop a risk concept that integrates deterministic and probabilistic approaches for accident prevention.
• To facilitate the achievement of a quantitative acceptable risk level through consensus on safety targets.

Main Methods:

• Development of a simplified risk assessment procedure incorporating deterministic and probabilistic elements.
• Identification of eight representative accident scenarios involving robot-human interactions.
• Proposal of seven prevention policies to address identified accident scenarios.

Main Results:

• The procedure provides a framework for decision-making in safety management for automated systems.
• An additional probabilistic approach helps identify cost-effective safety measures for risk reduction.
• Discussion of three risk evaluation methods to achieve broad consensus on safety targets.

Conclusions:

• The presented procedure aids in balancing safety, cost, and risk reduction for automatic production systems.
• A quantitative approach to acceptable risk levels is crucial for effective safety management.
• Consensus on safety targets is vital for implementing successful risk mitigation strategies in industrial automation.