Identification of human errors in process safety management via cognitive reliability and error analysis method (CREAM): An illustrative case study

• Main Authors: Ramli, Azizan, Zaini, Nurhani Izzati Mohd, Majid, Noor Diana Abdul, Abidin, Mardhati Zainal
• Format: Conference Proceeding
• Language: English
• Subjects: Company structure; Data analysis; Data collection; Error analysis; Error reduction; Hazardous materials; Human error; Human factors; Industrial safety; Parameter identification; Reliability; Safety management
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0214088

The integration of human factors analysis and process safety management has emerged as a critical strategy for mitigating exposure to hazardous substances and consequential incidents. Given that human factors and behavior are major contributors to industrial accidents, the identification and assessment of human errors and their associated probabilities have become essential. In response, the Cognitive Reliability and Error Analysis Method (CREAM) was employed to seamlessly incorporate human factors into process safety management and to analyze human errors. This research aims to explore the factors that contribute to human-related incidents and to ascertain the probabilities of human errors within the chemical industry. Utilizing the CREAM methodology, the objective is to proactively reduce or prevent such errors. The creation of a CREAM Template within Microsoft Excel followed a comprehensive parameter study. Subsequently, insights were gathered from industry experts and on-site personnel, enriching the CREAM system with contextual data. Validation of the CREAM system was conducted by an experienced evaluator to ensure parameter accuracy. The resultant data underwent rigorous analysis and were benchmarked against industry standards. Notably, the likelihood of a human error occurring within one of the company’s Hierarchical Task Analyses (HTAs) was determined to be 0.01152. During data collection, an in-depth analysis of parameters contributing to human incidents was also conducted. Furthermore, human errors were identified for each task step, with the highest error rate associated with the cognitive function of execution, reaching 64.71%. In conclusion, the CREAM system equips experts to pinpoint human errors and their probabilities, enabling proactive measures to prevent incidents from occurring.