... management (APM) platform. The Digital Workshop application leverages machine learning and advanced vision analytics to identify and automatically report occurrences of non-compliance within the company's own maintenance and technology centers. Abstract Performing complex activities on industrial...

...&learn learning tool environmental golden rule machine learning hse culture information enhancing hse culture knowledge retention application process safety gamification retention environment golden rule Introduction and Background In response to a concerning rise of incidents...

... of designing an MOC platform that operate in digitalized manner with a streamlined workflow covering all MOC process steps to manage and control MOC life cycle following gate concepts and incorporating machine learning predictive capabilities to help predicting scope, cost and schedule compliance. Design...

... language natural language processing deep learning large language model artificial intelligence sentiment machine learning nlp dataset inconsistency operation monitoring sentiment opinion mining perception information sentiment analysis application petroleum engineer fine-tuning risk...

... the organization's shift towards a reliable safety-focused learning approach. artificial intelligence lfnw hsse reporting incident machine learning example tool investigation seamless synergy exploring learning team normal work interconnection petroleum engineer iogp normal work tool operator...

... by the VAWS must be dismissed or acknowledged by the HSE operators at site. Through monitoring and interaction with the HSE operators, the VAWS system progressively learns (Machine Learning) to recognize HSE e and actual or potential hazardous situations to which the workers are exposed voluntarily...

..., facilitated by a generic and adaptable data schema and model architecture. prediction artificial intelligence neural network explanation application interpretable explanation llm preprint arxiv healthcare provider machine learning dataset architecture deep learning natural language...

... misspelled. The company wants to use machine learning to improve the data quality, risk rank, identify patterns and trends, and enhance the decision-making process for HSE management. The aim is to do real-time intervention at the time of reporting an event based on AI tool, further analysis for these unsafe...

... that is not possible in individual companies. IOGP is in a unique industry position to encourage international upstream industry collaboration and sharing of industry best practices to prevent process safety incidents, and their potential impact on life, the environment and assets loss. machine learning subsea...

... operations, especially during times of chaos. Health & Medicine safety culture Artificial Intelligence Hurricane Harvey machine learning contingency planning Resilience Engineering communication engagement adaptive resilience organizational culture eap wl information storm operation...

... by an intelligent system by applying logic that a human would apply to search data. Provision of such intuitive data can make decision making faster and safer. Machine learning methods can be used to develop and continuously build such logic that makes information intelligent and intuitive. A combination...

... whether learning is occurring. This study proposes a model that would allow companies to select appropriate metrics for various aspects of learning from incidents. educational software Upstream Oil & Gas Artificial Intelligence computer based training energy company information machine...

... building quantity drilling contractor consumer workshop management system emission drawwork machine learning Drilling Equipment energy consumption baseline Energy Management consumption artificial intelligence Introduction Energy Management: The Standard that Saves The world has...

... learning capabilities—and that van lead to implementing more effective actions. As such it can provide a sound basis for a further reduction of the number of incidents in the petrochemical industry to the ultimate goal: zero.
 Artificial Intelligence machine learning benchmarking Health...

... interfaces (HMI) could help the company achieve this goal in developing systematic trends, predictive analytics and machine learning capabilities to help workers reduce incidents, injuries, and disease. This efactory team is focused on creating HSE innovations based on the human signal detection, real time...

.... operational safety work planning Artificial Intelligence Upstream Oil & Gas incident machine learning contingency planning safety science performance indicator drilling operation assessment identification accident vehicle road traffic accident Indicator well control annular pressure...

... liquid seal manhole oily water sump machine learning drainage system hydrocarbon explosion accumulation maintenance operation oily water drainage system adnoc gas processing plant Introduction According to the sump design, the maximum content of hydrocarbon in the water drained...

... a number of "I Statements" to help leaders understand what they need to do as part of the change journey to take learning from incidents to the next level. Upstream Oil & Gas Effectiveness engagement Artificial Intelligence intervention incident machine learning LFI process zwetsloot...

... safety science research question search term vinnem operational safety major accident risk correlation machine learning Upstream Oil & Gas high risk industry safety indicator reliability petroleum industry process safety indicator accident literature review Indicator performance...

... "to adapt, compete, excel, innovate, produce, be safe, improve service and reach goals" in a downturn environment ( Salas et al. 2012 ). personnel competence educational technology educational software Upstream Oil & Gas machine learning educational setting Artificial Intelligence...