MODERN APPROACHES TO RISK MANAGEMENT IN THE SAFETY SYSTEM AT INDUSTRIAL ENTERPRISES

Abstract

The article provides an in-depth analysis of the safety management system at Ukrainian oil and gas industry enterprises, which operates under conditions of an unprecedented convergence of risks, making outdated, reactive approaches to labor pro- tection not only ineffective but also unacceptable. It is substantiated that in addition to the traditional production hazards inher- ent in all stages of the cycle–from geological exploration to hydrocarbon processing–three key aggravating factors of modernity have been added. Firstly, a high degree of physical and moral deterioration of infrastructure, which significantly increases the likelihood of accidents due to equipment failure. Secondly, the intensification of production at depleted fields, which gener- ates new, insufficiently studied professional risks. Thirdly, direct military threats that have turned the industry’s facilities into strategic targets for missile strikes and UAV attacks. Under such conditions, safety management is transformed from a narrowly focused function into a fundamental element of national resilience. The key thesis of the work is the need for a fundamental paradigm shift–a transition to a proactive, risk-oriented manage- ment model that focuses on predicting and neutralizing threats before they are realized. The theoretical basis for this approach is, in particular, James Reason’s “Swiss cheese model”, which demonstrates that an accident is the result of a confluence of hidden deficiencies at several levels of defense, namely technological, organizational, competence, and supervisory. The goal of a pro- active system is the constant identification and elimination of these “holes” to prevent a catastrophic coincidence. The technological foundation for implementing a proactive approach is identified as digital transformation based on Industry 4.0 principles. The creation of a unified intellectual ecosystem is proposed, where: the Internet of Things IoT acts as a real-time data collection system through vibration and corrosion sensors on equipment, gas analyzers in work areas, and weara- ble “smart” helmets and biometric trackers for personnel; artificial intelligence AI processes this data for predictive equipment failure and intelligent video analytics; immersive VR/AR technologies and digital twins provide skills training in extreme situa- tions without risk to life and allow for the safe modeling of the most complex emergency scenarios. To objectify management decisions, a transition from qualitative assessments to quantitative risk analysis QRA is pro- posed. This approach is based on the formula Risk = Probability × Consequences and uses mathematical tools such as deductive “fault tree analysis” FTA and inductive “event tree analysis” ETA to calculate the probabilities of complex accidents. Such analysis allows for an economically justified “cost-benefit” assessment for investments in safety systems. The key conclusion of the work is that in modern conditions, the line between labor protection, technological safety, and civil defense is completely blurred. A conceptual model of a unified, integrated safety management system that combines these three components is proposed. The practical implementation of the model involves the arrangement of shelters, the creation of duplicate notification and communication systems, and the conduct of comprehensive training that combines first aid skills with elements of tactical medicine. The creation of such an adaptive system is the only way to ensure the protection of personnel and the resilience of the functioning of strategic enterprises in Ukraine.