Transformation of Production Control: Barrier-Based Risk Management Model

Managing industrial safety at high-hazard facilities requires a shift from reactive measures to proactive control. The core of this transition lies in the ability to focus on what matters most, without wasting resources on insignificant factors. This presentation by Alexander Valiev (Sibkor), Head of HSE Management Systems Development Division, focuses on the practical experience of transforming production control through the lens of critical risk management—risks whose realization can lead to catastrophic consequences, including multiple-fatality accidents and environmental disasters.

Guided by ISO 14001 principles, the company identified 13 critical risks for its mining operations. Notably, the selected criteria correlate perfectly with official analytics on fatal injury causes from Rostekhnadzor, confirming the objectivity of the chosen strategic direction.

From Theory to Practice: The Bow-Tie Method and Safety Barriers

To manage the identified risks, the classic Bow-Tie methodology was applied. The risk itself is placed at the center of the model, with causal factors recorded on the left and potential consequences on the right. Based on the established safety barriers, checklists were developed for regular workplace inspections.

However, the initial implementation phase revealed significant flaws in the traditional approach. Issuing printed checklists to the production floor led to formalistic inspections without the ability to collect and analyze data in real time. The lack of a unified digital environment made the process cumbersome: specialists had to descend into mine workings with paper, and upon returning to the surface, manually transfer information into fragmented analytics systems and outdated work order logs.

Digital Control Architecture: System Integration

The solution was a deep digitalization of the process. The speaker details the architecture of the new approach, where the Insight analytics system (for data visualization via dashboards) and the Altan operational management system play key roles. The primary task was not to create a single isolated master system, but to ensure seamless data exchange between existing IT products.

The configured integration enabled the automation of the entire cycle: from assigning inspection routes via checklists to monitoring result recording and the automatic generation of corrective action orders.

Mobile Solutions in Underground Workings

The practical implementation of production control now relies on the use of explosion-proof mobile devices. Thanks to the deployment of Wi-Fi networks and positioning systems in the mines, risk management occurs in real time.

Employees log into the system to receive assigned routes and checklists. The mobile app interface allows them to record the status of safety barriers directly on-site. If a non-functional barrier is identified, the employee can leave a detailed comment, including by using voice-to-text input.

A major outcome of this automation was the elimination of paper-based routines. The system allows for the creation of non-conformances and work orders for their resolution for the next shift directly from the mine face. Furthermore, a proactive response algorithm has been implemented: if identical violations are regularly recorded in the same area, the system automatically suggests changing the location status to "hazardous production situation," drawing additional attention from management. This directly engages engineering and technical staff in the risk management process and makes production control truly transparent.

What you will learn from this presentation:

• How to adapt the Bow-Tie method to create operational production control checklists?
• Why moving paper-based inspections into a digital environment requires the integration of work order and analytics systems?
• How to organize work with explosion-proof mobile devices in underground mine workings?
• How to automate the issuance of work orders for correcting violations directly from the point of detection?
• How algorithms help identify systemic issues and prevent the development of hazardous production situations?