Primatech

Designers

Data analytics from design-stage PHA studies help designers to ensure safe designs. They are used to compare the risk profiles of the new process with existing processes to identify any anomalies, address facility siting and layout by examining the distribution of risks across a facility, improve the human factors design of the process by examining human error contributions to process risks, and decide on an appropriate mix of safeguards in the hierarchy of controls.

Engineers

Process, control, and other engineers all benefit from PHA data analytics. Knowledge of PHA data analytics supports process optimization, functional safety, alarm management, damage mechanism reviews, compliance with industry standards, and many other engineering functions.

Managers

PHA data analytics provide managers with insights into the nature, sources, levels, and distribution of risks in a process.

PHA data analytics are used by managers for a variety of purposes. First and foremost, they enable managers to develop and execute a well-founded implementation plan for PHA recommendations that reflects the criticality of action items. However, PHA data analytics also assist with many other managerial responsibilities, such as highlighting items for emphasis in operational discipline programs, involving facility personnel with process safety, addressing safety culture, briefing contractors on high risk actions and areas in processes, performing management review of PHA, and stakeholder outreach.

PHA Facilitators

PHA facilitators use data analytics to ensure the quality and consistency of studies. A variety of study metrics provide the means to calibrate a study against expectations for meeting industry norms. Facilitators compare analytics from different processes to help identify any omissions or deficiencies, for example, missing scenarios or inadequate safeguards. Also, analytics are used to audit against previous PHA studies.

PHA data analytics facilitate the development and maintenance of reference databases on initiating events, safeguards, and other hazard analysis elements to use in performing studies. They also contribute to improving checklists and guidelines used for performing studies.

Risk and Reliability Analysts

PHA data analytics are used to identify critical hazard scenarios so that LOPA or QRA can be performed for those scenarios of greatest concern. Such studies support reliability-centered maintenance, and the determination of safety integrity levels in functional safety.

Process Safety Managers and Coordinators

PHA data analytics are used to quickly gauge the overall risk posed for an entire process, its operating units, and different operating modes. Risk profiles of different processes, units, and operating regimes and modes are compared to guide the allocation of risk reduction resources. Analytics also enable the sharing of process safety insights and knowledge across facilities and benchmarking of PHA against other companies to facilitate the adoption of best practices. Prevention and mitigation strategies for hazards can be compared across processes to identify flaws in strategies. Similarly, scenarios can be compared across processes to gain insights into underlying reasons for differences and improve the quality and consistency of PHA studies. Such comparisons also enable the examination of the impact of different facilitators and study teams on PHA results.

PHA data analytics are used to prioritize recommendations by criticality to guide their implementation and ensure the most critical recommendations are addressed first. They also enable the development and execution of an implementation plan for PHA recommendations. Additionally, they provide a sound basis for communicating priorities for safety improvements to stakeholders, such as operators and mechanics, and they support the communication of risks to all stakeholders.

PHA data analytics support most other process safety elements. For example, they contribute to the development and maintenance of process safety information and knowledge, the use of performance indicators, safeguards protection analysis, and hierarchy of controls analysis.

MOC Coordinators

MOC PHA studies identify new and/or modified hazard scenarios for a process that result from changes. Each change results in new and/or modified scenarios. Data analytics are used to compare risk profiles of the process before and after a change. This comparison provides the basis for deciding whether or not to proceed with the change and how any increased risk from the change can be ameliorated.

Operations Personnel

PHA data analytics are used to identify safety critical actions to highlight in the development and review of procedures and operator training programs. They provide insights into risk contributions from specific pieces of equipment and people to better manage process risks. Also, they Inform decisions on area occupancy and PPE use.

PHA data analytics assist with operational readiness by flagging high risk scenarios that occur during startup so special measures can be taken to control their risk. Also, they are used to support safeguard bypass analysis by ranking safeguards according to their criticality, and turnaround planning by showing how the process risk profile changes during turnarounds and what actions are needed to manage the modified risks.

Maintenance Personnel

PHA data analytics are used to identify safety critical equipment for use in prioritizing maintenance for process equipment and safeguards and to support risk-based inspection programs for assuring asset integrity. They facilitate the management of safety instrumented systems, relief devices, alarms, and other safety systems.

Procedure Writers

PHA data analytics are used to identify safety-critical actions performed by operators, mechanics and other facility personnel. This information is essential knowledge for developing operating, maintenance, and other procedures for facilities, such as safe work practices.

Existing procedures that have not benefitted from such knowledge can be reviewed and updated once such analytics are used.

Emergency Planners and Responders

PHA data analytics that categorize process hazards according to their type, severity, risk, and process area are employed in the development of emergency response plans. Their use ensures that response plans are risk-based and that they are tailored to realistic scenarios rather than hypothesized situations.

Trainers

Data analytics relating to human contributions to hazard scenarios and process safeguards provide valuable insights into how people impact process risks that can be factored into the initial and refresher training of front-line workers such as operators, mechanics, and contractors. Analytics identify high risk actions performed by front-line workers. Visual representation of key analytics facilitates the comprehension by workers of the importance of the training.

Human Resource Personnel

Data analytics on the human contributions to hazard scenarios and process safeguards play an important role in establishing competency requirements for people who occupy roles that can affect process safety. Such people must be able to perform their assigned tasks without adversely impacting facility risk. Data analytics provide a means to help ensure sufficient competency to avoid such impacts.

Incident Investigators

PHA data analytics provide insights into scenarios that match the combinations of causal factors from incidents. This knowledge enables investigators to better understand how incidents occurred and also helps to improve the process of scenario identification in PHA.

Auditors

When auditing the PHA element of process safety programs, PHA data analytics provide a valuable means for auditors to probe deeper into the efficacy of studies than is otherwise possible. Better assessments can be made of the quality and completeness of studies.

Additionally, PHA data analytics provide a roadmap for auditors to follow when auditing other process safety elements, for example, data analytics for safety- critical equipment focus auditor’s attention on the most important pieces of equipment when auditing mechanical / asset integrity.

Summary

PHA data analytics have many uses to improve process operability, reliability, and safety. They support all other process safety elements. Every person in a process facility can use or benefit from PHA data analytics to facilitate their tasks and improve their personal safety.