Energy

Helping suppliers provide energy safely and more efficiently

Energy

Increased operational costs for offshore drilling and diminishing financial returns from lower oil prices have made oil and gas business leaders focus more on operational excellence. Operational excellence requires effective design and operational efficiency (especially on maintenance), better asset and human operator performance, improved health and safety compliance and enhanced project planning and control capability using technology.

Human Factors Engineering (HFE) or Human Factors Integration (HFI) aims to incorporate human factors knowledge into systems engineering, so that it is part of all complex systems throughout their life cycle. In the nuclear industry, human factors is seen as central to the safe and effective design and running of all nuclear facilities. The International Atomic Energy Agency (IAEA) recommends  that:

Systematic consideration of human factors, including the human-machine interface shall
be included at an early stage in the design process for a nuclear power plant and shall
continue throughout the entire process

Human Factors has a major role in the prevention of personal injury and dangerous occurrences such as hydrocarbon releases associated wells, pipelines etc., dropped objects, collisions, subsidence or collapse of the seabed, problems with lifting equipment or evacuation of installations.

When incidents are reviewed or risk assessments are conducted, the Human Factors issues that typically arise include:

  • Individual risk perception
  • Overestimating own abilities
  • Underestimating the consequences of familiar hazards
  • Failing to recognise subtle changes to familiar tasks
  • Collective influences such as safety culture
  • Deviations from processes mistaken for ‘efficiency’ or ‘innovation’
  • Reluctance to slow or halt activities regardless of circumstances
  • Organisational, technical or environmental influences affecting human behaviour
  • Designs/configurations do not match operator expectations
  • Critical information is not clearly communicated or understood

 

 

 

Case studies