The relationship between automation complexity and operator error

Ogle, Russell A.; Morrison, Delmar “Trey”; Carpenter, Andrew R.

doi:10.1016/j.jhazmat.2008.01.065

Cited by 12 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Poor usability characterized by a combination of high complexity and low transparency of highly automated technical systems can also lead to difficulties for the operators to build up an adequate mental representation of the current situation (Endsley, ; Kaber & Endsley, ; Ogle, Morrison, & Carpenter, ). This might become even more important as the human operator in the modern manufacturing industry is more and more involved in monitoring tasks that require a good representation of all ongoing processes in order to be able to take over manual control when needed.…”

Section: Introductionmentioning

confidence: 99%

Perceived stress in human–machine interaction in modern manufacturing environments—Results of a qualitative interview study

et al. 2019

View full text Add to dashboard Cite

Rapid advances in digitization technologies are changing modern working conditions especially in industrial settings. Consequently, employees are confronted with new forms of human–machine interaction. Whether changes in working conditions in general, and the increasing relevance of human–machine interaction in particular, affect psychosocial working conditions, and employee's health is currently matter of debate, but empirical data are lacking. Therefore, we conducted semistructured interviews with 36 employees working in five different companies. The interviews were aimed at identifying potential stressors associated with the introduction and use of modern technologies in the manufacturing industry. The results show that stressors linked to human–machine interaction are technical problems, poor usability, low situation awareness, and increased requirements on employees' qualification. For example, technical problems such as breakdowns or slowdowns were described as a main stressor when employees were not qualified to handle these problems on their own, thus decelerating work flows and causing additional time pressure. Overall, the results show that problems in human–machine interaction, which have been observed in laboratory and nonindustrial settings, also apply to industrial work places with highly automated working conditions and are a potential source of stress. These factors should be considered in psychosocial risk assessment of work‐related stressors.

show abstract

Section: Introductionmentioning

confidence: 99%

Perceived stress in human–machine interaction in modern manufacturing environments—Results of a qualitative interview study

et al. 2019

View full text Add to dashboard Cite

show abstract

“…However, it has also been shown that merely replacing the manual control actions with automatic control actions does not readily reduce the risk of accidents (Kletz et al, 1995;HSE, 2003). Ogle et al (2008) reported the relationship between the complexity of automation and operator error, demonstrating that operators are at the center of the control missions. To intervene and mitigate the process failures effectively, operators must have the necessary information to diagnose the problem, must receive the information within sufficient time to respond, and must possess the appropriate skills and knowledge to perform the corrective actions.…”

Section: Discussionmentioning

confidence: 99%

Emergency shutdown of fluidized bed reaction systems

Sano

Koshiba

Ohtani

2020

Journal of Loss Prevention in the Process Industries

View full text Add to dashboard Cite

“…Today, more advanced control algorithms allow the operator to execute commands directly targeting production specifications, rather than single set‐point values such as pressure and flow rate. As a result of the increased complexity of the underlying process control system, plants may be more susceptible to equally complex failure modes, including multiple event failures which could include operator error .…”

Section: Introductionmentioning

confidence: 99%

Hazards inherent to control systems: Case studies and lessons learned

et al. 2016

Self Cite

View full text Add to dashboard Cite

Control systems are an integral part of almost all chemical processes, regardless of size or complexity. As the demands for performance and safety increase, control systems will only proliferate. With automation comes the ability to develop more complex and interrelated processes, and to respond more rapidly to disturbances. However, increased reliance on control systems, both discrete and continuous, requires increased diligence with respect to their development and testing, as well as the implementation of independent layers of protection.A control system that provides optimal product for typical feed conditions may behave poorly during abnormal conditions, such as idling or turnarounds. Similarly, independent control systems charged with safety instrumented functions may not be called upon to act until they become necessary to prevent or mitigate an emergency situation. To recognize and mitigate hazards associated with control systems, process design and process hazard assessment teams may need to consider these and other potential issues.Presented here is a brief overview of the hazards associated with control systems. Finally, case studies are used to highlight the need for considering the potential hazards associated with control systems, from the design stage, through startup, operation, and turnarounds.

show abstract

The relationship between automation complexity and operator error

Cited by 12 publications

References 4 publications

Perceived stress in human–machine interaction in modern manufacturing environments—Results of a qualitative interview study

Perceived stress in human–machine interaction in modern manufacturing environments—Results of a qualitative interview study

Emergency shutdown of fluidized bed reaction systems

Hazards inherent to control systems: Case studies and lessons learned

Contact Info

Product

Resources

About