Operationalizing normal accident theory for safety-related computer systems
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners. As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i

Operationalizing normal accident theory for safety-related computer systems

Filetype[PDF-279.09 KB]



Details:

  • Personal Author:
  • Description:
    Computer-related accidents have caused injuries and fatalities in mining as well as other industries. Normal accident theory (NAT) explains that some accidents are inevitable because of system complexity. NAT is a classic argument in organizational sociology although it has been criticized as having imprecise definitions and lacking criteria for quantifying complexity. These limitations are addressed by a unique approach that recasts this organizational theory into an engineering-based methodology to quantify NAT complexities of computer-based systems. In this approach complexity is categorized as external or internal. External complexity is defined by the external behavior of a system, and is quantified by these dependent variables: system predictability, observability, and usability. Dependent variable data contain the perceptions of 32 subjects running simulations of a system. The system’s internal complexity is characterized by modeling system-level requirements with the software cost reduction (SCR) formal method. Model attributes are quantified using 15 graph-theoretical metrics—the independent variables. Five of 15 metrics are correlated with the dependent variables as evidenced by structure correlations exceeding 0.25, with standard errors <0.10 and a 95% confidence interval. The results also show that the system predictability, observability, and usability decreased as NAT complexities increased. This research takes a step forward in operationalizing NAT for computerized systems. The research benefits mining and other industries as well.
  • Subjects:
  • Collection(s):
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files
More +

You May Also Like

Checkout today's featured content at stacks.cdc.gov