• DocumentCode
    3040457
  • Title

    A Framework to Classify Processes in the Field of Human-Machine Systems Engineering

  • Author

    Ley, Daniel

  • Author_Institution
    Fraunhofer FKIE, Wachtberg, Germany
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    1582
  • Lastpage
    1587
  • Abstract
    The analysis of workflows is a core element for the design and evaluation of complex human-machine systems. Based on the attributes of corresponding processes, appropriate methods for capturing data and a proper process modeling language must be chosen. But what are relevant attributes for these decisions? What are typical attributes of processes for discussions independent from application domains? A proper method to classify processes is missing in literature. Therefore, based on a two stage qualitative literature analysis a framework to classify processes was developed. Firstly, various process designations were identified. Secondly, definitions and descriptions of these designations were used in an iterative approach to extract attributes relevant for all kinds of processes. The qualitative approach, the consequent results in form of a "Process Disc" with eight process attributes and related values as well as the application are described in this paper.
  • Keywords
    man-machine systems; pattern classification; specification languages; data capturing; human-machine systems engineering; iterative approach; process classification; process disc; process modeling language; qualitative literature analysis; workflow analysis; Business; Electronic mail; Gears; Man machine systems; Modeling; Unified modeling language; Data Capturing Methods; Human-Machine Systems Engineering; Modeling Language; Process Analysis; Process Attributes; Process Classification; Workflow Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.273
  • Filename
    6722026