• DocumentCode
    2553637
  • Title

    Process control system of roof disaster based on PDCA cycle

  • Author

    Yongkui, Shi ; Guofeng, Song

  • Author_Institution
    Coll. of Natural Resource & Environ. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
  • fYear
    2009
  • fDate
    21-23 Oct. 2009
  • Firstpage
    199
  • Lastpage
    203
  • Abstract
    In order to control the whole process of roof disaster, first estimates the movement parameters of working face roof, calculates weighting intensity, chooses the method of roof support, calculates support parameters, predicts possible types of incidents and proposes preventive measures, according to geological conditions and design parameters. Then realizes auto-drawing which is depend on technical parameters, works out operational rules intelligently and ensures the implement of support design. At the same time, the system analyses the monitoring data of support quality and roof dynamic at actual working face, then makes contrast with the design results of the roof support design expert system, using the actual data to amend the expert system step by step, to complete "self-learning" function and realize PDCA cycle. It has proved that the system can control roof disaster very well, and it is of significance to coal mine safety production.
  • Keywords
    coal; disasters; expert systems; learning (artificial intelligence); mining industry; occupational safety; process control; roofs; PDCA cycle; coal mine safety production; design expert system; geological condition; preventive measure; process control system; roof disaster; self-learning function; Control systems; Data analysis; Disaster management; Expert systems; Feedback; Geology; Monitoring; Process control; Production systems; Quality management; Operational Rules; PDCA; information feedback; process control; roof disaster; roof monitoring; support design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3671-2
  • Electronic_ISBN
    978-1-4244-3672-9
  • Type

    conf

  • DOI
    10.1109/ICIEEM.2009.5344605
  • Filename
    5344605