Title page for etd-0806111-095502


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URN etd-0806111-095502
Author Yung-Chi Su
Author's Email Address yungchisu@gmail.com
Statistics This thesis had been viewed 5361 times. Download 2214 times.
Department Information Management
Year 2010
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title A Study of Deploying Monitor-Oriented System Simulation Models to Improve the Efficiency of Statistical Process Control
Date of Defense 2011-07-15
Page Count 120
Keyword
  • System Simulation
  • Statistical Test
  • SPC
  • Process Capacity
  • Process Innovation
  • Statistical Sampling
  • Abstract The development of statistical process control has been for a long time and can be turned up in many manufacturing environments. However, statistical process control applications in process control generally limited to use the control chart applications, the deepening capacity for control charts such as process capability control, variation detection and evaluation, are rarely described so often so that statistical process control techniques is relegated. Meanwhile, statistical process control can detect the production process of the variations, but it can’t integrate the production resource capacity. Although the process control of manufacturing processes can achieve real-time control of effects, but the resources of the production process appeared to be quite inadequate in response to future demand forecast and capacity analysis.
    Therefore, this study combined with statistical process control system simulation technology for innovative management. Through the process observation and sample collection, we can use simulation technology to propose the process feasibility and applicability in resource constraint and resource allocation for considering the variation of the statistical process control, and use the quality improvement tools and causal feedback map, the system dynamics tools, in the resource dynamic ability for decision-making management.
    The research result appears:
    1、Based on the effective input parameters of simulation model , it can effectively simulate the actual production processes and produce an effective output.
    2、Through the appropriate statistical data validation, it can improve the sample reliability as an important reference to system simulation methods.
    3、Using the simulation technology, we can monitor the online process control, production resources allocation and capacity prediction.
    Advisory Committee
  • William S. Chao - chair
  • Yi-Ming Tu - co-chair
  • Pin-Yang Liu - advisor
  • Files
  • etd-0806111-095502.pdf
  • Indicate in-campus at 0 year and off-campus access at 1 year.
    Date of Submission 2011-08-06

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