||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.