Statistical process control (SPC) is an efficient way of controlling and reducing the variability in a process when it is implemented and managed as designed by statisticians. However, recent research (Kelly, 2002; Kelly & Drury, 2002) suggests that statistical process control is not being used as statisticians intended due to its misalignment with operator and organizational goals, inconsistent performance as a decision making tool and inability to aid operators in process understanding. To overcome these issues Kelly (2002) developed an alternative human centered process control monitor known as the process window monitor (PWM). However, the significance of this concept has not been tested rigorously.

The main thesis of this work challenges the claims made by Kelly's (2002) that present the PWM as a superior alternative to a traditional SPC X¯and R chart. Experimental testing was performed that aimed at comparing the performance of the PWM to a traditional statistical process control X¯ and R chart in a manufacturing setting. This statistical comparison was developed to analyze the process control treatments ability to influence the stress placed on an operator in relation to process control, an operators' response to significant out-of-control conditions and the human/process control system interaction for performance and human interests.

This examination resulted in findings, divergent from traditional statistician beliefs, that reasonable suggest the PWM is a significant alternative to an SPC X¯ and R chart in practice. Findings also found the PWM is a process control tool more appealing to manufacturing operators. Strong findings do suggest certain operators may exhibit difficulties with using the process window monitors interpretation procedure leading to a misunderstanding of the process window monitors out-of-control rules. Potential modifications and additional training suggestions are presented herein to counteract this finding. It is recommended organizations implement the PWM on the manufacturing floor and hand over the current versus historical performance analysis associated with an SPC X¯ and R chart to engineers.