Process Improvement Plan
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- Date Submitted: 04/11/2011 02:38 PM
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Process Improvement Plan
Charles “Chris” Bozue
OPS 571
March 14, 2011
Michael Kline
Introduction
In this paper the subject to discuss is the effects of any seasonal factors and confidence intervals based on the process of “getting to work by 6:45am.” Earlier investigation revealed bottlenecks and overcoming them through Goldratt’s Theory of Constraints (TOC). This paper will consist of discussing any control limits along with the calculations and data used to determine them. This discussion takes into effect the very limited collection of process performance data over an initial four-week period. Also to be presented will be the measures of confidence usefulness on the number of data points collected.
Statistical Process Control
The bottom line goal of Statistical Process Control (SPC) is to “arrive at” and “keep” process control. The process identified in week one of getting to work by a certain time is monitored through control chart tracking using the process flowchart identified in Attachment 1 and an Excel spreadsheet as shown in Attachment 2. The top of the Excel spreadsheet chart identifies the “in-control” requirements of the process. Daily measurements were laid into the chart. Comparisons between the in-control and “actual” measurements were used to identify any variations. After week one analysis, investigative analysis showed variations identified as potential process problems which were then modified.
Because the process was time based, measurement will be accomplished by a process known as sampling variables that is measuring the amount of deviation from the set standard identified. The use of these statistical techniques of measuring and analyzing the variations recognizes the measurement of statistical process control. According to Chase, Jacobs, & Aquilano (2006), the standard practice is that statistical process control for variable is to set control limits out to three standard deviations for variable sampling. This particular...
Charles “Chris” Bozue
OPS 571
March 14, 2011
Michael Kline
Introduction
In this paper the subject to discuss is the effects of any seasonal factors and confidence intervals based on the process of “getting to work by 6:45am.” Earlier investigation revealed bottlenecks and overcoming them through Goldratt’s Theory of Constraints (TOC). This paper will consist of discussing any control limits along with the calculations and data used to determine them. This discussion takes into effect the very limited collection of process performance data over an initial four-week period. Also to be presented will be the measures of confidence usefulness on the number of data points collected.
Statistical Process Control
The bottom line goal of Statistical Process Control (SPC) is to “arrive at” and “keep” process control. The process identified in week one of getting to work by a certain time is monitored through control chart tracking using the process flowchart identified in Attachment 1 and an Excel spreadsheet as shown in Attachment 2. The top of the Excel spreadsheet chart identifies the “in-control” requirements of the process. Daily measurements were laid into the chart. Comparisons between the in-control and “actual” measurements were used to identify any variations. After week one analysis, investigative analysis showed variations identified as potential process problems which were then modified.
Because the process was time based, measurement will be accomplished by a process known as sampling variables that is measuring the amount of deviation from the set standard identified. The use of these statistical techniques of measuring and analyzing the variations recognizes the measurement of statistical process control. According to Chase, Jacobs, & Aquilano (2006), the standard practice is that statistical process control for variable is to set control limits out to three standard deviations for variable sampling. This particular...