Process_Improvement_Plan

Process Improvement Plan OPS/571 The process improvement plan suggests a way to improve upon a process to eliminate wasted time. Getting to work on time is a valued because not doing so may cause termination of services. This is a plan to refine the structure of a process, as opposed to explaining problems singularly. This is done by the statistical process control, control limit, and confidence intervals. Statistical process control (SPC) entails using random samples to assess and examine the differences in a process (Chase, 2006). Statistical quality control is about being able to improve the quality of a process which includes SPC, a variation decrease, process capacity breakdown, and a process enhancement plan. Statistical process control (SPC) is a way to monitor the process behavior procedures (Chase, 2006). The behavior that was monitored is getting out of the house on time. There is no possible way to get to bed early without finishing daily responsibilities and waking up earlier would cause sleep deprivation. So, bargaining with the times of waking up and going to bed is not an option. Hence, shortening the time getting ready in the morning will help the process of getting out of the house on time. The bottleneck to this process is doing everything the night before. This process will eliminate some of the wasted time. To explain how to get the outcome of the specific process under control or even improved, it is suggested that one should shorten the time getting reading in the morning process. If doing everything the night before will eliminate up to 25 minutes from the process. This process will consist of packing lunch and doing my daughter hair before I leave for the drive to work. Also, having an idea of what I am going to wear to work so, that there is no need for extra decisions in the morning. Taking control of these processes help eliminate up to 25 minutes per day. Use the control limits to evaluate whether or not the variations are out of stink or abnormal, statistical process control techniques are used in the control charts. The point variation from the start to finish is then shown. Day 1 Day 2 Day 3 Day 4 Day 5 Sample Means Week 1 30.0 0.0 0.0 0.0 30.0 12.0 Week 2 0.0 0.0 30.0 0.0 30.0 12.0 Week 3 0.0 0.0 30.0 0.0 0.0 6.0 Week 4 0.0 0.0 120.0 0.0 50.0 34.0 Total Mean 16.0 The Control Limits for the mean: Upper Control Limit = 68.95 minutes Lower Control Limit =36.95 minutes Mean =16.0 minutes By observing and recording the measurements for a longer duration, the mean would be better understood, and the control limits modified. The upper control limit for the four week period is 68.95 minutes; the middle is 16 minutes, and the lower control limit is 36.95 minutes. The control limits are usually placed three standard deviations from the mean which means that it is 99.73 percent likely that the data points will be within the limits. The confidence interval is the series of value which extends from the lower confidence limit to the upper confidence limit. “This range is expected to cover the population parameter of concern, such as the population mean, with a degree of certainty which is specified up front” (Charusombat, 1997). Under SPC, a process performs and is spelled out to get as much done as possible with the least down time and waste. While SPC has been applied most frequently to controlling manufacturing lines, it applies just as well to any process with a measurable output. Much of the power of SPC lies in the ability to examine a process and the sources of variation in that process using tools that give weight to objective analysis over subjective opinions and that allow the strength of each source to be determined numerically. Variations in the process that may affect the quality of the end product or service can be detected and corrected, thus reducing waste. Many situations and occurrences could easily cause a delay in me getting out on time for work such as making my lunch, doing my daughter hair, or deciding what to wear for work. Once in the car there could be traffic constraints or a need for gas. Other factors may include rain or even snow depending on the season. When these situations occur, the result is always a major delay in getting out of the house and my drive time to work–which causes all steps in the process to be thrown off schedule. In well-optimized processes, significant investment of preparation may be required to achieve a marginal improvement. Sacrifice the evening before may result in a gain that may or may not be sufficient to time waste management. A benefit analysis should be performed to determine if a process change is worth the time investment. Ultimately, present value will determine whether a process "improvement" really is an improvement. Key Performance Indicators (KPI) is used to evaluate its success or the success of a particular activity in which it is engaged. Sometimes success is defined in terms of making progress toward strategic goals; success is simply the repeated achievement of some level of operational goal (zero defects, 10/10 customer satisfaction etc.). Accordingly, choosing the right KPIs is reliant upon having a good understanding of what is important to the organization. In conclusion being prepared for what may happen will be the best choice in preparing for the day to come. There will always be things that come up such as weather constraints, gas, and even traffic, but preparing the night before will reduce the lag time and may even get the day started out rite. References: Charusombat, U. & Sabalowsky, A. (1997). What are Confidence Intervals , Tolerance Intervals and Prediction Intervals' Retrieved February 7, 2011, from, http://www.cee.vt.edu/ewr/environmental/teach/smprimer/intervals/interval.html Chase, R.B., Jacob, F.R., & Aquilano, N.J. (2006). Operations management for competitive advantage. (11th ed). New York: McGraw Hill/Irwin.