Ops 571 – Process Improvement Plan
Ops 571 – Process Improvement Plan
Process Improvement Plan
Week 5
University of Phoenix
OPS/GM571
March 14, 2011
Process Improvement Plan
Over the past five weeks data was collected for the purpose of monitoring and reviewing the results of morning preparations. This reviews the process for a person to establish an efficient morning routine. The initial flowchart was reviewed to make efficient changes in the system (see table 1). The morning preparation process is reviewed one last time to develop a process improvement plan. The statistical process controls are reviewed along with the confidence intervals.
Table 1
Control Limits
Process control monitors the quality of the product as the product or service is produced (Chase, Jacobs, & Aquilano, 2006). The purpose of these controls is to produce the information in a timely manner. The Statistical process control (SPC) takes a random sample and determines whether the output is within the selected range (Chase, Jacobs, & Aquilano, 2006). Basically an improvement process involves monitoring and examining where one could better the time it takes to get ready in the morning. After re-examining and adjusting for maximizing time in the morning, it is found that some steps could be eliminated with no problems in the end as seen in table 2. What was found to be the most beneficial was breaking the tasks down into chucks of time. These times are found in table 2 and applied to each task.
Table 2
Table 3
Table 3 shows the average weekly times. When a process is operating at an acceptable capability level, the mean and standard deviation operate within acceptable upper and lower control limits. Process control levels will be within plus or minus three standard deviations. Bottlenecks were present in the situation. One bottleneck that came up was the weather. During these five weeks winter weather made a big impact in everyones lives as the ice storm passed through. It became necessary to take time in the morning to start the car early and scrap ice off the windows. This created the spike shown in table 4. An awareness of the problem in the process is the first part of taking action to improve.
Table 4
Material requirement planning (MRP) began as a system for “computing schedules and amounts of materials required” (Chase, Jacobs, & Aquilano, 2006, p. 630). MRP was found useful in the morning preparation scenario. MRP uses logic to understand the approach used for determining what tasks are necessary, (number of parts or components) and the time needed for each task (materials needed). MRP is not only valuable in industries, it also valuable to people who want to create order and efficieny in their schedules. In week one, the average time spent in morning preparations is .81. By week five the average time was down to .44 minutes. The process almost decreased by half. This is a dramatic amount of time that can be used in other areas such as sleep or in productive areas such as finishing school work.
Forecasting
Forecasting involves generating a number or set of numbers to predict a future occurrence. A forecast uses past data to plan for short-range and long-range planning (Forecasting, n.d.). Forecasting is not always exact, but it can provide valuable data. Many factors can affect forecasting: weather, economic situations, and consumer buying habits. As seen by the winter storm, forecasting must take into consideration that there will be times that are unpredictable and will cause delays. By using past data, these delays are taken into consideration and are part