ABC is a multinational company that manufactures components that are sold in its two market segments which are the local and international. The market requires products which are manufactured using common criteria as any deviations lead to waste. The company loses on wasted assessment time and items which do not meet the standards. The company has therefore developed an acceptable limit that all manufactured components must meet. The company is therefore capable of optimizing the manufacture of the components to sufficient measurable levels. The company has also established strategies that ensure that defects are identified in advance before it is fully assembled. ABC, therefore, detects bad components quickly enhancing its ability to produce quality final products. The company performs statistics on measures of its processes and compares different approaches to determine the best approach to act on them. It measures different aspects of a process and analyses the measurements in a way that enables the determination of the cause and therefore a remedy (Bramwell, 2013; Wheeler & Chambers, 2010) . This report presents the results of a statistical process control analysis conducted in the production facility of ABC Company to determine whether data from 50 samples conform to the requirements of the company.
Statistical Process Control
The first step for the Statistical Process Control was to determine the data to be collected. Variable data was collected for the analysis of the components. The data involved the weight of the samples. Variable data was useful as it promotes higher quality and eliminates any arbitrary distinction of the attributes for describing the data. The measurement system was then qualified to ensure that it falls within the acceptable level (Bramwell, 2013) . The entire process was conducted with precision and accuracy to reduce any errors which could affect the accuracy of the collected data.
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Data Collection
Data collection was then initiated where a sampling plan and appropriate training on proper measurement as well as charting was done. There were two subgroups in this case as the company has two shift workers. The data so collected will, therefore, be sensitive to the entire process considering that there can be slight variations in the shifts (Wheeler & Chambers, 2010) . Fifty samples were collected randomly from the production line for analysis. The data were carefully collected in a five-hour interval where ten samples were selected each hour. A sample was picked randomly after every six minutes to ensure that the entire ten hours were adequately represented in the data. It was envisioned that any variations in the production process could be accommodated by the data collection process.
The data collected was recorded in a table which showed the reported values and the value number. The data was then used to develop a chart. A reaction plan was then developed to guide actions of the user if there is an out of control condition. A chart was then added to the control plan and control limits established. The limits were 18.73 and 18.89. The process was then assessed for stability over time. The following confidence intervals were computed for the data.
| Confidence Levels Level |
Sample data |
| 68.3%, SE x̄ | 18.80200148019 - 18.81247851981 |
| 90%, 1.645SE x̄ | 18.798622634913 - 18.815857365087 |
| 95%, 1.960SE x̄ | 18.796972501173 - 18.817507498827 |
| 99%, 2.576SE x̄ | 18.79374557297 - 18.82073442703 |
| 99.9%, 3.291SE x̄ | 18.790000031306 - 18.824479968694 |
| 99.99%, 3.891SE x̄ | 18.786856919421 - 18.827623080579 |
| 99.999%, 4.417SE x̄ | 18.784101458001 - 18.830378541999 |
| 99.9999%, 4.892SE x̄ | 18.781613161091 - 18.832866838909 |
X Bar Chart
R Chart
Results
Statistics
The sample mean for the collected data is 18.80724 and the median is 18.8. The mode is 18.831 with the population variance being 0.0013447 and standard deviation of 0.0366696. The sample variance for the data is 0.0013721 and the sample standard deviation was 0.0370419. The lowest or minimum value from the sample is 18.734 and the maximum is 18.888. The range is 0.154.
Interpretation
The chart was divided into equal time zones above and below the mean as shown in the figure above. The zones are equal to 1, 2 and 3 standard deviations from the mean. There were no points which were below or above the control limits. There were no two out of three points in the second standard deviation on the same side of the center line. Similarly, there were no four points on the second standard deviation beyond the same side of the mean. There are no more than four points beyond the 1 standard deviation on the same side of the X bar chart. Additionally, there were no six consecutive points with an increasing or decreasing trend. Most of the points were within the 1 standard deviation from the mean. From the X bar, the process is in control as all the results are within the control point and fall within a 68% confidence interval (Wheeler & Chambers, 2010) . The R Chart shows a similar trend for the sample data. From the analysis of the sample data, ABC should continue with its operations as they are within the limits. There are no extreme values that call for appropriate actions to be taken. The company is, therefore, producing the components as required and the wastage is therefore minimal.
References
Bramwell, D. (2013). An introduction to statistical process control in research proteomics. Journal Of Proteomics , 95 , 3-21. doi: 10.1016/j.jprot.2013.06.010
Wheeler, D., & Chambers, D. (2010). Understanding statistical process control . Knoxville, Tenn.: SPC Press.
