In a manufacturing process, variation control is a critical tool that enhances the quality of products delivered to customer. A problem occurs when the variation exceeds the customer's expectation, which may lead to non-conformance to AS9103 and customer's dissatisfaction. If an organization is unable to enhance quality conformance, the quality of the product will be automatically degraded thereby leading to the increase in the cost of production and decrease in profitability. Variation of products leads to a process where products deviate from customer's requirements, and the issue will lead to a customer's dissatisfaction, which may lead to a decline in a firm's profitability.
Process control is a strategic tool to identify variations in order to eliminate wastes. Once an organization identifies the sources of variations, it will be possible to minimize the level of variations in the production process. Statistical process control is an effective tool to manage variation in order to satisfy AS9103 requirements. Despite the importance of statistical process for the management of variation in the Aerospace and Aviation industry, there is still a scanty of scholarly research that focuses on the statistical process control in variation management to satisfy AS9103 requirements.
Gordon, (2007) pointed out that AS9103 is an advanced quality product planning to enhance production process in the Aviation and Aerospace industry. However, the author made no mention how the variation occurs in the production process. Moreover, the author did not identify statistical process control in the management of variation in order to satisfy the AS9103 requirements.
The thesis fills the gap created with the paucity on scholarly research on statistical process control and variation management to satisfy AS9103 requirements. The thesis addresses the challenges that Aerospace and Aviation industry is facing with variations in the production process.
ii. Applying and selecting key characteristics to drawings
According to AS9103, 5.1 & 5.4, the key characteristics applicable to drawing is that the measurable evidence related to variation control is effective. Moreover, an appropriate monitoring methodology should be implemented to ensure continued performances.
Section 5.4 of AS9103 requires variation control method for process such as tooling standard process as well as ensuring process and stability. Moreover, measurements used for the control charts should represent the normal production output. Thus, the control chart for the process must be appropriate for the application. (Society of Automotive Engineers, 2009).
iii. Using SPC to meet the requirements of AS9103
The SPC is very critical to meet the requirements of A39103, and the SPC tool assists in error control, which is appropriate for application. Thus, advanced statistical techniques using SPC is useful in identifying and correcting sources of variation in KC (Key Characteristics). (Society of Automotive Engineers, 2012). The control chart, control line, capability analysis, histogram, range, mean and standard deviation are the SPC tools used in AS9103.
"A control chart (also called process chart or quality control chart) is a graph that shows whether a sample of data falls within the common or normal range of variation. A control chart has upper and lower control limits that separate common from assignable causes of variation. The common range of variation is de-ned by the use of control chart limits. A process is out of control when a plot of data reveals that one or more samples fall outside the control limits." (Wiley 2009, P 176).
d. Purpose of the Study
The purpose of this study is to investigate the statistical process control and variation management to satisfy AS9103 requirements. The SPC is the statistical tool in satisfying the requirements of AS9103. The study is expected to guide the Aviation and Aerospace professionals on the use of statistical techniques to reduce variations in order to enhance continuous improvement in quality and productivity in the Aerospace industry.
The thesis also provides the strategies to reduce variations and enhance process control to maintain high production standards that will lead to zero defects in the manufacturing of aviation and aerospace product.
ii. Applying...
Applying Statistical Process Control Pharmaceutical Manufacturing The use of applied statistics in studying a pharmaceutical manufacturing process is examined in the work of Tiani (2004) reports that health care quality is critically important in society and the quality of health care is important to all individuals. It is important that treatment is given in an accurate manner and this is particularly true of medications given to patients as it is expected
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It should be verified why things started off so great and then dipped very close to the lower control limit and stayed there for such a vast portion of the timeline. That being said, the fact that no values are outside of the lower control limit shows that the graph is at least somewhat accurate if not completely accurate, but it is worth of review nonetheless. Conclusion In short, control charts
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