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...
Typically, SPC assists in quality control in the manufacturing process, which includes inspection that enhances early detection and prevention of problems in the production process. Apart from assisting manufacturing firms to reduce waste, SPC assists in eliminating time waste required for the production process.
iii. Combining SPC and variation management to satisfy the requirements of AS9103
Combination of SPC and variation management will assist in enhancing quality standard in the production process. The SPC will assist in identifying variations in production process and the variation management will assist an organization to ensure that quality product is on the control line.
e. Theoretical Bases and Organization
The project uses the process model to fulfill the requirements of the production process. The model consists of several stages starting from product definition related to KCs variation management. The process model ends with the product monitoring and maintenance. The research will follow the theoretical model using SPC to enhance manufacturing of quality product. The following hypothesis is developed to evaluate the importance SPC tool in the variation management.
HO: SPC tools and variation management are the effective tools to satisfy AS9103 requirements.
H1: SPC tools and variation management are not the effective tools to satisfy AS9103 requirements.
To test the hypothesis, the study is organized in the following format:
Chapter one provides the background of the study, the theoretical framework and the overview of the SPC and the AS9103.
Chapter two of the study provides the literatures review that explores the past studies on the SPC and the AS9013.
The chapter three reveals the research methodology that provides the method of data collection, and data analysis using a quantitative technique.
Chapter four provides the results and discussion.
Chapter five provides summary and conclusion.
ii. AS9103SAE standard
AS9103 SAE is the Society of Automotive Engineering standard that applies to product of Aviation parts, and the standard is applicable in the production process, which influences the variation of Key Characteristics. The AS9103SAE Standard is designed to drive up the improvement in the manufacturing processes using effective management and adequate planning of Key Characteristic.
f. Limitation of the Study
The study will be limited to the statistical process for the variation control in the production of Aviation and Aerospace parts. The thesis will also be limited to the production process that could influence variation of KC (Key characteristics). The application of AS9103 will be limited to the Aerospace industry in enhancing adequate planning and effective management of KC variation.
References
Crossley, M.L. (2008).The Desk Top reference of Statistical Quality Methods.Milwaukee, WI: ASQ Quality Press
Fontanares, R. (1997). Statistical Process Control Implementation in an Aerospace Manufacturing Machine Shop (Master's Thesis).Available from California State University, Dominguez Hill Library.
Gordon, D.K. (2007). Changes Coming in Aerospace Standards. Quality Progress. 40(1):74.75.
International Organization for Standards, (2008).ISO 9001:2008 Quality management system-requirements.Geneva, Switzerland: ISO/IEC.
SAE Aerospace (2012). Aerospace Series - Quality Management Systems -Variation Management of Key Characteristics. SAE Internatioanal.
Society of Automotive Engineers. (2012)Aerospace Standard AS9103AVariation management of key characteristics.London, United Kingdom: SAE.
Society of Automotive Engineers. (2009) Aerospace Standard AS9100CQuality management systems - requirements for aviation, space and defense organizations. London, United Kingdom: SAE.
Yang, F. (2011). Key characteristics and based model for quality assurance in supply chain. IEEE Xplore, 2, 1428-1432. doi: 10.1109/ICIEEM.2011.6035424
Wiley (2009). Chapter 6: Statistical Quality Control. Wiley Publication.
