Towards Zero Defects in the Aerospace Industry through Statistical Process Control : A Case Study at GKN Aerospace Engine Systems

With the ongoing transformation of modern manufacturing systems in an industry 4.0 environment, industrial actors may see great improvements with respect to quality towards a state of near zero defects. For the aerospace industry, where increased quality and reduced risk is strongly related, new technologies may be used in manufacturing to see to the increasing demands on products. The safety, as well as the manufacturing complexity of products and processes, make the collected measurement data an integral asset for enterprises within the aerospace industry. Collected data may be analysed using statistical tools and methods to improve process capability and, in extension, product quality. Communicating the need for zero defects, original equipment manufacturers demand increased capability from product and component manufacturers. Hence, zero defects are typically operationalised through exhibiting a process capability of Cpk= 2.0. In response to the challenge, GKN Aerospace need to raise the traditional process capability targets of Cpk=1.33. By employing an exploratory research strategy with a deductive approach, the thesis combines theoretical knowledge from the literature with empirical findings in a thematic analysis. The thematic analysis was conducted by employing six phases as suggested by Braun and Clarke (2006) and resulted in the identification of 50 codes from a total of 459 data extracts. Based on the empirical interview data, a framework for how zero defects is interpreted at GKN Aerospace was developed, which describes zero defects as a cycle. Taking into account that zero defects is operationalised through Cpk= 2.0, the cycle consists of six phases that start with a vision and is completed by delivering a true and reliable Cpk of 2.0. In addition, the codes from the thematic analysis were collated into a thematic mind map, focusing on key aspects of working with statistical process control (SPC) to support zero defects. Two main themes are presented in the mind map, statistical approach to improvement work; highlighting necessary aspects of statistical process control and measurability, and removing barriers for improvement; highlighting fundamental organisational barriers that impede proactive quality improvement. To support the findings and give a practical example of how process data may be presented and analysed using tools and methods within statistical process control, an SPC study was conducted on a set of data. In the SPC study, the construction and analysis of individuals Shewhart control charts and moving range charts were described in detail. These procedures provide better insights about process behaviour through statistical thinking and thus better knowledge on how to approach more proactive process improvements