System Analysis and Operation Optimization for Aerospace and Related Manufacturing Processes

点击翻译按钮获取中文摘要

The importance of Canada's aerospace manufacturing sector cannot be overestimated in any terms. According to the 2013 Aerospace Industries Association of Canada (AIAC) and Industry Canada News Release, the overall impact of Canadian aerospace industry to the nation's economy, share of the total GDP value, R&D activities, employment numbers and quality, among many other key indicators, are all ranked very high, if not the top ones, in comparing to other manufacturing sectors in the country. Advanced fabrication and assembly technologies including the making and use of composite materials, precision machining, robotics and automation, among many others, have contributed to large extent to the success of Canadian aerospace industry. In addition, various system engineering methodologies and operation management tools such as lean engineering, supply chain management, production planning, inventory control, quality control and improvement, manufacturing cell configuration, etc., should and could play more significant roles in the design and improvement of aerospace manufacturing processes. The current literature and manufacturing practice show that there is a need to further develop these system engineering tools in addressing different manufacturing issues specific to aerospace manufacturing. For example, the aerospace quality management system, AS9100, has been adopted by many major aerospace companies. However, some of the statistical quality tools were initially developed for mass production systems such as those for automotive products and consumer goods. On the other hand, aerospace manufacturing is typically associated with slow production rate, large product variety, very high level quality requirements and high production cost. Standard statistical tools and other analytical tools must be further developed or revised before they can be properly used for aerospace process control and optimization. In the proposed research, we will investigate and develop statistical quality tools for applications in aerospace manufacturing where data availability is limited and evolving. In addition, we plan to develop new mathematical models and solution methods, or modify existing ones, for aerospace supply chain management considering joint product development, profit and risk sharing, and high level quality requirements. We will also investigate problems related to optimal production planning and control of aerospace manufacturing. An example problem is production control of manufacturing systems combining heavy manual operations and robotic assembly processes which widely exist in aerospace and other manufacturing industry. The outcome of the proposed research will be modeling and solution methodologies suitable for solving systems engineering and optimization problems many aerospace companies face in supply chain design and management, total quality control and improvement, and in optimal manufacturing system and process development. The research outcome should benefit Canadian aerospace industry in competing with those from other developed countries/regions as well as from emerging economies.