Manufacturing processes like aeroengine manufacturing, sheet manufacturing or rod manufacturing are examples of complex engineered systems because they have many interconnected components and there is little knowledge about the interactions between these different components. These processes consist of a raw material in the form of powder or a preform (pre-manufactured shape) which is an input from another manufacturing process and through a series of steps, converts it into a product. These manufacturing processes are designed and operated to achieve a specific goal: the final quality of the product being output from that process.
The current design cycle for these different manufacturing processes treats the different system components (sub-processes) in isolation. Each engineer and personnel looks at the problem in his own perspective and optimizes the solution pertaining to the requirements or specifications of his particular department or sub-process only.This approach leads to a non-optimal design and lot of variation in the quality attributes.
To overcome these limitations, a new approach and methodology for the design of these systems is presented in this dissertation. This methodology decomposes the quality attribute into the various factors which affect it and determine its value. These factors are further decomposed into the physical phenomena which cause these factors to affect the quality attribute. The physical phenomena are finally decomposed into the manufacturing processes and material uncertainties which cause them to influence the quality attributes.Interdependencies are determined between the different sub-processes and only those sub-processes are concentrated on which affect the quality attributes.
Novel approach of combining process models with the data obtained by testing sensors is developed through the use of Bayesian Hierarchical modeling. Case studies involving sheet, rod and aeroengine manufacturing are demonstrated. The developed Bayesian models are used in designing these processes for improved quality.