A Decision Tool for Quality System Improvement Any quality process has some weaknesses, and let nonconformities run through production process. Sometimes it reaches the final customer. Organizations give their operational managers the mission to improve the quality system in order to minimize the risk of delivering nonconform products to customers. In this work, a decision tool is developed and presented to determine how to improve an existing quality control process. Firstly, a probabilistic modeling of the propagation of nonconformities is proposed and used to evaluate the Average Outgoing Quality (AOQ). Then, an iterative method is presented, based on the AOQ estimation, aimed to determine the most profitable improvements to perform. The proposed method help managers to reach their global quality target by guiding the improvement process. The proposed tool determines which particular control operation should be improved for maximizing the impact on the Average Outgoing Quality.

Practical Framework for Advanced Qualitybased Process Control in Interlinked Manufacturing Processes As the economic manufacturing of highquality products becomes an increasingly crucial competitive factor, corresponding quality assurance measures are gaining a growing interest. Even though research interest and industrial demand are both high, there is a large gap between methological approaches and practical applicability that needs to be closed. In this paper we therefore present a practical framework for advanced qualitybased process control (AQPC) in interlinked manufacturing processes. Machine learning algorithms are used to predict the expected product quality based on recorded process parameters. That information then serves as an input for the derivation of optimal control decisions. Therefore, we formulate a mathematical optimization model including different options such as order reassignment and process parameter adaption to determine an optimal set of control decisions. We then break down the optimization into a gradual procedure that allows an applicationspecific integration into manufacturing.