Towards a condition-monitoring framework for quality assurance in intelligent multistage manufacturing environment

Manufacturing processes, such as machining, welding or tooling and assembly are increasingly automated to reduce the costs and furthermore to negate the decrease of a skilled labor force. Each process has its own key parameters that are required to be within a certain tolerance band in order to ensure product quality, such as e.g. surface finish. The application of intelligent automation allows the manufacturer to create an environment where the sensory systems that are inherently connected to intelligent components are utilized for manufacturing process monitoring purposes. In addition this framework is meant to be used in a multistage manufacturing environment to control the propagation of variations introduced at upstream stations. The widely available smart sensors in today's manufacturing industry can assist to reduce the number of direct dimensional measurement tools required for this purpose. In this paper, a generic framework for the design of the monitoring and decision making system is demonstrated with a simulated case study in milling, using the tracking of the force rate as a successful technique to detect certain events, such as tool breakage. Moreover, the data can be used for compensation in the next production or assembly stage for variation reduction in multistage manufacturing processes.