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Intelligent Fault Correction and self Optimizing Manufacturing systems (IFaCOM)
Start date: Nov 1, 2011, End date: Apr 30, 2015 PROJECT  FINISHED 

The goal of zero defect manufacturing encompasses both short and long term perspectives. The short term perspective is to develop and implement a real time process control system that eliminates the production of any faulty component due to variances in materials, components and process properties. The long term perspective is to minimize all failures by continuous optimizing of the production process and the manufacturing system.A framework of an Intelligent Fault Correction and self Optimizing Manufacturing system (IFaCOM) will be developed, which can become a general framework for manufacturing equipment and processes for different industrial branches. In this framework it is proposed to extend the use of closed loop control to all vital parameters of a component or product. In today's manufacturing it is still the case that many vital parameters are controlled indirectly, thus creating a larger variability in the output than acceptable within the zero-defect paradigm. The project will create a basic understanding of the method of direct closed loop control of vital parameters and apply this control principle both to single operations and to the entire part manufacturing process in order to eliminate the propagation of defects along the process stages.The principles can be extended to processes where the input material has too large variability leading to high defect rates in production. This involves both the development of suitable measurement and monitoring techniques of the input condition of components as well as development of the necessary actuation methods and mechanisms to implement the necessary control actions.To establish and continuously improve the closed loop methods and to extend them over the entire process chain of part manufacturing, the control models must be upgraded in accordance with the increased insight in the operations that can be obtained by analysis of large amounts of data available from multiple sensors both in the manufacturin
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