Reference number : GC-2017-Q1-03552, amendment number : , agreement type : G, recipient legal name : Khameneifar, Farbod (École Polytechnique de Montréal), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Inspection in manufacturing is a crucial exercise, not only to verify the quality of the manufactured part, but also to provide the necessary feedback for process control. Without fast and accurate measurement of the manufactured part, maintaining production precision to minimize scrap parts is not possible. On today&rsquo;s advanced manufacturing shop floors, the inspection process is performed using computer-aided technologies, as opposed to traditional hard gauges and visual evaluation by experienced inspectors. A few decades ago, the introduction of computer-aided inspection (CAI) technologies (which at that time was mainly limited to the touch-trigger probes on coordinate measuring machines) opened a whole new world for manufacturers by greatly increasing the speed and accuracy of the inspection process. With the modern manufacturing processes, there is an ever-increasing need for more sophisticated computer-aided inspection technologies that can catch up with the new manufacturing practices. Today, with the advancement of additive manufacturing (AM), a process in which a part is made layer by layer, new paradigms are emerging in advanced manufacturing. Parts with extremely complex geometries and functional internal structures can be made that could never be achievable by the means of traditional subtractive manufacturing. However, in regulated industries such as aerospace, one of the most serious hurdles to the expansion of AM is the question of part qualification. The additively manufactured parts with complex geometries have a wide variety of inspection needs that are not yet addressed by current measurement systems and data analysis techniques. Once the part is completely manufactured, its internal geometry is inaccessible and impossible to be measured by conventional inspection tools relying on surface measurements. I propose here a 5-year research program with the main philosophy that the most effective and efficient way of measuring AM parts is in-process measurement in which each layer of the part is inspected as it is built. This approach enables defect detection as well as evaluation of internal geometric errors on a layer-by-layer basis. Moreover, such layer-wise inspection enables in-situ process control at each layer in the form of corrective actions. In-situ process control is the key to the introduction of AM parts in regulated industries such as aerospace. The proposed research program will develop tools for in-process shape measurement, as well as novel algorithms to enable automatic defect detection and evaluation of internal geometric errors on a layer-by-layer basis. The proposed research program is of high interest since it will close the gap between metal AM process and the precision requirements of the regulated industries such as aerospace. Furthermore, the program will train the next generation of engineers who enable the commercial success of AM in Canada., program purpose french : Inspection in manufacturing is a crucial exercise, not only to verify the quality of the manufactured part, but also to provide the necessary feedback for process control. Without fast and accurate measurement of the manufactured part, maintaining production precision to minimize scrap parts is not possible. On today&rsquo;s advanced manufacturing shop floors, the inspection process is performed using computer-aided technologies, as opposed to traditional hard gauges and visual evaluation by experienced inspectors. A few decades ago, the introduction of computer-aided inspection (CAI) technologies (which at that time was mainly limited to the touch-trigger probes on coordinate measuring machines) opened a whole new world for manufacturers by greatly increasing the speed and accuracy of the inspection process. With the modern manufacturing processes, there is an ever-increasing need for more sophisticated computer-aided inspection technologies that can catch up with the new manufacturing practices. Today, with the advancement of additive manufacturing (AM), a process in which a part is made layer by layer, new paradigms are emerging in advanced manufacturing. Parts with extremely complex geometries and functional internal structures can be made that could never be achievable by the means of traditional subtractive manufacturing. However, in regulated industries such as aerospace, one of the most serious hurdles to the expansion of AM is the question of part qualification. The additively manufactured parts with complex geometries have a wide variety of inspection needs that are not yet addressed by current measurement systems and data analysis techniques. Once the part is completely manufactured, its internal geometry is inaccessible and impossible to be measured by conventional inspection tools relying on surface measurements. I propose here a 5-year research program with the main philosophy that the most effective and efficient way of measuring AM parts is in-process measurement in which each layer of the part is inspected as it is built. This approach enables defect detection as well as evaluation of internal geometric errors on a layer-by-layer basis. Moreover, such layer-wise inspection enables in-situ process control at each layer in the form of corrective actions. In-situ process control is the key to the introduction of AM parts in regulated industries such as aerospace. The proposed research program will develop tools for in-process shape measurement, as well as novel algorithms to enable automatic defect detection and evaluation of internal geometric errors on a layer-by-layer basis. The proposed research program is of high interest since it will close the gap between metal AM process and the precision requirements of the regulated industries such as aerospace. Furthermore, the program will train the next generation of engineers who enable the commercial success of AM in Canada., agreement title english : Next-generation computer-aided inspection technologies, agreement title french : Next-generation computer-aided inspection technologies, agreement number : RGPIN, agreement value : 115000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada