Reference number : GC-2017-Q1-02044, amendment number : , agreement type : G, recipient legal name : Ahmad, Rafiq (University of Alberta), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Production technologies such as subtractive (machining) &amp; additive (3D printing) machines and process automation enable precise manufacturing; however, product and process complexity leads to other challenges such as manual setup changeovers, part dislocations, feature identification, operations scheduling, tracking of material deposition, perception of robots, and collisions avoidance. These challenges lead to increasing manufacturing costs, and limit the broad implementation of existing advanced manufacturing techniques. Thus, machines need intelligent, fast, and robust systems to enhance their performance and reconfigure themselves for unexpected/unavoidable changes. The proposed research program will overcome these limitations during hybrid manufacturing (HM) of combined additive &amp; subtractive processes and robotics for enhanced accuracy, speed, quality, automation and intelligence. 
In this research program a methodologies based on knowledge from the design, initial plan, preparation and real manufacturing (vision sensors) will be developed. This will be implemented on a HM system to be designed and developed. Based on our developed snakes &amp; ladders and level-set algorithms the deposition of materiel and manufacturing strategy will be generated. Neural network and supervised-learning rules will complement the decision process. The systems developed will then be implemented on a high-level platform using standardized ontologies. Finally, the developed systems will be extended to application of multi-pass welding and assembly automation in a human-robot collaborative environment. 
The program aims to advance state-of-the-art technologies in HM and robotics by integrating machining and additive manufacturing, effective re-manufacturing to enhance clean and green technologies, safe human-machine interaction and minimizing wastes in manufacturing. The production of such innovative hybrid systems, which is faster and more advanced than existing technologies on the market will certainly benefit Canadian manufacturing industries in order to match the predicted global 3D printing compound annual growth rate of 28.5% by 2022. In addition, the program will enable the training of at least ten HQPs on cutting edge technologies., program purpose french : Production technologies such as subtractive (machining) &amp; additive (3D printing) machines and process automation enable precise manufacturing; however, product and process complexity leads to other challenges such as manual setup changeovers, part dislocations, feature identification, operations scheduling, tracking of material deposition, perception of robots, and collisions avoidance. These challenges lead to increasing manufacturing costs, and limit the broad implementation of existing advanced manufacturing techniques. Thus, machines need intelligent, fast, and robust systems to enhance their performance and reconfigure themselves for unexpected/unavoidable changes. The proposed research program will overcome these limitations during hybrid manufacturing (HM) of combined additive &amp; subtractive processes and robotics for enhanced accuracy, speed, quality, automation and intelligence. 
In this research program a methodologies based on knowledge from the design, initial plan, preparation and real manufacturing (vision sensors) will be developed. This will be implemented on a HM system to be designed and developed. Based on our developed snakes &amp; ladders and level-set algorithms the deposition of materiel and manufacturing strategy will be generated. Neural network and supervised-learning rules will complement the decision process. The systems developed will then be implemented on a high-level platform using standardized ontologies. Finally, the developed systems will be extended to application of multi-pass welding and assembly automation in a human-robot collaborative environment. 
The program aims to advance state-of-the-art technologies in HM and robotics by integrating machining and additive manufacturing, effective re-manufacturing to enhance clean and green technologies, safe human-machine interaction and minimizing wastes in manufacturing. The production of such innovative hybrid systems, which is faster and more advanced than existing technologies on the market will certainly benefit Canadian manufacturing industries in order to match the predicted global 3D printing compound annual growth rate of 28.5% by 2022. In addition, the program will enable the training of at least ten HQPs on cutting edge technologies., agreement title english : Hybrid intelligent system for Manufacturing (Hi4Man), agreement title french : Hybrid intelligent system for Manufacturing (Hi4Man), agreement number : RGPIN, agreement value : 105000.0, 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