Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Mechanical Engineering


Dr. Tim Nye


Dr. Allan Spence

Committee Member

Dr. Don Metzger


An adaptive forging schedule procedure that targets forging simple 3-D external profiles on a flexible forging cell is presented. The cell is composed of a numerically controlled press, a robot for workpiece manipulation, a shape feedback system and a main supervisory computer. The scheduling procedure utilizes the shape error, computed from the required and the initial workpiece shapes, to plan and execute a set of forging steps. The feedback system is then used to capture the deformed shape of the workpiece and update the shape error to adaptively plan the next set of forging steps. This adaptive control loop iterates until the workpiece shape is forged within a preset tolerance. The reduction in height and the bite values used in the schedule are limited by a set of technological bounds. Several of those bounds were identified and modelled as constraints on the adaptive scheduling procedure. Illustrative case studies showed that the adaptive scheduling procedure successfully forged external profiles (given an arbitrarily set tolerance limit) when a-priori approaches failed. The studies also showed that the new scheduling procedure could forge 2-D and 3-D profiles as easily (in terms of programming effort) as forging a uniform billet. Three new spread prediction models are developed, of which the newly developed Incrementally Updated Upper Bound model proved to provide the most accurate spread estimate compared to other developed and traditional spread prediction models. This model was then chosen to be integrated with the adaptive scheduling procedure to form an intelligent forging schedule procedure. The integration provided predictive capabilities to the adaptive scheduling module and enabled the generation of better quality forging schedules. In a typical example the number of forging steps in the forging schedule were reduced from six (using the adaptive scheduling procedure) to two (using the intelligent scheduling one).

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