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Abstract:

In a postmodern world where mass customization of products is a key driver of modern manufacturing systems design, the quick and accurate shaping of metallic shapes has acquired significant importance in key frontiers of technological developments. While additive manufacturing techniques have bridged the gap in terms of rapid manufacture of certain products, the possibility of flexible and rapid manufacture of sheet metal products on the other hand has been supported by the developments in incremental sheet deformation techniques. Specifically, single point incremental sheet forming or SPIF has come forward as a potential industrial technology of the future that can help shape sheet metal with the help of a tool and without any supporting dies, that can deform a sheet incrementally by following a defined toolpath. This toolpath, in turn, can be generated with a CAD/CAM software, for a given part geometry.The single point incremental sheet forming process comes with a number of limitations, which hinder its implementation in industry. Specifically, the process was characterized by material and process parameter specific forming limits and low accuracy at the outset of this research. The existing state of the art in incremental forming proposed a feature-based accuracy improvement system based on a broad classification of part features into planes, ruled features, freeform features and ribs. However, such a classification was not refined enough to produce accurate parts consistently and within specified tolerances. To overcome low forming limits, a laser-based dynamic heating system is available. Besides, formability can be improved by using multi-step toolpaths where a part is formed in steps starting with a part with wall angles lower than the final part and increasing the wall angles in subsequent steps. While both techniques result in improved formability, there are certain drawbacks in these techniques which need to be overcome. While the dynamic heating system can extend forming limits of specific materials, multi-step toolpaths can lead to high processing times, and non-uniform bottom surfaces.In this research, steps were taken to improve upon the existing state of the art in the incremental sheet forming process using an experimental campaign on study of behavior of part features, in-process digital image correlation (DIC) studies and developing advanced process planning tools for generating optimized toolpaths that helped improve upon the drawbacks existing at the start of the research. Specifically, to improve on the accuracy, a detailed taxonomy of 33 sheet metal feature types was created. A matrix of interactions between features was generated based on experimental studies on interactions. These details were captured in a process planning system developed in Visual C# as a continuation of previous work done in the research group, to detect and identify the features, and join the features in a network creating conceptual graphs that captures all the different interactions between features based on neighborhoodrelations. Based on this network, toolpath strategies can be selected from a database of ranked toolpath strategies, and used to generate optimized toolpaths, by sequencing and integrating partial toolpaths into continuous toolpaths. A number of case studies were conducted on parts with maximum dimensions determined by the size of the machine tool setup (180 mm x 180 mm blank size) showing average absolute deviations less than 0.5 mm. Besides, in a number of test cases where uncompensated toolpaths result in maximum deviations larger than 4 mm, the maximum deviations were reduced to less than 1 mm using the optimized strategies.In addition, a number of toolpath strategies based on mathematical compensation techniques using multivariate adaptive response splines (MARS) based predictions, systematic multi step mesh morphing, location specific toolpaths, intelligent offsetting and bottom pre-forming were explored. Using a digital image correlation based measurement set up in collaboration with researchers from the Vrije Universiteit Brussels (VUB), the effect of material properties on the accuracy response surfaces was studied, and generic error correction functions based on material, thickness and size were proposed to improve the accuracy of parts.In order to address the second issue of forming limits, a new system was developed based on the observation of higher ductility limits at low temperatures. In this setup, an in-process cryogenic fluid was used to locally chill down the sheet material to temperatures below -100°C, which led to a limited increase in formability limits for aluminium alloys AA 1050, AA 3103 and AA 5754. Test cases showing this improvement were conducted.To illustrate the achievements of the above improvements in the course of the current research, a number of different applications of incremental forming were selectively undertaken as case studies. Few of these applications include a thin sheet die manufacture, a 3D human face mask manufacture, cranial implant manufacture, and airfoils for aerospace applications, using different sheet materials such as aluminium alloys (AA 1050, AA 3103, AA 5754), low carbon steel alloy DC01, Titanium grade 2 and stainless steel (AISI 304), where improvements in both accuracy and formability were illustrated.