Mold Feature Recognition using Accessibility Analysis for Automated Design of Core, Cavity, and Side-Cores and Tool-Path Generation of Mold Segments
MetadataShow full item record
Injection molding is widely used to manufacture plastic parts with good surface finish, dimensional stability and low cost. The common examples of parts manufactured by injection molding include toys, utensils, and casings of various electronic products. The process of mold design to generate these complex shapes is iterative and time consuming, and requires great expertise in the field. As a result, a significant amount of the final product cost can be attributed to the expenses incurred during the product’s design. After designing the mold segments, it is necessary to machine these segments with minimum cost using an efficient tool-path. The tool-path planning process also adds to the overall mold cost. The process of injection molding can be simplified and made to be more cost effective if the processes of mold design and tool-path generation can be automated. This work focuses on the automation of mold design from a given part design and the automation of tool-path generation for manufacturing mold segments. The hypothesis examined in this thesis is that the automatic identification of mold features can reduce the human efforts required to design molds. It is further hypothesised that the human effort required in many downstream processes such as mold component machining can also be reduced with algorithmic automation of otherwise time consuming decisions. Automatic design of dies and molds begins with the part design being provided as a solid model. The solid model of a part is a database of its geometry and topology. The automatic mold design process uses this database to identify an undercut-free parting direction, for recognition of mold features and identification of parting lines for a given parting direction, and for generation of entities such as parting surfaces, core, cavity and side-cores. The methods presented in this work are analytical in nature and work with the extended set of part topologies and geometries unlike those found in the literature. Moreover, the methods do not require discretizing the part geometry to design its mold segments, unlike those found in the literature that result in losing the part definition. Once the mold features are recognized and parting lines are defined, core, cavity and side-cores are generated. This work presents algorithms that recognize the entities in the part solid model that contribute to the design of the core, cavity and side-cores, extract the entities, and use them in the design of these elements. The developed algorithms are demonstrated on a variety of parts that cover a wide range of features. The work also presents a method for automatic tool-path generation that takes the designed core/cavity and produces a multi-stage tool-path to machine it from raw stock. The tool-path generation process begins by determining tool-path profiles and tool positions for the rough machining of the part in layers. Typically roughing is done with large aggressive tools to reduce the machining time; and roughing leaves uncut material. After generating a roughing tool-path for each layer, the machining is simulated and the areas left uncut are identified to generate a clean-up tool-path for smaller sized tools. The tool-path planning is demonstrated using a part having obstacles within the machining region. The simulated machining is presented in this work. This work extends the accessibility analysis by retaining the topology information and using it to recognize a larger domain of features including intersecting features, filling a void in the literature regarding a method that could recognize complex intersecting features during an automated mold design process. Using this information, a larger variety of new mold intersecting features are classified and recognized in this approach. The second major contribution of the work was to demonstrate that the downstream operations can also benefit from algorithmic decision making. This is shown by automatically generating roughing and clean-up tool-paths, while reducing the machining time by machining only those areas that have uncut material. The algorithm can handle cavities with obstacles in them. The methodology has been tested on a number of parts.
Cite this work
Rajnish Bassi (2012). Mold Feature Recognition using Accessibility Analysis for Automated Design of Core, Cavity, and Side-Cores and Tool-Path Generation of Mold Segments. UWSpace. http://hdl.handle.net/10012/7000