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Abstract While three-dimensional (3D) printing has been making significant strides over the past decades, it still trails behind mainstream manufacturing due to its lack of scalability in both print size and print speed. Cooperative 3D printing (C3DP) is an emerging technology that holds the promise to mitigate both of these issues by having a swarm of printhead-carrying mobile robots working together to finish a single print job cooperatively. In our previous work, we have developed a chunk-based printing strategy to enable the cooperative 3D printing with two fused deposition modeling (FDM) mobile 3D printers, which allows each of them to print one chunk at a time without interfering with the other and the printed part. In this paper, we present a novel method in discretizing the continuous 3D printing process, where the desired part is discretized into chunks, resulting in multi-stage 3D printing process. In addition, the key contribution of this study is the first working scaling strategy for cooperative 3D printing based on simple heuristics, called scalable parallel arrays of robots for 3DP (SPAR3), which enables many mobile 3D printers to work together to reduce the total printing time for large prints. In order to evaluate the performance of the printing strategy, a framework is developed based on directed dependency tree (DDT), which provides a mathematical and graphical description of dependency relationships and sequence of printing tasks. The graph-based framework can be used to estimate the total print time for a given print strategy. Along with the time evaluation metric, the developed framework provides us with a mathematical representation of geometric constraints that are temporospatially dynamic and need to be satisfied in order to achieve collision-free printing for any C3DP strategy. The DDT-based evaluation framework is then used to evaluate the proposed SPAR3 strategy. The results validate the SPAR3 as a collision-free strategy that can significantly shorten the printing time (about 11 times faster with 16 robots for the demonstrated examples) in comparison with the traditional 3D printing with single printhead. 

Purpose The purpose of this research is to develop a new slicing scheme for the emerging cooperative three-dimensional (3D) printing platform that has multiple mobile 3D printers working together on one print job. Design/methodology/approach Because the traditional lay-based slicing scheme does not work for cooperative 3D printing, a chunk-based slicing scheme is proposed to split the print job into chunks so that different mobile printers can print different chunks simultaneously without interfering with each other. Findings A chunk-based slicer is developed for two mobile 3D printers to work together cooperatively. A simulator environment is developed to validate the developed slicer, which shows the chunk-based slicer working effectively, and demonstrates the promise of cooperative 3D printing. Research limitations/implications For simplicity, this research only considered the case of two mobile 3D printers working together. Future research is needed for a slicing and scheduling scheme that can work with thousands of mobile 3D printers. Practical implications The research findings in this work demonstrate a new approach to 3D printing. By enabling multiple mobile 3D printers working together, the printing speed can be significantly increased and the printing capability (for multiple materials and multiple components) can be greatly enhanced. Social implications The chunk-based slicing algorithm is critical to the success of cooperative 3D printing, which may enable an autonomous factory equipped with a swarm of autonomous mobile 3D printers and mobile robots for autonomous manufacturing and assembly. Originality/value This work presents a new approach to 3D printing. Instead of printing layer by layer, each mobile 3D printer will print one chunk at a time, which provides the much-needed scalability for 3D printing to print large-sized object and increase the printing speed. The chunk-based approach keeps the 3D printing local and avoids the large temperature gradient and associated internal stress as the size of the print increases.