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Triboluminescence (TL) is a phenomenon of light emission induced by impact, stress, fracture, or an applied mechanical force. This phenomenon can be used to detect, evaluate, and predict mechanical failures in composites. In this report, we utilized manganese-doped zinc-sulphide (ZnS: Mn) and Polystyrene (PS) composite to fabricate a TL functional part via additive manufacturing. The morphology of the particles inside the polymer matrix were studied using scanning electron microscopy and micro CT scan. Thermoanalytical techniques such as differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were carried out to evaluate the thermal transitions and degradation of the composites. The mechanoluminescence performance of the printed samples is evaluated by three-point flexural test and observed to depend on processing conditions that can be utilized to achieve a strong light signal at different mechanical loads. The polymer composite fabrication and processing reduced particle size, enhanced particle dispersion, and altered the mechanical properties of the polymer to help increase the mechanoluminescence response up to 10 times in the 3D printed parts. The unique mechanoluminescence properties of 3D printed luminescent composite have great potential for structural monitoring applications. 

The demand for additively manufactured polymer composites with increased specific properties and functional microstructure has drastically increased over the past decade. The ability to manufacture complex designs that can maximize strength while reducing weight in an automated fashion has made 3D-printed composites a popular research target in the field of engineering. However, a significant amount of understanding and basic research is still necessary to decode the fundamental process mechanisms of combining enhanced functionality and additively manufactured composites. In this review, external field-assisted additive manufacturing techniques for polymer composites are discussed with respect to (1) self-assembly into complex microstructures, (2) control of fiber orientation for improved interlayer mechanical properties, and (3) incorporation of multi-functionalities such as electrical conductivity, self-healing, sensing, and other functional capabilities. A comparison between reinforcement shapes and the type of external field used to achieve mechanical property improvements in printed composites is addressed. Research has shown the use of such materials in the production of parts exhibiting high strength-to-weight ratio for use in aerospace and automotive fields, sensors for monitoring stress and conducting electricity, and the production of flexible batteries. 

Additive manufacturing processes, especially those based on fused filament fabrication mechanism, have a low productivity. One solution to this problem is to adopt a collaborative additive manufacturing system that employs multiple printers/extruders working simultaneously to improve productivity by reducing the process makespan. However, very limited research is available to address the major challenges in the co-scheduling of printing path scanning for different extruders. Existing studies lack: (i) a consideration of the impact of sub-path partitions and simultaneous printing of multiple layers on the multi-extruder printing makespan; and (ii) efficient algorithms to deal with the multiple decision-making involved. This article develops an improved method by first breaking down printing paths on different printing layers into sub-paths and assigning these generated sub-paths to different extruders. A mathematical model is formulated for the co-scheduling problem, and a hybrid algorithm with sequential solution procedures integrating an evolutionary algorithm and a heuristic is customized to multiple decision-making in the co-scheduling for collaborative printing. The performance was compared with the most recent research, and the results demonstrated further makespan reduction when sub-path partition or the simultaneous printing of multiple layers is considered. This article discusses the impacts of process setups on makespan reduction, providing a quantitative tool for guiding process development. 

Additive manufacturing processes, especially those based on fused filament fabrication (FFF) mechanism, have relatively low productivity and suffer from production scalability issue. One solution is to adopt a collaborative additive manufacturing system that is equipped with multiple extruders working simultaneously to improve productivity. The collaborative additive manufacturing encounters a grand challenge in the scheduling of printing path scanning by different extruders. If not properly scheduled, the extruders may collide into each other or the structures built by earlier scheduled scanning tasks. However, there existed limited research addressing this problem, in particular, lacking the determination of the scanning direction and the scheduling for sub-path scanning. This paper deals with the challenges by developing an improved method to optimally break the existing printing paths into sub-paths and assign these generated sub-paths to different extruders to obtain the lowest possible makespan. A mathematical model is formulated to characterize the problem, and a hybrid algorithm based on an evolutionary algorithm and a heuristic approach is proposed to determine the optimal solutions. The case study has demonstrated the application of the algorithms and compared the results with the existing research. It has been found that the printing time can be reduced by as much as 41.3% based on the available hardware settings. 

Assembly system configuration determines the topological arrangement of stations with defined logical material flow among them. The design of assembly system configuration involves (1) subassembly planning that defines subassembly tasks and between-task material flows and (2) workload balancing that determines the task-station assignments. The assembly system configuration should be flexibly changed and updated to cope with product design evolution and updating. However, the uncertainty in future product evolution poses significant challenges to the assembly system configuration design since the higher cost can be incurred if the assembly line suitable for future products is very different from that for the current products. The major challenges include (1) the estimation of reconfiguration cost, (2) unavailability of probability values for possible scenarios of product evolution, and (3) consideration of the impact of the subassembly planning on the task-station assignments. To address these challenges, this paper formulates a concurrent optimization problem to design the assembly system configuration by jointly determining the subassembly planning and task-station assignments considering uncertain product evolution. A new assembly hierarchy similarity model is proposed to estimate the reconfiguration effort by comparing the commonalities among different subassembly plans of current and potential future product designs. The assembly system configuration is chosen by maximizing both assembly hierarchy similarity and assembly system throughput under the worst-case scenario. A case study motivated by real-world scenarios demonstrates the applicability of the proposed method including scenario analysis.