Study regarding the influence of material type on economic objectives in MEX fabrication

Material Extrusion has been used extensively as an additive manufacturing technology for a variety of applications like visual models, functional prototypes, tooling components, patterns for castings, and final parts. The current research paper proposes a study on the material type influence on economic objectives in material extrusion fabrication of complex assemblies. Three economic objectives have been analysed, namely, estimated fabrication time, material usage and material cost, whilst two commercial additive manufacturing machines have been considered for the simulation. Cura and ZSuite slicing software were used for the generation of Gcode and project files. Five filaments were selected from the same manufacturer and all components of the selected assembly were included in the analysis. Throughout the study, the additive manufacturing parameters were kept constant, as well as the component layout on the build platform of the two machines. Study results were analysed in correspondence with the manufacturing requirements and the optimum fabrication scenario was selected. Further research includes the analysis of multiple material manufacturers, in order to evaluate the influence of chemical composition on economic outputs.

A Rapid Fabrication Methodology for Payload Modules, Piloted for the Observation of Queen Honey Bees (Apis mellifera) in Microgravity

Microgravity experiment modules for living organisms have been instrumental to space research, yet their design remains complex and costly. As the private space sector enables more widely available payloads for researchers, it is increasingly necessary to design experimental modules innovatively so that they are proportionately accessible. To ease this bottleneck, we developed a rapid fabrication methodology for producing custom modules compatible with commercial payload slots. Our method creates a unified housing geometry, based on a given component layout, which is fabricated in a digital design and subtractive manufacturing process from a single lightweight foam material. This module design demonstrated a 25–50% reduction in chassis weight compared with existing models, and is extremely competitive in manufacturing time, simplicity, and cost. To demonstrate the ability to capture data on previously limited areas of space biology, we apply this methodology to create an autonomous, video-enabled module for sensing and observing queen and retinue bees aboard the Blue Origin New Shepard 11 (NS-11) suborbital flight. To explore whether spaceflight impacts queen fitness, results used high-definition visual data enabled by the module's compact build to analyze queen-worker regulation under microgravity stress (n = 2, with controls). Overall, this generalizable method for constructing experimental modules provides wider accessibility to space research and new data on honey bee behavior in microgravity.

A collaborative design method for satellite module component assignment and layout optimization

The collaborative design of the multi-module satellite component (equipment) assignment and layout is the key aspect of the overall satellite design, and the two parts are closely related. In the past, satellite module component layout optimization usually adopted fixed component assignments, which remained constant in the layout optimization stage. If the components were improperly distributed in these modules, it would seriously affect the layout optimization. To overcome this disadvantage, a collaborative design method for the component assignment and layout design is presented for the multi-module (or multi-bearing plate) satellite component layout problem, based on a multi-agent system. First, the component assignment agent adopted a multi-objective optimization method (the non-dominated sorting genetic algorithm II, NSGA-II) to obtain the approximate Pareto solution set of the satellite component assignment scheme. Second, it adopted a fuzzy multi-objective decision method to select a high-quality component assignment scheme from the approximate Pareto solution set. Third, the layout agent employed a dual system co-evolutionary method for the layout optimization design. In the process of the layout optimization, the layout result is fed back to the component assignment design, and the component assignment is adjusted according to the result of the layout optimization. Thus, the above process is continually iterated to achieve the optimal collaborative design of the component assignment and the layout. The proposed method is applied to a simplified multi-module satellite component assignment and layout optimization problem and aims to provide a reference and technical support for other similar multi-module equipment assignment and layout optimization problems.

Farsi document image recognition system using word layout signature

In this paper, a new representation of Farsi words is proposed to present the keyword spotting problems in Farsi document image retrieval. In this regard, we define a signature for each Farsi word based on the word connected component layout. The mentioned signature is shown as boxes, and then, by sketching vertical and horizontal lines, we construct a grid of each word to provide a new descriptor. One of the advantages of this method is that it can be used for both handwritten and machine-printed texts. Finally, to evaluate the performance of our system in comparison to other methods, a database that contains 19,582 printed Farsi words is examined, and after applying this approach, a recall rate of 98.1% and a precision rate of 94.3% are obtained.