Abstract:Binder jetting additive manufacturing (BJAM) is a comparatively low-cost process that enables manufacturing of complex and customizable metal parts. This process is applied to low-cost wateratomized iron powder with the goal of understanding the effects of printing parameters and sintering schedule on maximizing the green and sintered densities of manufactured samples respectively. The powder is characterized by using scanning electron microscopy (SEM) and particle size analysis (Camsizer X2). In the AM proces… Show more
“…2 is devoted to the “purely” additive manufacturing stage using the BJP technique alone. As was explained above, such a method enables production of complex geometrical structures, however the porosity of such parts is high (~ 50–60%), and their density is low 22 , 24 , 29 . The second route involved uniaxial pressing (compaction moulding) and was performed purely to illustrate the density/porosity achievable from the “traditional” route (CM-samples).…”
Section: Methodsmentioning
confidence: 99%
“…Unlike other methods, the BJP method does not require a rigid die for sample preparation 32 . Moreover, BJP can produce geometrically complex parts free from residual stresses and with controlled porosity 24 . Figure 3 ( a ) Scanning electron microscopy (SEM) image showing graphite powder morphology and ( b ) Particle size distribution of the graphite powder used.…”
Section: Methodsmentioning
confidence: 99%
“…Unlike other methods, the BJP method does not require a rigid die for sample preparation 32 . Moreover, BJP can produce geometrically complex parts free from residual stresses and with controlled porosity 24 .…”
Section: Binder Jetting Printing (Bjp)mentioning
confidence: 99%
“…Attempts have recently been made to apply BJP to manufacture graphite-based structures with required physical properties 18 – 20 , 22 , 23 . One of the advantages of the BJP process is the capability to achieve the required density and mechanical performance using typical post-processing such as the reaction sintering or liquid metal infiltration 22 , 24 , 25 . The limited reported data about the possible density of graphite and carbon-containing materials by BJP shows for instance that the part density of graphene-based electrodes processed by BJP was only 0.44 g/cm 3 19 .…”
This study introduces two hybrid processes integrating an additive manufacturing technique with post-processing treatments namely (i) Binder Jetting Printing (BJP) + Cold Isostatic Pressing (CIP) + cycle and (ii) BJP + cycle where cycle refers to a sequence of Impregnation—Drying—Pyrolysis. These two new processes yielded additively manufactured parts with higher density and reduced defects/porosities. As a testbed, we used these new processes to fabricate graphite structures. The samples produced by both methods were compared with each other and benchmarked to the samples produced by (a) BJP alone and (b) Traditional uniaxial pressing like compaction moulding. Various characterisation methods were used to investigate the microstructure and mechanical properties which showed that the porosity of hybrid manufactured samples reduces from 55% to a record 7%. This technological pathway is expected to create a new avalanche of industrial applications that are hitherto unexplored in the arena of hybrid additive manufacturing with BJP method.
“…2 is devoted to the “purely” additive manufacturing stage using the BJP technique alone. As was explained above, such a method enables production of complex geometrical structures, however the porosity of such parts is high (~ 50–60%), and their density is low 22 , 24 , 29 . The second route involved uniaxial pressing (compaction moulding) and was performed purely to illustrate the density/porosity achievable from the “traditional” route (CM-samples).…”
Section: Methodsmentioning
confidence: 99%
“…Unlike other methods, the BJP method does not require a rigid die for sample preparation 32 . Moreover, BJP can produce geometrically complex parts free from residual stresses and with controlled porosity 24 . Figure 3 ( a ) Scanning electron microscopy (SEM) image showing graphite powder morphology and ( b ) Particle size distribution of the graphite powder used.…”
Section: Methodsmentioning
confidence: 99%
“…Unlike other methods, the BJP method does not require a rigid die for sample preparation 32 . Moreover, BJP can produce geometrically complex parts free from residual stresses and with controlled porosity 24 .…”
Section: Binder Jetting Printing (Bjp)mentioning
confidence: 99%
“…Attempts have recently been made to apply BJP to manufacture graphite-based structures with required physical properties 18 – 20 , 22 , 23 . One of the advantages of the BJP process is the capability to achieve the required density and mechanical performance using typical post-processing such as the reaction sintering or liquid metal infiltration 22 , 24 , 25 . The limited reported data about the possible density of graphite and carbon-containing materials by BJP shows for instance that the part density of graphene-based electrodes processed by BJP was only 0.44 g/cm 3 19 .…”
This study introduces two hybrid processes integrating an additive manufacturing technique with post-processing treatments namely (i) Binder Jetting Printing (BJP) + Cold Isostatic Pressing (CIP) + cycle and (ii) BJP + cycle where cycle refers to a sequence of Impregnation—Drying—Pyrolysis. These two new processes yielded additively manufactured parts with higher density and reduced defects/porosities. As a testbed, we used these new processes to fabricate graphite structures. The samples produced by both methods were compared with each other and benchmarked to the samples produced by (a) BJP alone and (b) Traditional uniaxial pressing like compaction moulding. Various characterisation methods were used to investigate the microstructure and mechanical properties which showed that the porosity of hybrid manufactured samples reduces from 55% to a record 7%. This technological pathway is expected to create a new avalanche of industrial applications that are hitherto unexplored in the arena of hybrid additive manufacturing with BJP method.
“…Taking Tripp Trapp, a chair that "grows" with children, for example, Ghobakhloo et al [23] expounded a modular design method for parts replacement and upgrading of children's furniture, and summarized three principles for the green design and manufacturing of children's furniture: following children's growth, environmentally friendly materials, and space conservation. For the green design of children's furniture, Rishmawi et al [24] advised children's furnituremakers to adopt the decomposable compressed solid wood panels or laminated veneer materials that are certified by Forest Stewardship Council (FSC), the relatively lightweight disassembly and assembly method of wood screws, and green packaging materials like corrugated paper or polyethylene plastic.…”
With the differentiation of the furniture market, there is a growing demand for children’s furniture. The design of children’s furniture must fully consider the special cognition and preference of children, highlight environmental friendliness and health, and benefit the physical and mental development of children. These design objectives are similar to those of green furniture. Therefore, it is necessary to accurately evaluate the quality of green manufacturing, the key link of green furniture production, with the aid of the excellent data processing technique of artificial intelligence (AI). Thus, this paper summarizes the AI applications in quality testing of children’s furniture and statistical analysis on its greenness, and constructs an evaluation model for green manufacturing quality of children’s furniture. Firstly, the authors introduced the architecture of the green manufacturing system for children’s furniture, and analyzed the product lifecycle and environmental pollutions. On this basis, a complete and scientific evaluation index system (EIS) was constructed. Next, the weight coefficients of the goal layer and criteria layer were determined by the entropy method, and the initial evaluation result were provided. Finally, a comprehensive evaluation model was established for the green manufacturing quality of children’s furniture, based on backpropagation neural network (BPNN), and genetic algorithm with adaptive mutation (AMGA). The proposed EIS and model were proved effective through experiments. The research results provide a reference for the quality evaluation in other fields.
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