Analyzing the cost drivers and process optimization in additive manufacturing
01 Oct 2019-Vol. 561, Iss: 1, pp 012062
About: The article was published on 2019-10-01 and is currently open access. It has received 2 citations till now. The article focuses on the topics: Cost driver & Process optimization.
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TL;DR: In this paper , an energy value stream map (EVSM) for additive manufacturing (AM) process chains in end-use part production, augmenting methods of lean manufacturing by the energy dimension, is presented.
TL;DR: In this article , two different design techniques for customized cranial prostheses for cranial reconstruction are assessed for asymmetrical skull defects. And the results of fitting accuracy reveal that the manufactured implant's average deviation is very close to the planned reconstruction area with an error less than 1 mm, suggesting that the customized titanium implant fits the skull model quite precisely.
Abstract: Cranioplasty or cranial reconstruction is always a challenging procedure even for experienced surgeons. In this study, two different design techniques for customized cranial prostheses are assessed for cranial reconstruction. Mirror reconstruction is one of the commonly used reconstruction techniques that fails when cranial defects cross the midline of symmetry. Hence, there is a need for a design technique for the reconstruction of cranial defects irrespective of their location on the symmetrical plane. The anatomical reconstruction technique demonstrates its applicability for a wide spectrum of complex skull defects irrespective of the defective position in the anatomical structure. The paper outlines a methodological procedure involving a multi-disciplinary approach involving physicians and engineers in the design and reconstruction of customized cranial implants for asymmetrical skull defects. The proposed methodology is based on five foundation pillars including the multi-disciplinary approach, implant design process, additive-manufactured implant, implant fitting analysis, and cost and time analysis for the customized implant. The patient’s computed tomography scan data are utilized to model a customized cranial implant, which is then fabricated using electron beam melting technology. The dimensional validation of the designed and fabricated titanium implant based on the anatomical approach results in a precision of 0.6345 mm, thus indicating a better fit than the standard mirroring method. The results of fitting accuracy also reveal that the manufactured implant’s average deviation is very close to the planned reconstruction area with an error less than 1 mm, suggesting that the customized titanium implant fits the skull model quite precisely. The cost and time analysis reports that the cost for producing a customized cranial implant using electron beam melting technology is around USD 217.5 and the time taken to build is approximately 14 h and 27 min, which is low when compared to other studies. The cost and time analysis also demonstrates that the proposed design would be less burdensome to patients when compared to standard practice. Therefore, the new anatomical design process can be used effectively and efficiently to treat a number of diverse cranial abnormalities with the enhanced cranial implant design.
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TL;DR: In this paper, the ground structure method and density-based topology optimization are used to generate additive manufacturing output, with specific examples given from the fields of health, architecture and engineering.
Abstract: Topology optimization is a technique that allows for increasingly efficient designs with minimal a priori decisions. Because of the complexity and intricacy of the solutions obtained, topology optimization was often constrained to research and theoretical studies. Additive manufacturing, a rapidly evolving field, fills the gap between topology optimization and application. Additive manufacturing has minimal limitations on the shape and complexity of the design, and is currently evolving towards new materials, higher precision and larger build sizes. Two topology optimization methods are addressed: the ground structure method and density-based topology optimization. The results obtained from these topology optimization methods require some degree of post-processing before they can be manufactured. A simple procedure is described by which output suitable for additive manufacturing can be generated. In this process, some inherent issues of the optimization technique may be magnified resulting in an unfeasible or bad product. In addition, this work aims to address some of these issues and propose methodologies by which they may be alleviated. The proposed framework has applications in a number of fields, with specific examples given from the fields of health, architecture and engineering. In addition, the generated output allows for simple communication, editing, and combination of the results into more complex designs. For the specific case of three-dimensional density-based topology optimization, a tool suitable for result inspection and generation of additive manufacturing output is also provided.
361 citations
TL;DR: Functionally Graded Additive Manufacturing (FGAM) is a layer-by-layer fabrication process that involves gradationally varying the material organization within a component to achieve an intended function as mentioned in this paper.
Abstract: Functionally Graded Additive Manufacturing (FGAM) is a layer-by-layer fabrication process that involves gradationally varying the material organisation within a component to achieve an intended function. FGAM establishes a radical shift from contour modelling to performance modelling by having the performance-driven functionality built directly into the material. FGAM can strategically control the density and porosity of the composition or can combine distinct materials to produce a seamless monolithic structure. This paper presents a state-of-art conceptual understanding of FGAM, covering an overview of current techniques that can enable the production of FGAM parts as well as identify current technological limitations and challenges. The possible strategies for overcoming those barriers are presented and recommendations on future design opportunities are discussed.
262 citations
TL;DR: In this paper, the optimal connectivity between topology optimized microstructures is found by considering the assembly of adjacent cells together with the optimization of individual cells, to ensure material connectivity and smoothly varying physical properties.
Abstract: Microstructures with spatially-varying properties such as trabecular bone are widely seen in nature. These functionally graded materials possess smoothly changing microstructural topologies that enable excellent micro and macroscale performance. The fabrication of such microstructural materials is now enabled by additive manufacturing (AM). A challenging aspect in the computational design of such materials is ensuring compatibility between adjacent microstructures. Existing works address this problem by ensuring geometric connectivity between adjacent microstructural unit cells. In this paper, we aim to find the optimal connectivity between topology optimized microstructures. Recognizing the fact that the optimality of connectivity can be evaluated by the resulting physical properties of the assemblies, we propose to consider the assembly of adjacent cells together with the optimization of individual cells. In particular, our method simultaneously optimizes the physical properties of the individual cells as well as those of neighbouring pairs, to ensure material connectivity and smoothly varying physical properties. We demonstrate the application of our method in the design of functionally graded materials for implant design (including an implant prototype made by AM), and in the multiscale optimization of structures.
77 citations
"Analyzing the cost drivers and proc..." refers background or methods in this paper
...Identifying the cost drivers will aid in optimizing the cost within additive manufacturing [1]....
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...An equationderived to compute the total cost correlated along with machining cost and machining hour [1]....
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...Introduction Customization of products is one of the current trends in Industries [1]....
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