Pre-processing methodology for optimizing stereolithography apparatus build performance

Canellidis, V.; Dedoussis, V.; Mantzouratos, N.; Sofianopoulou, Stella

doi:10.1016/j.compind.2006.02.004

Cited by 46 publications

(39 citation statements)

References 15 publications

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“…The other measure that could be used to determine the optimal part build orientation is the building time without compromising the surface quality. Canellidis et al [2] considered that the building time includes the time required to manufacture the object as well as the time required for support removal and surface finishing. However, Zhao [9] considered the building time as the preparation time that includes the time required to move down the platform during the re-coating, the scraping time and other preparation times.…”

Section: Problem Formulationmentioning

confidence: 99%

“…One of the current challenges is the reduction of construction time through adoption of rapid prototyping technologies, whose performance can depend on the way parts are oriented on the build platform. Therefore, each part should be appropriately oriented to achieve better surface quality and either minimal support structure or lower building time in order to result in a process more environmental friendly since it will require less energy consumption and material waste [2].…”

Section: Introductionmentioning

confidence: 99%

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On optimizing the build orientation problem using genetic algorithm

Matos

Rocha

Pereira

2019

AIP Conference Proceedings

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Build orientation is a critical issue in Additive manufacturing (AM), where three-dimensional objects are created layerby-layer directly from a 3D CAD model, since it is associated with the object accuracy, the number of supports required and the processing time to produce the object. Finding the best build orientation in the AM will reduce, significantly, the building costs and will improve the object accuracy. This work presents the solutions obtained by the Genetic Algorithm (GA) in solving the part build orientation optimization problem, considering the staircase effect, support area characteristics and the building time of four models. Preliminary experiments show that GA gives competitive results in solving the build orientation problem when compared with other metaheuristics.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On optimizing the build orientation problem using genetic algorithm

Matos

Rocha

Pereira

2019

AIP Conference Proceedings

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“…Selective Laser Sintering), little work has been done concerning the 2D problem [9], [10]. Taking into account the nature of the problem, it can be considered as a 2D nesting problem, the term "nesting problem" defined as "a process where more than one piece of irregular shape must be placed in a configuration with the other piece(s) in order to optimize an objective" [11].…”

Section: Previous Workmentioning

confidence: 99%

Effective nesting of Layer Manufacturing fabricated parts using a Genetic Algorithm and a bottom-left ray casting procedure

Canellidis

Giannatsis

Dedoussis

2010

2010 IEEE International Conference on Industrial Engineering and Engineering Management

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Two aspects have been identified to be the key elements to the effective utilization of Layer Manufacturing (LM) technologies, that is maximization of the build volume and part orientation. The present work examines the utilization of a Genetic Algorithm in conjunction with effective placement rules as a mean of optimizing the build volume of LM technologies. The optimization is achieved via the dense nesting of parts, to be fabricated, on the LM machine platform. The software tool developed tackles the 2D nesting problem associated with the parts projections on the machine platform. The effectiveness and reliability of the proposed methodology is demonstrated via a case study concerning representative "real-world" parts/objects with quite general free form geometry.

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“…Despite the improvement of resolution of scanners from macros to micros, one of the major reasons that this technique has not yet been largely used in practice is due to its loose accuracy and inconsistency, especially when it is applied to those assemblies requiring high precision. The accuracy of a fi nished component is infl uenced by many effects, from a preparation process [ 17 ], operating conditions [ 18 , 19 ], a post-process [ 20 ], and other manufacturing processes with specifi c chemical reaction [ 21 ]. A standard operation procedure is defi ned to overcome these issues making loose accuracy and inconsistency to allow a printed model fi tted with a manufactured zirconium denture, as shown in Fig.…”

Section: D Printing Applications In Digital Dentistrymentioning

confidence: 99%

Open-Source Technologies and Workflows in Digital Dentistry

Kuo

Fang

2016

Interface Oral Health Science 2016

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The Medical Device Innovation Center (MDIC) at the National Cheng Kung University has developed a complete and professional digital dentistry design workfl ow with cutting-edge equipment and software. MDIC certifi ed with ISO13485 can provide total solutions in digital dentistry. An "Intelligent Manufacturing Systems Center" (IMSC) has been established using dental open technologies toward providing digital dentistry training and restoration design services. This digital dental laboratory is able to control the entire digital process from digital impressions to the CAD/CAM creation of the restoration and model milling. An intraoral scanner is used to make digital impressions for 3D geometric models from the chair side or from traditional impressions. In the design phase, three different commercial software packages are considered for the design portion. After importing the digital impression STL data fi le, one or more of these packages are used to design the restoration. The design is then sent to a fi ve-axis milling machine for production. The CNC machines are chosen for machining or milling of the prosthetics from various materials including wax, PMMA, zirconia, chromium cobalt, resin nano-ceramics, glass ceramics, lithium disilicate, silicate ceramics, and titanium. As a cloud base solution, these design packages allow a connection to a remote manufacturing site. Our R&D team built a web-based cloud solution that can be deployed to each pertinent location. All data from the design package is stored on a private cloud which is then automatically synced to the remote public cloud. Work orders from various sources are then processed by any remote technician. Through the above settings, we may produce several common digital dentistry products including crowns and bridges, veneers, inlays and onlays, temporary crowns, and virtual diagnostic wax-ups. This digital dentistry laboratory is also equipped to handle advanced clinical cases such as implant planning, digital smile design analysis and customized surgical guides, custom abutments, implant bridges and bar designs, and orthodontics. Digital animation is applied for patient education and communication. For academics and training, a comprehensive digital technology training program has been developed to help dentists and dental technicians.

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Pre-processing methodology for optimizing stereolithography apparatus build performance

Cited by 46 publications

References 15 publications

On optimizing the build orientation problem using genetic algorithm

On optimizing the build orientation problem using genetic algorithm

Effective nesting of Layer Manufacturing fabricated parts using a Genetic Algorithm and a bottom-left ray casting procedure

Open-Source Technologies and Workflows in Digital Dentistry

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