Automated post machining process planning for a new hybrid manufacturing method of additive manufacturing and rapid machining

Chen, Niechen; Barnawal, Prashant; Frank, Matthew C.

doi:10.1108/rpj-04-2017-0057

Cited by 18 publications

(5 citation statements)

References 14 publications

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“…Then, using the information about critical features, visualization analysis is performed [2], and sacrificial support structures are added to fixture components in such a way to allow machining of critical features without interference. The AMF-TOL file is updated to include these support structures, and machining allowances can be automatically generated to ensure there is enough material to remove during machining [1].…”

Section: Digital Additive and Subtractive Hybrid (Dash)mentioning

confidence: 99%

“…Additive manufacturing is "a process of joining materials to make objects from 3D model data; usually layer upon layer, as opposed to subtractive manufacturing methodologies" [5]. This type of manufacturing process expands the geometric capabilities that can be attained with traditional subtractive machining techniques [2]. These geometrical advantages lead to some great use cases for AM parts in medical and aerospace industries to produce custom components with very organic shapes including mesh structures [6][7][8].…”

Section: Additive Manufacturingmentioning

confidence: 99%

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Automatic feature-based inspection and qualification for additively manufactured parts with critical tolerances

Kelly,

Wysk,

Harrysson

et al. 2024

IJMTM

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KELLY, CHRISTOPHER JAMES. Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances (Under the direction of Dr. Richard Wysk and Dr. Ola Harrysson).This thesis focuses on extending the capabilities of the Digital Additive and Subtractive Hybrid (DASH) system by extending the functionality of the system to include some "geometric qualification" of mechanical products. Specifically, the developments for this research incorporate the extended Additive Manufacturing Format files (AMF-TOL) which include American Society of Mechanical Engineers (ASME) Y14.5 specifications for planes, cylinders and circular features so that "in-process" inspection can be completed automatically as part of the hybrid process. This work utilizes a Renishaw touch probe paired with the Renishaw Inspection plus software to collect sample data points to create confidence bounds on the accuracy of size and position of finished cylindrical features. Size, location, and tolerance callouts for specified features are gathered directly from the AMF-TOL file used as part of the existing DASH system. With this information, Numerical Control (NC) code for the probing device is automatically generated, which can be inserted into the existing program to be executed on the Computer Numerical Control (CNC) machine. These probing commands incorporate machine specific writing commands (DPRNT) to automatically export measured values to a computer. These values can then be placed directly into a Microsoft Excel spreadsheet which utilizes a nonlinear least squares regression algorithm to create statistical bounds on the true size and position of the cylindrical feature. These statistical bounds can then be compared to the specified tolerance callouts to determine whether a part is within specification, with a userdefined level of confidence.

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Section: Digital Additive and Subtractive Hybrid (Dash)mentioning

confidence: 99%

Section: Additive Manufacturingmentioning

confidence: 99%

Automatic feature-based inspection and qualification for additively manufactured parts with critical tolerances

Kelly,

Wysk,

Harrysson

et al. 2024

IJMTM

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“…Zheng et al [20] study hybrid process planning based on cost minimization models focused on remanufacturing. In [42,85,[110][111][112] the hybrid process is studied by separately attending each activity.…”

Section: Hybrid Manufacturing Process Planning Modelsmentioning

confidence: 99%

Hybrid manufacturing process planning with predictive approach: a comprehensive literature review

Velázquez

Simon²,

Helleno³

2022

Preprint

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The hybrid manufacturing has attracted industrial community interest due to its ability to produce functional parts with varied geometries, using different types of materials in the most varied applications. As with most manufacturing processes, before executing the hybrid process for the manufacture of a certain geometry, it is important to make a proper process planning that allows having an integral and proactive view of the operation. This work aims to synthesize through a systematic literature review (SLR) the state of the art on hybrid manufacturing process planning (HMPP) models with predictive approach. Three SLRs were developed to extract the articles of interest (2012-2022) from Science Direct, Springer Link, and Web of Science databases. PRISMA method was used to gather the papers and oriented the qualitative and quantitative analysis. Snowballing technique was used to gather articles of interest out of the period defined. Literature review showed that there is still no consensus between existing HMPP models, regarding all the activities necessary to ensure proper operation. In addition, the developed models have a limitation regarding the inclusion of a process simulation step. The simulation step on the existing models, does not allow to proactively check whether the experimental process conditions are adequate to ensure the manufacture of the modeled geometry before running the hybrid manufacturing process. An efficient simulation step would ensure a predictive approach to operation performance and would imply the reduction of geometric deviations without the need for excessive experimentation, reducing material consumption, manufacturing time, and resulting in a better deposition strategy. Using computational and statistical methods as support for decision-making in the process will allow the processing and analysis of data to assertively direct the structuring of a robust model for HMPP with predictive approach. A differentiated, more complete, and comprehensive process planning model is a relevant study opportunity for future research. This paper contributes to the theory development since it identifies and analyzes the existing HMPP models, highlights important gaps on the subject, and proposes insights for future development.

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“…Within AMF Creator, the user can specify critical features, material conditions, datum and tolerances associated with each feature and save this information directly into the AMF-TOL file. Then, using the information about critical features, visualization analysis is performed [4], and sacrificial support structures are added to fixture components in such a way to allow machining of critical features without interference. The AMF-TOL file is updated to include these support structures, and machining allowances can be automatically generated to ensure there is enough material to remove during machining [3].…”

Section: Introductionmentioning

confidence: 99%

Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances

King,

Harrysson,

Wysk

et al. 2023

IJMTM

View full text Add to dashboard Cite

This work focuses on expanding the capabilities of the Digital Additive and Subtractive Hybrid (DASH) system by extending the functionality to include some "geometric qualification" of mechanical products. Specifically, the developments for this research incorporate the extended Additive Manufacturing Format files (AMF-TOL) which include American Society of Mechanical Engineers (ASME) Y14.5 specifications for planes, cylinders and other features so that "in-process" inspection can be completed automatically as part of the hybrid process. A Renishaw touch probe is used to perform On Machine Measurements (OMM), collecting sample radii to create confidence bounds on the accuracy of size and position of finished cylindrical features. Measurements are imported to a spreadsheet where a nonlinear least squares regression algorithm creates statistical bounds on the true size and position of the cylindrical feature. These statistical bounds can then be compared to the specified tolerance callouts to determine whether a part is within specification, with a user-defined level of confidence. Seven different sampling strategies were evaluated on a DASH part to determine that four different sampling techniques, including the bird cage sampling strategy defined in ISO 12180, can be utilized with no statistically significant difference in accuracy. Special considerations for each method are discussed. Finally, analysis shows that using the DASH process with automatic inspection is economically advantageous for low volume production runs.

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Automated post machining process planning for a new hybrid manufacturing method of additive manufacturing and rapid machining

Cited by 18 publications

References 14 publications

Automatic feature-based inspection and qualification for additively manufactured parts with critical tolerances

Automatic feature-based inspection and qualification for additively manufactured parts with critical tolerances

Hybrid manufacturing process planning with predictive approach: a comprehensive literature review

Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances

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