scholarly journals Determination of optimal build orientation for additive manufacturing using Muirhead mean and prioritised average operators

2019 ◽  
Vol 30 (8) ◽  
pp. 3015-3034 ◽  
Author(s):  
Yuchu Qin ◽  
Qunfen Qi ◽  
Paul J. Scott ◽  
Xiangqian Jiang
Keyword(s):  
Additive Manufacturing ◽  
Fuzzy Decision ◽  
Decision Matrix ◽  
Build Orientation ◽  
Part Quality ◽  
Determination Process ◽  
Build Time ◽  
Finite Set ◽  
Multi Attribute Decision Making

Abstract Build orientation determination is one of the essential process planning tasks in additive manufacturing since it has crucial effects on the part quality, post-processing, build time and cost, etc. This paper introduces a method based on fuzzy multi-attribute decision making to determine the optimal build orientation from a finite set of alternatives. The determination process includes two major steps. In the first step, attributes that are considered in the determination and heterogeneous relationships of which are firstly identified. A fuzzy decision matrix is then constructed and normalised based on the values of the identified attributes, which are quantified by a set of fuzzy numbers. In the second step, two fuzzy number aggregation operators are developed to aggregate the fuzzy information in the normalised matrix. By comparing the aggregation results, a ranking of all alternative build orientations can then be generated. Two determination examples are used to demonstrate the working process of the proposed method. Qualitative and quantitative comparisons between the proposed method and other methods are carried out to demonstrate its feasibility, effectiveness, and advantages.

CAD-Integrated Cost Estimation and Build Orientation Optimization to Support Design for Metal Additive Manufacturing

2017 ◽  
Author(s):  
Michael Barclift ◽  
Andrew Armstrong ◽  
Timothy W. Simpson ◽  
Sanjay B. Joshi
Keyword(s):  
Additive Manufacturing ◽  
Cost Estimation ◽  
Application Programming Interface ◽  
External Support ◽  
Support Design ◽  
Build Orientation ◽  
3D Cad ◽  
Build Time ◽  
Cad Models ◽  
Integrated Cost

Cost estimation techniques for Additive Manufacturing (AM) have limited synchronization with the metadata of 3D CAD models. This paper proposes a method for estimating AM build costs through a commercial 3D solid modeling program. Using an application programming interface (API), part volume and surface data is queried from the CAD model and used to generate internal and external support structures as solid-body features. The queried data along with manipulation of the part’s build orientation allows users to estimate build time, feedstock requirements, and optimize parts for AM production while they are being designed in a CAD program. A case study is presented with a macro programmed using the SolidWorks API with costing for a metal 3D-printed automotive component. Results reveal that an imprecise support angle can under-predict support volume by 34% and build time by 20%. Orientation and insufficient build volume packing can increase powder depreciation costs by nearly twice the material costs.

scholarly journals On the Impact of Additive Manufacturing Processes Complexity on Modelling

2021 ◽  
Vol 11 (16) ◽  
pp. 7743
Author(s):  
Panagiotis Stavropoulos ◽  
Panagis Foteinopoulos ◽  
Alexios Papapacharalampopoulos
Keyword(s):  
Additive Manufacturing ◽  
Performance Indicators ◽  
Part Quality ◽  
Build Time ◽  
Modelling Techniques ◽  
And Performance ◽  
The Many ◽  
Process Complexity ◽  
The Impact ◽  
Am Processes

The interest in additive manufacturing (AM) processes is constantly increasing due to the many advantages they offer. To this end, a variety of modelling techniques for the plethora of the AM mechanisms has been proposed. However, the process modelling complexity, a term that can be used in order to define the level of detail of the simulations, has not been clearly addressed so far. In particular, one important aspect that is common in all the AM processes is the movement of the head, which directly affects part quality and build time. The knowledge of the entire progression of the phenomenon is a key aspect for the optimization of the path as well as the speed evolution in time of the head. In this study, a metamodeling framework for AM is presented, aiming to increase the practicality of simulations that investigate the effect of the movement of the head on part quality. The existing AM process groups have been classified based on three parameters/axes: temperature of the process, complexity, and part size, where the complexity has been modelled using a dedicated heuristic metric, based on entropy. To achieve this, a discretized version of the processes implicated variables has been developed, introducing three types of variable: process parameters, key modeling variables and performance indicators. This can lead to an enhanced roadmap for the significance of the variables and the interpretation and use of the various models. The utilized spectrum of AM processes is discussed with respect to the modelling types, namely theoretical/computational and experimental/empirical.

Part Build Orientation Optimization and Neural Network-Based Geometry Compensation for Additive Manufacturing Process

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Sushmit Chowdhury ◽  
Kunal Mhapsekar ◽  
Sam Anand
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Surface Finish ◽  
Quality Measurement ◽  
Dimensional Accuracy ◽  
Build Orientation ◽  
Part Quality ◽  
Heating And Cooling ◽  
Orientation Optimization

Significant advancements in the field of additive manufacturing (AM) have increased the popularity of AM in mainstream industries. The dimensional accuracy and surface finish of parts manufactured using AM depend on the AM process and the accompanying process parameters. Part build orientation is one of the most critical process parameters, since it has a direct impact on the part quality measurement metrics such as cusp error, manufacturability concerns for geometric features such as thin regions and small fusible openings, and support structure parameters. In conjunction with the build orientation, the cyclic heating and cooling of the material involved in the AM processes lead to nonuniform deformations throughout the part. These factors cumulatively affect the design conformity, surface finish, and the postprocessing requirements of the manufactured parts. In this paper, a two-step part build orientation optimization and thermal compensation methodology is presented to minimize the geometric inaccuracies resulting in the part during the AM process. In the first step, a weighted optimization model is used to determine the optimal build orientation for a part with respect to the aforementioned part quality and manufacturability metrics. In the second step, a novel artificial neural network (ANN)-based geometric compensation methodology is used on the part in its optimal orientation to make appropriate geometric modifications to counteract the thermal effects resulting from the AM process. The effectiveness of this compensation is assessed on an example part using a new point cloud to part conformity metric and shows significant improvements in the manufactured part's geometric accuracy.

scholarly journals Search for the Optimal Build Direction in Additive Manufacturing Technologies: A Review

2020 ◽  
Vol 4 (3) ◽  
pp. 71 ◽  
Author(s):  
Luca Di Angelo ◽  
Paolo Di Stefano ◽  
Emanuele Guardiani
Keyword(s):  
Additive Manufacturing ◽  
Optimization Techniques ◽  
Manufacturing Cost ◽  
Layer By Layer ◽  
Part Quality ◽  
Advantages And Disadvantages ◽  
Build Time ◽  
Set Up ◽  
Manufacturing Technologies ◽  
The Cost

By additive manufacturing technologies, an object is produced deposing material layer by layer. The piece grows along the build direction, which is one of the main manufacturing parameters of Additive Manufacturing (AM) technologies to be set-up. This process parameter affects the cost, quality, and other important properties of the manufactured object. In this paper, the Objective Functions (OFs), presented in the literature for the search of the optimal build direction, are considered and reviewed. The following OFs are discussed: part quality, surface quality, support structure, build time, manufacturing cost, and mechanical properties. All of them are distinguished factors that are affected by build direction. In the first part of the paper, a collection of the most significant published methods for the estimation of the factors that most influence the build direction is presented. In the second part, a summary of the optimization techniques adopted from the reviewed papers is presented. Finally, the advantages and disadvantages are briefly discussed and some possible new fields of exploration are proposed.

Orientation Optimization in Additive Manufacturing: Evaluation of Recent Trends

2021 ◽  
Author(s):  
Jannatul Bushra ◽  
Hannah D. Budinoff
Keyword(s):  
Additive Manufacturing ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Practical Implementation ◽  
Objective Functions ◽  
Build Orientation ◽  
Computational Optimization ◽  
Build Time ◽  
Orientation Optimization

Abstract Build orientation in additive manufacturing influences the mechanical properties, surface quality, build time, and cost of the product. Rather than relying on trial-and-error or prior experience, the choice of build orientation can be formulated as an optimization problem. Consequently, orientation optimization has been a popular research topic for several decades, with new optimization methods being proposed each year. However, despite the rapid pace of research in additive manufacturing, there has not been a critical comparison of different orientation optimization methods. In this study, we present a critical review of 50 articles published since 2015 that proposes a method for orientation optimization for additive manufacturing. We classify included papers by optimization methods used, AM process modeled, and objective functions considered. While the pace of research in recent years has been rapid, most approaches we identified utilized similar objective functions and computational optimization techniques to research from the early 2000s. The most common optimization method in the included research was exhaustive search. Most methods focused on broad applicability to all additive manufacturing processes, rather than a specific process, but a few works focused on powder bed fusion and material extrusion. We also identified several areas for future work including integration with other design and process planning tasks such as topology optimization, more focus on practical implementation with users, testing of computational efficiency, and experimental validation of utilized objective functions.

Feature based building orientation optimization for additive manufacturing

2016 ◽  
Vol 22 (2) ◽  
pp. 358-376 ◽  
Author(s):  
Yicha Zhang ◽  
Alain Bernard ◽  
Ravi Kumar Gupta ◽  
Ramy Harik
Keyword(s):  
Decision Making ◽  
Additive Manufacturing ◽  
High Performance ◽  
Research Work ◽  
Geometric Features ◽  
Content Type ◽  
Build Orientation ◽  
Multi Attribute Decision Making ◽  
Production Knowledge ◽  
Short Time

Purpose The purpose of this paper is to present research work based on the authors’ conceptual framework reported in the VRAP Conference 2013. It is related with an efficient method to obtain an optimal part build orientation for additive manufacturing (AM) by using AM features with associated AM production knowledge and multi-attribute decision-making (MADM). The paper also emphasizes the importance of AM feature and the implied AM knowledge in AM process planning. Design/methodology/approach To solve the orientation problem in AM, two sub-tasks, the generation of a set of alternative orientations and the identification of an optimal one within the generated list, should be accomplished. In this paper, AM feature is defined and associated with AM production knowledge to be used for generating a set of alternative orientations. Key attributes for the decision-making of the orientation problem are then identified and used to represent those generated orientations. Finally, an integrated MADM model is adopted to find out the optimal orientation among the generated alternative orientations. Findings The proposed method to find out an optimal part build orientation for those parts with simple or medium complex geometric shapes is reasonable and efficient. It also has the potential to deal with more complex parts with cellular or porous structures in a short time by using high-performance computers. Research limitations/implications The proposed method is a proof-of-concept. There is a need to investigate AM feature types and the association with related AM production knowledge further so as to suite the context of orientating parts with more complex geometric features. There are also research opportunities for developing more advanced algorithms to recognize AM features and generate alternative orientations and refine alternative orientations. Originality/value AM feature is defined and introduced to the orientation problem in AM for generating the alternative orientations. It is also used as one of the key attributes for decision-making so as to help express production requirements on specific geometric features of a desired part.

Build Direction for 3D Heterogeneous Object in Additive Manufacturing

2013 ◽  
Author(s):  
AKM B. Khoda
Keyword(s):  
Additive Manufacturing ◽  
Object A ◽  
Support Materials ◽  
Part Quality ◽  
Material Deposition ◽  
Heterogeneous Object ◽  
Build Time ◽  
Functional Object ◽  
Continuous Material ◽  
Internal Architecture

Build direction in additive manufacturing is mostly determined considering the time, support materials and surface finish of the fabricated part. However, internal architecture of the part cannot be ignored in porous functional object design. Especially, heterogeneous object with internal features can be decomposed into 2D heterogeneous slices with island in which each island represent associated feature’s properties different from the base. Continuous material deposition in such multi-feature/multi-contour slices can be intervened by frequent directional changes intersecting those islands and can affect the build time and part quality. This research aims to minimize such intervention in the decomposed slices of heterogeneous object. A computational algorithm is proposed to quantify the build direction considering the location and alignment of the internal feature which can maximize the homogeneous slices generated from a heterogeneous object. The proposed methodology is illustrated by an example in this work. The algorithm can provide better control over the internal architecture design by selecting the best build direction for the heterogeneous object.

scholarly journals Adaptive Slicing in Additive Manufacturing Process Using a Modified Boundary Octree Data Structure

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Nandkumar Siraskar ◽  
Ratnadeep Paul ◽  
Sam Anand
Keyword(s):  
Data Structure ◽  
Additive Manufacturing ◽  
Layer By Layer ◽  
Adaptive Slicing ◽  
Stl File ◽  
Part Quality ◽  
Part Geometry ◽  
Build Time ◽  
Part Surface ◽  
Am Processes

In additive manufacturing (AM) processes, the layer-by-layer fabrication leads to a staircase error resulting in dimensional inaccuracies in the part surface. Using thinner slices reduces the staircase error and improves part accuracy but also increases the number of layers and the build time for manufacturing the part. Another approach called adaptive slicing uses slices of varying thicknesses based on the part geometry to build the part. A new algorithm to compute adaptive slice thicknesses using octree data structure is presented in this study. This method, termed as modified boundary octree data structure (MBODS) algorithm, is used to convert the stereolithography (STL) file of an object to an octree data structure based on the part's geometry, the machine parameters, and a user defined tolerance value. A subsequent algorithm computes the variable slice thicknesses using the MBODS representation of the part and virtually manufactures the part using these calculated slice thicknesses. Points sampled from the virtually manufactured part are inspected to evaluate the volumetric, profile, and cylindricity part errors. The MBODS based slicing algorithm is validated by comparing it with the uniform slicing approach using various slice thicknesses for different parts. The developed MBODS algorithm is observed to be more effective in improving the part quality while using lesser number of slices.

Self-Determination Through Autonomy or Independence? – On the Current and Future Position of New Caledonia

ICL Journal ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 67-105
Author(s):  
Markku Suksi
Keyword(s):  
Human Rights ◽  
New Caledonia ◽  
Legal Order ◽  
The Self ◽  
Self Determination ◽  
Normative Framework ◽  
European Court ◽  
Determination Process ◽  
The Right

Abstract New Caledonia is a colonial territory of France. Since the adoption of the Nouméa Accord in 1998, a period of transition towards the exercise of self-determination has been going on. New Caledonia is currently a strong autonomy, well entrenched in the legal order of France from 1999 on. The legislative powers have been distributed between the Congress of New Caledonia and the Parliament of France on the basis of a double enumeration of legislative powers, an arrangement that has given New Caledonia control over many material fields of self-determination. At the same time as this autonomy has been well embedded in the constitutional fabric of France. The Nouméa Accord was constitutionalized in the provisions of the Constitution of France and also in an Institutional Act. This normative framework created a multi-layered electorate that has presented several challenges to the autonomy arrangement and the procedure of self-determination, but the European Court of Human Rights and the UN Human Rights Committee have resolved the issues regarding the right to vote in manners that take into account the local circumstances and the fact that the aim of the legislation is to facilitate the self-determination of the colonized people, the indigenous Kanak people. The self-determination process consists potentially of a series of referendums, the first of which was held in 2018 and the second one in 2020. In both referendums, those entitled to vote returned a No-vote to the question of ‘Do you want New Caledonia to attain full sovereignty and become independent?’ A third referendum is to be expected before October 2022, and if that one also results in a no to independence, a further process of negotiations starts, with the potential of a fourth referendum that will decide the mode of self-determination New Caledonia will opt for, independence or autonomy.

Sign in / Sign up

Export Citation Format

Share Document