Effect of process parameters on parts quality and process efficiency of fused deposition modeling

Galetto, Maurizio; Verna, Elisa; Genta, Gianfranco

doi:10.1016/j.cie.2021.107238

Cited by 34 publications

(17 citation statements)

References 34 publications

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“…In this process, several input variables can affect the quality of the finished product, including continuous variables, such as laser power, scan speed and hatching distance, and discrete variables, e.g., the use of virgin/recycled powder and the layer thickness [29][30][31][32][33]. These input variables can affect a variety of quality characteristics of products, which will be called from now on output variables, including surface roughness, macro-hardness, porosity, tensile strength and dimensional accuracy [34,35]. A first problem is to determine which is the probability of occurrence of defects related to the selected output variables.…”

Section: Problem Statement In a Real Case Applicationmentioning

confidence: 99%

Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production

Verna

Genta

Galetto

et al. 2021

Prod. Eng. Res. Devel.

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The assessment of the performance of inspection strategies is a crucial element in the design phase of product quality inspections of manufacturing companies. The aspects that inspection designers need to consider include: (1) the typology of quality inspection, (2) the inspection variables involved, (3) the potential interaction between variables and (4) the presence of inspection errors. In particular, low-volume inspection design is critical due to the lack of historical data and the inadequacy of traditional statistical approaches. By considering these issues, this paper proposes a novel approach to support inspection designers in the prediction of offline quality inspection performance. The development of a probabilistic model based on the analysis of the possible variable interactions and inspection errors and the definition of some performance measures may successfully help designers in the early design stages of inspection process planning. The approach is supported by a practical application in the Additive Manufacturing field.

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Section: Problem Statement In a Real Case Applicationmentioning

confidence: 99%

Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production

Verna

Genta

Galetto

et al. 2021

Prod. Eng. Res. Devel.

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“…additive manufacturing centers equipment of the AM machines are different, leading to possible differences in terms of resulting quality of the parts (Galetto et al, 2021). The AM machines used in each AM center have different production capacity: the machine of Center I has the largest surface of the plate, followed by that of Center II and Center III, respectively.…”

Section: Distributedmentioning

confidence: 99%

“…Fixtures are produced in three distributed AM centers, referred to as “Center I,” “Center II” and “Center III.” All AM centers use polymeric materials, although the three different machines in use are not disclosed for industrial secrecy reasons. Although these AM centers adopt the same technology, that is fused deposition modeling (FDM), the architecture and equipment of the AM machines are different, leading to possible differences in terms of resulting quality of the parts (Galetto et al , 2021). The AM machines used in each AM center have different production capacity: the machine of Center I has the largest surface of the plate, followed by that of Center II and Center III, respectively.…”

Section: Case Studymentioning

confidence: 99%

A benchmark analysis of the quality of distributed additive manufacturing centers

Verna

Maisano

2022

IJQRM

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PurposeNowadays, companies are increasingly adopting additive manufacturing (AM) technologies due to their flexibility and product customization, combined with non-dramatic increases in per unit cost. Moreover, many companies deploy a plurality of distributed AM centers to enhance flexibility and customer proximity. Although AM centers are characterized by similar equipment and working methods, their production mix and volumes may be variable. The purpose of this paper is to propose a novel methodology to (1) monitor the quality of the production of individual AM centers and (2) perform a benchmarking of different AM centers.Design/methodology/approachThis paper analyzes the quality of the production output of AM centers in terms of compliance with specifications. Quality is assessed through a multivariate statistical analysis of measurement data concerning several geometric quality characteristics. A novel operational methodology is suggested to estimate the fraction nonconforming of each AM center at three different levels: (1) overall production, (2) individual product typologies in the production mix and (3) individual quality characteristics.FindingsThe proposed methodology allows performing a benchmark analysis on the quality performance of distributed AM centers during regular production, without requiring any ad hoc experimental test.Originality/valueThis research assesses the capability of distributed AM centers to meet crucial quality requirements. The results can guide production managers toward improving the quality of the production of AM centers, in order to meet customer expectations and enhance business performance.

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“…[7,8]. In order to solve these problems, some researchers have tried to greatly improve the quality of the printed parts by the FFF process by optimizing these parameters that affect the printing quality and enhancing the connection between the printed filaments and the adhesion between the layers, which can considerably reduce the anisotropy of the printed parts brought by the FFF process [9][10][11][12]. Based on the different types of implementation these methods can be broadly divided into two parts, process parameters and path planning.…”

Section: Introductionmentioning

confidence: 99%

A 3D printing tool-path generation strategy based on the partition of principal stress field for FFF Platform

Zhang¹,

Yao

Ma³

et al. 2022

Preprint

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In order to enhance the strength of 3D printed parts made of polymer materials and reduce the anisotropy caused by the fused filament fabrication process, this paper proposes an inter-layer interleaved composite path planning method based on the directional partition of the principal stress field. This method not only ensures intra-layer reinforcement under specific working conditions but also increases the strength of the printed part by enhancing the adhesion of adjacent layers through staggered filling between layers. The mechanical performance is improved by 17% compared to other conventional filling patterns such as the zigzag filling algorithm. IICP is suitable for path planning of structures with complex shapes and is easily integrated into existing general computer-aided engineering processes.

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Effect of process parameters on parts quality and process efficiency of fused deposition modeling

Cited by 34 publications

References 34 publications

Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production

Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production

A benchmark analysis of the quality of distributed additive manufacturing centers

A 3D printing tool-path generation strategy based on the partition of principal stress field for FFF Platform

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