Cylindricity Error Measuring and Evaluating for Engine Cylinder Bore in Manufacturing Procedure

Chen, Qiang; Tao, Xueheng; Lu, Jinshi; Xue-jun, Wang

doi:10.1155/2016/4212905

Cited by 6 publications

(5 citation statements)

References 11 publications

(9 reference statements)

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“…This work selected find noms because the nominal values had not been known yet. The least-squares method (Sui and Zhang, 2012; Chen et al , 2016; Liu et al , 2020) was applied to calculate the errors of circularity and cylindricity because of its mature theory, specific mathematical formula and easy use. Besides, this method is the most common technique to determine circularity and cylindricity, and it is also the default mode in PC-DMIS.…”

Section: Experimental Approachmentioning

confidence: 99%

Dimensional accuracy and surface finish of 3D printed polyurethane (PU) dog-bone samples optimally manufactured by fused deposition modelling (FDM)

Nugroho

Dong

Pramanik

2022

RPJ

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Purpose This paper aims to investigate the dimensional accuracy consisting of thickness, grip section width, full length, circularity, cylindricity and surface finish of printed polyurethane dog-bone samples based on American Society for Testing and Materials (ASTM) D638 type V standard, which were optimally printed by fused deposition modelling (FDM). Design/methodology/approach The experimental approach focuses on determining main effects of printing parameters, including nozzle temperature, infill percentage, print speed and layer height on dimensional error and surface finish of the printed samples, followed by the confirmation tests to warrant the reproducibility of experimental results. Findings This study shows that layer height has the most significant impact on dimensional accuracy and surface finish of printed samples compared to other printing parameters, whereas infill density has no significant effect on all sample dimensions. Originality/value This paper presents a comprehensive study relating to various dimensional accuracies in terms of full length, grip section width, thickness, circularity, cylindricity and surface finish of dog-bone samples printed by FDM to improve the printability and processibility via additive manufacturing.

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Section: Experimental Approachmentioning

confidence: 99%

Dimensional accuracy and surface finish of 3D printed polyurethane (PU) dog-bone samples optimally manufactured by fused deposition modelling (FDM)

Nugroho

Dong

Pramanik

2022

RPJ

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“…In this case, the sub-indices Δ and κ represent an increment in the y-axis. By computing Equations (15)(16)(17)(18), four parents (P1,t, P2,t, P3,t, P4,t) are determined for each parameter. The sub-index t indicates the generation number.…”

Section: Micro-scale Cylindrical Surface Modeling Via Genetic Algorithmmentioning

confidence: 99%

“…For instance, the spherical surface modeling has been implemented in geomatics to determine rock surface sphericity [6,7], in optics to estimate lens sphericity [8,9], in object machining to determine surface sphericity [10,11], in pharmaceutics to determine proppants sphericity [12,13], in object prototyping to determine assemble sphericity [14,15], and so on. Moreover, the cylindrical surface modeling has been implemented in surface machining to inspect cylindrical surface [16,17], in surface milling to estimate milling cylindricity [18], and so on. Based on these statements, surface models have been constructed via surface data and mathematical equations for representing micro-scale spherical and cylindrical surfaces [19,20].…”

Section: Introductionmentioning

confidence: 99%

Micro-Scale Spherical and Cylindrical Surface Modeling via Metaheuristic Algorithms and Micro Laser Line Projection

Rodríguez

2022

Algorithms

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With the increasing micro-scale manufacturing industry, the micro-scale spherical and cylindrical surface modeling has become an important factor in the manufacturing process. Thus, the micro-scale manufacturing processes require efficient micro-scale spherical and cylindrical models to achieve accurate assembly. Therefore, it is necessary to implement models to represent micro-scale spherical and cylindrical surfaces. This study addresses metaheuristic algorithms based on micro laser line projection to perform micro-scale spherical and cylindrical surface modeling. In this technique, the micro-scale surface is recovered by an optical microscope system, which computes the surface coordinates via micro laser line projection. From the surface coordinates, a genetic algorithm determines the parameters of the mathematical models to represent the spherical and cylindrical surfaces. The genetic algorithm performs exploration and exploitation in the search space to optimize the models’ mathematical parameters. The search space is constructed via surface data to provide the optimal parameters, which determine the spherical and cylindrical surface models. The proposed technique improves the fitting accuracy of the micro-scale spherical and cylindrical surface modeling performed via optical microscope systems. This contribution is elucidated by a discussion about the model fitting between the genetic algorithms based on micro laser line projection and the optical microscope systems.

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“…Cylindricity describes how the hole surface deviates from a perfect cylinder with respect to geometrical tolerance in 3 Dimension (https://www.taylorhobson.com.de/media/ametektaylorhobson/files/ learning-zone/training-material/cylindricity). Some of the direct methods of cylindricity measurements involve the Radial methods (Adamczak et al 2011) and Error Separation Techniques (EST) (Chen et al 2016). Indirect measurement systems include vibration, force, current, acoustic emission, ultrasonics, etc.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Modeling of Cylindricity Error Using Vibration Signals in Drilling

Mary¹,

Dinakaran

Balaji

et al. 2021

Handbook of Smart Materials, Technologies, and Devices

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Cylindricity is a key factor that affects the assembly and dynamic performance characteristics of mechanical components. Real-time monitoring of cylindricity error during machining reduces the wastages and ensures the quality of the drilled holes. The possible causes of cylindricity error are the run out, mechanical looseness, misalignment, etc. A novel vibration-based monitoring method to predict the cylindricity error during drilling process is developed and presented in this chapter. An adaptive neuro fuzzy system models the cylindricity error with the peak amplitude of vibration at 1xRPM, process parameters, speed, and feed as inputs. The experimental study showed that the ANFIS model is capable of predicting the cylindricity error with 92.4% of accuracy.

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Cylindricity Error Measuring and Evaluating for Engine Cylinder Bore in Manufacturing Procedure

Cited by 6 publications

References 11 publications

Dimensional accuracy and surface finish of 3D printed polyurethane (PU) dog-bone samples optimally manufactured by fused deposition modelling (FDM)

Dimensional accuracy and surface finish of 3D printed polyurethane (PU) dog-bone samples optimally manufactured by fused deposition modelling (FDM)

Micro-Scale Spherical and Cylindrical Surface Modeling via Metaheuristic Algorithms and Micro Laser Line Projection

Monitoring and Modeling of Cylindricity Error Using Vibration Signals in Drilling

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