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One major problem preventing further application and benefits from additive manufacturing (AM) nowadays is that AM build parts always end up with poor geometrical quality. To help improving geometrical quality for AM, this study aims to propose geometrical deviation identification and prediction method for AM, which could be used for identifying the factors, forms and values of geometrical deviation of AM parts.

This paper applied the skin model-based modal decomposition approach to describe the geometrical deviations of AM and decompose them into different defect modes. On that basis, the approach to propose and extend defect modes was developed. Identification and prediction of the geometrical deviations were then carried out with this method. Finally, a case study with cylinders manufactured by fused deposition modeling was introduced. Two coordinate measuring machine (CMM) machines with different measure methods were used to verify the effectiveness of the methods and modes proposed.

The case study results with two different CMM machines are very close, which shows that the method and modes proposed by this paper are very effective. Also, the results indicate that the main geometrical defects are caused by the shrinkage and machine inaccuracy-induced errors which have not been studied enough.

This work could be used for identifying and predicting the forms and values of AM geometrical deviation, which could help realize the improvement of AM part geometrical quality in design phase more purposefully.

The transfer function (TF) method is a reliable tool for the detection of the transformer winding deformation and displacement. One of the most important problems is the discrimination between these mechanical defects using a measured TF. The purpose of this paper is to suggest a new method based on the TF estimation, to detect the type of the mechanical defects in high voltage inhomogeneous winding of a power transformer, i.e. the winding is not homogeneous and has interleaved and inverted disks.

The methodology of this paper is based on the estimation of the TF and in normal and defected cases can be properly achieved using vector fitting method. To study the mechanical defects, the detailed model of the transformer is in the frequency range of kHz<f.

In this paper, comparison of Nyquist diagrams of the estimated TF curves result in a new discrimination method between mechanical defects and localization of the deformed section in the transformer winding. The interpretation of the TF changes is based on comparison of the Nyquist diagrams in a selected frequency range.

This paper suggests new discrimination method between mechanical defects and localization of the deformed section in the transformer winding which is based on the TF estimation.

The purpose of this paper is to develop a numerical approach inspired by Geometrical Product Specifications (GPS) standards for the assessment of geometrical defects appearing during Additive Manufacturing (AM) by Laser Beam Melting (LBM).

The study is based on finite element (FE) simulations of thermal distortions, then an assessment of flatness defects (warping induced by the high-residual stresses appearing during the manufacturing) from the deformed surfaces provided by simulation, and finally the correction of the calculated flatness defects from preliminary comparison between simulated and experimental data.

For an elementary geometrical feature (a wall), it was possible to identify the variation in the flatness defect as a function of the dimensions. For a complex geometry exhibiting a significant flatness defect, it was possible to improve the geometric quality using the numerical tool.

To the best of the author’s knowledge, this work is the first attempt using a numerical approach inspired by GPS standards to identify variations in thermal distortions caused by LBM, which is an initial step toward optimization. This paper is mainly focused on flatness defect assessment, even though the approach is potentially applicable for all types of geometrical defects (shape, orientation or position defects).

The study opens prospects for the optimization of complex parts elaborated using LBM, based on the minimization of the geometric defects caused by thermal distortions.

The prospects in terms of shape optimization will extend the potential to benefit from the new possibilities offered by LBM additive manufacturing.

Unlike the usual approach, the proposed methodology does not require any artifacts or comparisons with the computer-aided-design (CAD) model for geometrical distortion assessment. The present approach opens up the possibility of performing metrology from FE simulation results, which is particularly promising in the AM field.

Remanufacturing of worn blades with various defects normally requires processes such as scanning, regenerating a geometrical reference model, additive manufacturing (AM) through laser cladding, adaptive machining and polishing and quality inspection. Unlike the manufacturing process of a new part, the most difficult problem for remanufacturing such a complex surface part is that the reference model adaptive to the worn part is no longer available or useful. The worn parts may suffer from geometrical deformation, distortion and other defects because of the effects of harsh operating conditions, thereby making their original computer aided design (CAD) models inadequate for the repair process. This paper aims to regenerate the geometric models for the worn parts, which is a key issue for implementing AM to build up the parts and adaptive machining to reform the parts. Unlike straight blades with similar cross sections, the tip geometry of the worn tip of a twist blade needs to be regenerated by a different method.

This paper proposes a surface extension algorithm for the reconstruction of a twist blade tip through the extremum parameterization of a B-spline basis function. Based on the cross sections of the scanned worn blade model, the given control points and knot vectors are firstly reconstructed into a B-spline curve D. After the extremum of each control point is calculated by extremum parameterization of a B-spline basis function, the unknown control points are calculated by substituting the extremum into the curve D. Once all control points are determined, the B-spline surface of the worn blade tip can be regenerated. Finally, the extension algorithm is implemented and validated with several examples.

The proposed algorithm was implemented and verified through the exampled blades. Through the extension algorithm, the tip geometry of the worn tip of a twist blade can be regenerated. This method solved a key problem for the repair of a twist blade tip. It provides an appropriate reference model for repairing worn blade tips through AM to build up the blade tip and adaptive machining/polishing processes to reform the blade geometry.

The extension errors for different repair models are compared and analyzed. The authors found that there are several factors affecting the accuracy of the regenerated model. When the cross-section interval and the extension length are set properly, the restoration accuracy for the blade tip can be improved, which is acceptable for the repairing.

The lack of a reference geometric model for worn blades is a significant problem when implementing blade repair through AM and adaptive machining processes. Because the geometric reference model is unavailable for the repair process, reconstruction of the geometry of a worn blade tip is the first crucial step. The authors proposed a surface extension algorithm for the reconstruction of a twist blade tip. Through the implementation of the proposed algorithm, the blade tip model can be regenerated.

Remanufacturing of worn blades with various defects is highly demeaned for the aerospace enterprises considering sustainable development. Unlike straight blades, repair of twist blades encountered a very difficult problem because the geometric reference model is unavailable for the repair processes. This paper proposed a different method to generate the reference model for the repair of a twist blade tip. With this model, repair of twist blades can be implemented through AM to build up the blade tip and adaptive machining to subtract the extra material.

The authors proposed a surface extension algorithm to reconstruct the geometric model for repair of twist blades.

The purpose of this paper is to present an experimental approach to measure and quantify the three‐dimensional geometrical manufacturing errors on a mass production of parts.

A methodology is developed to model and analyse the combined effect of these errors on a machined feature. Deviation of a machined feature due to the combined errors is expressed in terms of the small displacement torsor (SDT) parameters. Given a tolerance on the machined feature, constraints are specified for that feature to establish a relationship between the tolerance zone of the feature and the torsor parameters. These constraints provide boundaries within which the machined feature must lie. This is used for tolerance analysis of the machined feature. An experimental approach is proposed to measure and quantify the three‐dimensional manufacturing variations as torsors. The results are used to verify the analytical model.

Results show that it is possible to quantify manufacturing dispersions. The paper proposes a measuring method which can be done during the production. In the context of process planning, these experimental data allow us to perform realistic geometrical simulation of manufacturing. The results of this method are torsor components dispersions. Analysis and synthesis of the geometrical simulation of manufacturing are viable with reliable numerical data in order to predict the defects.

To perform realistic geometrical simulation of manufacturing, an experimental approach to measure and quantify the three‐dimensional geometrical manufacturing errors is proposed which is based on the SDT concept.

The purpose of this paper is to contribute to the solution of the buckling and resonance stability problems in inelastic beams and wooden plane trusses, taking into account geometric and material defects.

Two sources of non-linearity are analyzed, namely the geometrical non-linearity due to geometrical imperfections and material non-linearity due to material defects. The load-bearing capacity is obtained by the rheological-dynamical analogy (RDA). The RDA inelastic theory is used in conjunction with the damage mechanics to analyze the softening behavior with the scalar damage variable for stiffness reduction. Based on the assumed damages in the wooden truss, the corresponding external masses are calculated in order to obtain the corresponding fundamental frequencies, which are compared with the measured ones.

RDA theory uses rheology and dynamics to determine the structures' response, those results in the post-buckling branch can then be compared by fracture mechanics. The RDA method uses the measured P and S wave velocities, as well as fundamental frequencies to find material properties at the limit point. The verification examples confirmed that the RDA theory is more suitable than other non-linear theories, as those proved to be overly complex in terms of their application to the real structures with geometrical and material defects.

The paper presents a novel method of solving the buckling and resonance stability problems in inelastic beams and wooden plane trusses with initial defects. The method is efficient as it provides explanations highlighting that an inelastic beam made of ductile material can break in any stage from brittle to extremely ductile, depending on the value of initial imperfections. The characterization of the internal friction and structural damping via the damping ratio is original and effective.

Additive manufacturing (AM) is revolutionizing the manufacturing industry due to several advantages and capabilities, including use of rapid prototyping, fabrication of complex geometries, reduction of product development cycles and minimization of material waste. As metal AM becomes increasingly popular for aerospace and defense original equipment manufacturers (OEMs), a major barrier that remains is rapid qualification of components. Several potential defects (such as porosity, residual stress and microstructural inhomogeneity) occur during layer-by-layer processing. Current methods to qualify AM parts heavily rely on experimental testing, which is economically inefficient and technically insufficient to comprehensively evaluate components. Approaches for high fidelity qualification of AM parts are necessary.

This review summarizes the existing powder-based fusion computational models and their feasibility in AM processes through discrete aspects, including process and microstructure modeling.

Current progresses and challenges in high fidelity modeling of AM processes are presented.

Potential opportunities are discussed toward high-level assurance of AM component quality through a comprehensive computational tool.

Design methods for medical rapid prototyping (RP) of personalized cranioplasty implants are presented in this paper. These methods are applicable to model cranioplasty implants for all types of the skull defects including beyond‐midline and multiple defects. The methods are based on two types of anatomical data, solid bone models (STereoLithography files – STL) and bone slice contours (Initial Graphics Exchange Specification – IGES and StrataSys Layer files – SSL). The bone solids and contours are constructed based on computed tomography scanning data, and these data are generated in medical image processing and STL slicing packages.

Aims to investigate medical rapid prototyping (medical RP) technology applications and methods based on reverse engineering (RE) and medical imaging data.

Medical image processing and RE are applied to construct three‐dimensional models of anatomical structures, from which custom‐made (personalized) medical applications are developed.

The investigated methods were successfully used for design and manufacturing of biomodels, surgical aid tools, implants, medical devices and surgical training models. More than 40 medical RP applications were implemented in Europe and Asia since 1999.

Medical RP is a multi‐discipline area. It involves in many human resources and requires high skills and know‐how in both engineering and medicine. In addition, medical RP applications are expensive, especially for low‐income countries. These practically limit its benefits and applications in hospitals.

In order to transfer medical RP into hospitals successfully, a good link and close collaboration between medical and engineering sites should be established. Moreover, new medical applications should be developed in the way that does not change the traditional approaches that medical doctors (MD) were trained, but provides solutions to improve the diagnosis and treatment quality.

The presented state‐of‐the‐art medical RP is applied for diagnosis and treatment in the following medical areas: cranio‐maxillofacial and dental surgery, neurosurgery, orthopedics, orthosis and tissue engineering. The paper is useful for MD (radiologists and surgeons), biomedical and RP/CAD/CAM engineers.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.