Computer-aided Reverse Engineering Research Articles

Optimisation of the machining time required by insole orthotic shoes for patients with clubfoot using the Taguchi and response surface methodology approach

In this study, the application of the computer-aided reverse engineering system (CARE) to the novel design and manufacture of a comfortable insole for a clubfoot patient is presented. The Taguchi method (TM) and response surface methodology (RMS) were used to predict the machining time of the orthotic boot insole during both computer-aided manufacturing (CAM) simulation and computer numerical control (CNC) machining. Taguchi’s experimental design, presented as a matrix orthogonal array L2736, was acquired for controlling parameters, namely tool path strategy (A), spindle speed (B), step-down (C), step-over of the cutter (D), cutter diameter (E), and dimensional tolerance (F) of the insole size. In this method, the model generated by the RMS method evaluates the six parameters influencing the machining time. The objective of this study is to develop a regression model that demonstrates the relationship between the cutting parameters and insole machining time. The optimal parameters are A1B1C3D2E1F2, where A1 denotes raster finishing, B1 denotes a spindle speed of 10,000 rpm, C3 denotes a step-down of 850 mm, D2 denotes a step-over of 0.25 mm, E1 denotes a cutter diameter of 20–35 mm, and F2 deontes a tolerance of 0.75 mm. The experimental and calculated machining time (tm) results were 236 and 125.4 min, respectively. However, the real machining results were 334 and 152.25 min with error values of 46.86% and 54.42%, respectively. Meanwhile, with the tm RMS method, the simulated and calculated machining time results were 189.22 and 236.35 min, whereas the real tm values were 236.52 and 334.86 min with error values of 19.94% and 29.37%, respectively. This research obtains improvements of 19.82% (simulation time) and 29.19% (real-time).

Application of Computer-Aided Reverse Engineering System in the Design of Orthotic Boots for Clubfoot Patients

Clubfoot is an abnormal foot as a congenital disability in which one or both feet appear rotated inward and downward. In some cases, the foot and leg sizes may be smaller compared to each other. Accordingly, there is a need for customized shoes designed for clubfoot patients who has difficulty in wearing regular shoes to carry out their daily activities. This study examines using computer-aided reverse engineering system technology to design and manufacture customized boots with specific sizes and shapes. Reverse engineering with a handy scan 3D scanning tool with a tolerance of 0.001 mm was implemented to obtain 3D mesh data of the patient’s clubfoot (male with 65 years). The Curve Base Surface Modeling method provided 3D-CAD drawings of the insole and shoe, the last models, precisely and following the size and shape of the patient’s foot. This CAD data could be appropriately transferred to CNC machines and PowerMill CAM software to obtain patterns of insole and shoe-last from EVA foam rubber and wood. Both ways were well fitted with leather by a shoemaker into a pair of customized clubfoot boots. The field boot-wearing test used feedback from the clubfoot patient wear-testers to assess the functionality and acceptability of the boot products. In this way, the club foot patient can able to perceive wearing comfortably and perfectly. In the field boot-wearing test, the patient could walk at a speed of 83.1% -91.7% faster (2 - 5 minutes/foot) than that when the patient wears the old boot design model. Significantly, the present approach may add knowledge theoretically and practically to use CARE system-based technology in treating clubfoot patients with the need for custom shoes.

Reverse engineering from 3D mesh to ceramic product in the form of miranda kerr tea for one teapot in PT doulton Indonesia

The design and manufacturing strategy using reverse engineering (RE) for Miranda Kerr Tea for One Teapot are presented in this paper. A computer-aided reverse engineering system (CARE System) was a...

Computer-aided reverse engineering system in the design and production of orthotic insole shoes for patients with diabetes

Design and manufacturing strategies for custom orthotic insole shoes for patients with diabetes are presented in this paper. The computer-aided reverse engineering system (CARESystem) was applied f...

Impression technique for monitoring and virtual treatment planning in nasoalveolar moulding

We describe our experience with various silicone materials for making one-step and two-step impressions of the cleft-lip-palate-nose complex during nasoalveolar moulding. Our technique is superior to common alginate-based impression techniques, as it provides precise reproduction of the complex anatomy of the cleft, and is compatible with the latest available methods of planning treatment with nasoalveolar moulding, such as computer-aided reverse engineering and rapid prototyping.

Correction of maxillary deformity in infants with bilateral cleft lip and palate using computer-assisted design

The aim of this study was to introduce a method of presurgical maxillary molding using computer-aided design and rapid prototyping in infants with bilateral cleft lip and palate. Seven infants (4 male and 3 female with overall mean age of 7 days) with bilateral cleft lip and palate were subjected to nasoalveolar molding (NAM) technique before the cleft lip repair. The upper denture casts were scanned by a 3-dimensional laser scanner. The digital geometric data were exported to print the solid model with rapid prototyping system. The NAM appliances were fabricated based on these solid models. The computer-aided design could simplify the NAM procedure and estimate the treatment objective. The appliances could be fabricated based on the rapid prototyping system. In infants with bilateral cleft lip and palate, the presurgical orthopedic treatment design and the appliance fabrication could be simplified with computer-aided reverse engineering and rapid prototyping technique.

A Novel Technique for Presurgical Nasoalveolar Molding Using Computer-Aided Reverse Engineering and Rapid Prototyping

To establish a new method of presurgical nasoalveolar molding (NAM) using computer-aided reverse engineering and rapid prototyping technique in infants with unilateral cleft lip and palate (UCLP). Five infants (2 males and 3 females with mean age of 1.2 w) with complete UCLP were recruited. All patients were subjected to NAM before the cleft lip repair. The upper denture casts were recorded using a three-dimensional laser scanner within 2 weeks after birth in UCLP infants. A digital model was constructed and analyzed to simulate the NAM procedure with reverse engineering software. The digital geometrical data were exported to print the solid model with rapid prototyping system. The whole set of appliances was fabricated based on these solid models. Laser scanning and digital model construction simplified the NAM procedure and estimated the treatment objective. The appliances were fabricated based on the rapid prototyping technique, and for each patient, the complete set of appliances could be obtained at one time. By the end of presurgical NAM treatment, the cleft was narrowed, and the malformation of nasoalveolar segments was aligned normally. We have developed a novel technique of presurgical NAM based on a computer-aided design. The accurate digital denture model of UCLP infants could be obtained with laser scanning. The treatment design and appliance fabrication could be simplified with a computer-aided reverse engineering and rapid prototyping technique.

WITHDRAWN: Presurgical Nasoalveolar Molding With Computer-Aided Reverse-Engineering and Rapid Prototyping Technique in Infants With Unilateral Cleft Lip and Palate

WITHDRAWN: Presurgical Nasoalveolar Molding With Computer-Aided Reverse-Engineering and Rapid Prototyping Technique in Infants With Unilateral Cleft Lip and Palate

Computer-aided reverse engineering using simulated evolution on NURBS

The current study is related to the issue of computer-aided reverse engineering. Although the proposed technique has been suggested and adopted for the image-based planar objects, it is extendable to the objects in three dimensions (3D) with some modifications. The objective of the present study is to provide a robust and automated solution and methodology for the applications of reverse engineering technology in manufacturing and other industries. By extracting nearly exact geometric data of the models, the key points (one may call them ‘corner points’) from the data are detected using an efficient technique. Then curve or surface models are fitted by using non-uniform rational B-splines (NURBS). In curve or surface fitting problems, the selection of appropriate parameters, in order to obtain an optimized shape design, is a well-known problem. For large data, this problem needs to be dealt with by optimization algorithms avoiding possible local optima and at the same time reaching the desired solution in an iterative fashion. Many evolutionary optimization techniques including genetic algorithm and simulated annealing have been applied to the problem. This paper presents an application of an evolutionary heuristic technique known as ‘simulated evolution’ (SimE) to the curve and surface fitting problems using NURBS. NURBS have become the standard for representing curves and surfaces. This paper presents a method for approximating NURBS using digitized data. Instead of using the classical optimization approach to solve the problem, a new method based on SimE is developed. The shape parameters, in the description of NURBS, have been targeted to be optimized in a best possible way. The paper describes the mapping scheme of the problem to SimE followed by the proposed algorithm outlines with the interesting results obtained.

Computer-aided reverse engineering of the human musculoskeletal system

The objective of this study is to extend the applications of reverse engineering technology from manufacturing industries to the biomedical industry. By obtaining nearly exact geometric data of human tissues, such as bones, tendons, and ligaments, in a high-speed and inexpensive manner, potentially groundbreaking research becomes possible for applications in injury rehabilitation, injury prevention and strengthening. Previous applications of reverse engineering technologies in the biomedical community have dealt largely with prosthetic design and plastic surgery. This study expands this research to include muscular and skeletal applications. The primary advantage provided by scanning technologies is an improved quality of data. Secondly, the time investment for the medical researcher is greatly reduced. And finally, the use of a scanning technology will occasionally provide a less expensive alternative to the medical imaging counterparts. The goal of the research is to develop guidelines and methodologies for reverse engineering human structures.

English

Indigenous product development using conventional means involves a relatively long leadtime and cost, especially for replacing worn out and broken parts. This paper presentsmethodologies and technologies for computer-aided reverse engineering, illustrated by a reallifecase study of an aluminium alloy separator body of a hydraulic filter assembly for the specialarmy vehicle. It involved reconstruction of part geometry using 3-D scanning, materialidentification using spectrometry, casting process optimisation using simulation software, andfabrication of prototype and tooling using rapid prototyping systems. It was found that thefabrication of wax patterns directly from reverse-engineered CAD data in a suitable rapidprototyping system (such as thermojet), followed by conventional investment casting, gives areliable and economic route for rapid development of one-off intricate parts for the replacementpurpose.

Towards computer-aided reverse engineering of heavy vehicle parts using laser range imaging techniques

We present an integrated system to automatically generate computer-aided design (CAD) models of existing vehicle parts using laser range imaging techniques. The proposed system integrates data acquisition, model reconstruction, and post processing to generate a set of models from real-world automotive parts. This range image-based, computer-aided reverse engineering (CARE) system has potential for faster model reconstruction over traditional reverse engineering technologies. As part of this system, we also propose a novel crease detection algorithm, which segments the surfaces of reconstructed models along smoothness discontinuities. We present results for both the CARE system and the proposed crease detection algorithm for a set of automotive parts.

Digitizing uncertainty modeling for reverse engineering applications: regression versus neural networks

The coordinate measuring machine is one of the two types of digitizers most popularly used in reverse engineering. A number of factors affect the digitizing uncertainty, such as travel speeds of the probe, pitch values (sampling points), probe angles (part orientations), probe sizes, and feature sizes. A proper selection of these parameters in a digitization or automatic inspection process can improve the digitizing accuracy for a given coordinate-measuring machine. To do so, some empirical models or decision rules are required. This paper applies and compares the nonlinear regression analysis and neural network modeling methods in developing empirical models for estimating the digitizing uncertainty. The models developed in this research can aid error prediction, accuracy improvement, and operation parameter selection in computer-aided reverse engineering and automatic inspection.

Subset selection in predictive modeling of the CMM digitization uncertainty

Abstract A number of factors affect digitizing accuracy, such as the travel speed of the probe, pitch values, probe angles (part orientations), probe sizes, and feature sizes. A proper selection of these parameters in a digitization or automatic inspection process will improve the digitizing accuracy. Factorial design of experiments is used to plan the experiments. Regression analysis is applied to developing the empirical models for prediction of digitizing uncertainty. Four criteria, namely the PRESS statistic, the adjusted R 2 , the C p statistic, and the residual mean square s 2 , are employed to select the best regression model. Hypothesis testing is conducted to check the goodness of each model in construction and to qualify the validation of the model. It is shown that the prediction model has a satisfactory goodness of fit. The method for model selection and validation as well as the best model selected can be used in both computer-aided reverse engineering and automatic inspection for error prediction and accuracy improvement.

Modular software development for digitizing systems data analysis in reverse engineering applications: case of concentric rotational parts

The process of building a computer aided design (CAD) model from an existing part or prototype is necessary for design modifications and for other reverse engineering applications. Output of existing digitizing systems are not often compatible with most CAD data formats, thus limiting the use of these reverse engineering systems. This paper describes a methodology for vectorization of the output of existing digitizing systems. The methodology is implemented in software. It creates a CAD model compatible with the engineering drawing format. Interfaces to an existing CAD system have also been developed. The vectorization of the data allows substantial reduction in the size of the data base. The developed methodology and software can lead to the wider application of these computer aided reverse engineering (CARE) systems in a manufacturing environment. Some sample results of the implemented system are also presented.