Computer aided inspection procedures to support smart manufacturing of injection moulded components

This work presents Reverse Engineering and Computer Aided technologies to improve the inspection of injection moulded electro-mechanical parts. Through a strong integration and automation of these methods, tolerance analysis, acquisition tool-path optimization and data management are performed. The core of the procedure concerns the automation of the data measure originally developed through voxel-based segmentation. This paper discusses the overall framework and its integration made according to Smart Manufacturing requirements. The experimental set-up, now in operative conditions at ABB SACE, is composed of a laser scanner installed on a CMM machine able to measure components with lengths in the range of 5÷250 mm, (b) a tool path optimization procedure and (c) a data management both developed as CAD-based applications

Parametric Based Controller for Rapid Prototyping Applications

A methodology aiming at reproducing in Rapid Prototyping applications, exact parametric curves from CAD data is presented. The approach consists of converting the space-based parametric curves from the CAD system into time-base, such that the equations of the curve in terms of time are then fed to a controller directly. Optimization is used to solve the problem, which has both Rapid Prototyping process and scanning constraints. With information such as the equation of the curve, its first and second derivatives with respect to time, a real-time trajectory controller can be designed. The trajectory displays an increase in accuracy over traditional approaches using STL files, which is ofthe order of the chordal tolerance used to generate tessellations. The system model involves electrical and mechanical dynamics of the galvanometers and sensors. The controller, which acts on two mirrors, deflecting the laser beam of a stereolithography machine in the x and y directions respectively, should be easily substituted for current systems. Application of the methodology to freeform curves shows acceptable tracking and can be improved by judicious selection ofthe equation representing the spatial parameter as a function of time.Mechanical Engineerin

On the Use of Angled, Dynamic Laser Beams to Improve Stereolithography Surface Finish

Improved surface finish of Stereolithography (SLA) parts is an important goal for furthering the resolution of the technology. In order to improve the surface finish, a dynamic laser beam with changing angle, beam size, beam shape, and irradiance distribution is proposed. In this paper, an analytical irradiance model of an angled, dynamic laser beam in the SLA process is presented. This model is used to simulate cured shapes of SLA builds. Simulated build shapes are compared to established SLA analytical models and conclusions are drawn on the accuracy of the developed model.Mechanical Engineerin

3d Scanning And The Impact Of The Digital Thread On Manufacturing And Re-Manufacturing Applications

3D laser line scanners are becoming a powerful technology for capturing point cloud datasets and collecting dimensional information for many objects. However, the use of point cloud is limited due to many factors. These include the lack of on deep understanding of the effect of point cloud parameters on scan quality. This knowledge is critical to gaining an understanding of the measurement in point cloud. Currently, there are no adequate measurement procedures for 3D scanners. There is a need for standardized measurement procedures to evaluate 3D scanner accuracy due to uncertainties in 3D scanning, such as surface quality, surface orientation and scan depth [6]. The lack of standardized procedures does not allow the technology to be fully automated and used in manufacturing facilities that would allow 100% in-line inspection. In this dissertation I worked on accomplishing four tasks that will achieve the objective of having a standardized measurement procedure that is critical to develop an automated laser scanning system to avoid variations and have consistent data capable of identifying defects. The four tasks are: (1) linking the robot workspace with the scanner workspace; (2) studying the effect of the scanning speed and the resolution on point cloud quality by conducting an experiment with systematically varied scan parameters on scan quality; (3) studying the overall error of that is associated with the transformation of the point cloud in a remanufacturing facility using additive manufacturing. The parameters that were tested are the effect of view angle, standoff distance, speed, and resolution. Knowing the effect of these parameters is important in order to generate the scan path that provides the best coverage and quality of points collected. There is also a need to know the impact of all the scanning parameters especially the speed and the resolution; (4) modeling a machine learning tool to optimize the parameters of different scanning techniques after collecting the scanning results to select the optimal ones that provide the best scan quality. With the success of this work, the advancement and practice of automated quality monitoring in manufacturing will increase

Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining

The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection

Feature-based hybrid inspection planning for complex mechanical parts

Globalization and emerging new powers in the manufacturing world are among many challenges, major manufacturing enterprises are facing. This resulted in increased alternatives to satisfy customers\u27 growing needs regarding products\u27 aesthetic and functional requirements. Complexity of part design and engineering specifications to satisfy such needs often require a better use of advanced and more accurate tools to achieve good quality. Inspection is a crucial manufacturing function that should be further improved to cope with such challenges. Intelligent planning for inspection of parts with complex geometric shapes and free form surfaces using contact or non-contact devices is still a major challenge. Research in segmentation and localization techniques should also enable inspection systems to utilize modern measurement technologies capable of collecting huge number of measured points. Advanced digitization tools can be classified as contact or non-contact sensors. The purpose of this thesis is to develop a hybrid inspection planning system that benefits from the advantages of both techniques. Moreover, the minimization of deviation of measured part from the original CAD model is not the only characteristic that should be considered when implementing the localization process in order to accept or reject the part; geometric tolerances must also be considered. A segmentation technique that deals directly with the individual points is a necessary step in the developed inspection system, where the output is the actual measured points, not a tessellated model as commonly implemented by current segmentation tools. The contribution of this work is three folds. First, a knowledge-based system was developed for selecting the most suitable sensor using an inspection-specific features taxonomy in form of a 3D Matrix where each cell includes the corresponding knowledge rules and generate inspection tasks. A Travel Salesperson Problem (TSP) has been applied for sequencing these hybrid inspection tasks. A novel region-based segmentation algorithm was developed which deals directly with the measured point cloud and generates sub-point clouds, each of which represents a feature to be inspected and includes the original measured points. Finally, a new tolerance-based localization algorithm was developed to verify the functional requirements and was applied and tested using form tolerance specifications. This research enhances the existing inspection planning systems for complex mechanical parts with a hybrid inspection planning model. The main benefits of the developed segmentation and tolerance-based localization algorithms are the improvement of inspection decisions in order not to reject good parts that would have otherwise been rejected due to misleading results from currently available localization techniques. The better and more accurate inspection decisions achieved will lead to less scrap, which, in turn, will reduce the product cost and improve the company potential in the market

Kinematic Modeling Of An Automated Laser Line Scanning System

This research work describes the geometric coordinate transformation in an automated laser line scanning system caused by movements required for scanning a component surface. The elements of an automated laser scanning system (robot, laser line scanner, and the component coordinate system) function as a mechanical linkage to obtain a trajectory on a component surface. This methodology solves the forward kinematics, derives the component surface, and uses inverse kinematic equations to characterize the movement of the entire automated scanning system on point trajectory. To reach a point on the component, joint angles of robot have been calculated. As a result, trajectory path is obtained. This obtained robot poses on point trajectory of the component surface can be used as an input for future work that aims to develop optimal scan paths to collect “best” point cloud data sets. This work contributes in laser scanning inspection of component surfaces in manufacturing, remanufacturing, and reverse engineering applications