Contribution to the development of a digital twin based on CMM to support the inspection process

Digital twin (DT) based on CMMs acting as a mirror between the physical and virtual measuring system and process. The inspection planning process performed on the virtual components of DT, and execution of measurement on the physical components. In this paper the measurement system with the DEA-IOTA-2203 was used as a physical twin, and a virtual machine, generated after modeling and configuring in PTC Creo software. Also, a simulation process was performed in order to check the collision and generate a measuring path for one example prismatic part. The information flow is unidirectional and flowing from the virtual to the physical inspection system based on CMM. In this way, a data format or a list of instructions for the physical machine and its movements per axes is provided. Virtual measurement system is developed for inspection of the standard types of tolerances and family of prismatic mechanical parts. The result of this paper is a new contribution to the development of the digital twin for CMM based on unidirectional information flow by.ncl (DMIS) file. The application of the results of DT development is especially pronounced when planning the inspection of prismatic parts with a large number of tolerances in industrial conditions

Intelligent dual curve-driven tool path optimization and virtual CMM inspection for sculptured surface CNC machining

This paper investigates the profitability of a dual‐curve driven surface finish tool path under the concept of optimizing crucial machining parameters such as toroidal end‐mill diameter, lead angle and tilt angle. Surface machining error as well as tool path time are treated as optimization objectives under a multi‐criteria sense, whilst a central composite design is conducted to obtain experimental outputs for examination and, finally, fit a full quadratic model considered as the fitness function for process optimization by means of a genetic algorithm. A benchmark sculptured surface given as a second‐order parametric equation was tested and simulated using a cutting‐edge manufacturing modeling software and best parameters recommended by the genetic algorithm were implemented for validation. Further assessment involves the virtual inspection to selected profile sections on the part. It was shown that the approach can produce dual‐curve driven tool trajectories capable of eliminating sharp scallop heights, maximizing machining strip widths as well as maintaining smoothness quality and machining efficiency

Hardware-in-the-loop And Digital Twin Enabled Autonomous Robotics-assisted Environment Inspection

Empowered by the advanced 3D sensing, computer vision and AI algorithm, autonomous robotics provide an unprecedented possibility for close-up infrastructure environment inspection in an efficient and reliable fashion. Deep neural network (DNN) learning algorithms, pretrained on the large database can empower real-time object detection as well as fully autonomous, safe robotic navigation in unstructured environments while avoiding the potential obstacle. However, the development and deployment of the robots, inspection planning and operation procedures are still tedious and segmented with tremendous manual intervention during environmental inspection and anomaly monitoring. The proposed digital twin approach is able to provide a virtual representation model of the target environment either from a build-design or from 3D scanning of the real-world physical assets at high resolution in the Unity simulation environment, a transverse drone robot model and test its Robotics Operating System(ROS) autonomous navigation and obstacle avoidance software stack, and the hardware-in-the-loop test can thus be conducted for the flight control algorithm effectiveness and real-time object detection performance evaluation. The preliminary result shows that VGG16-UNet deep learning algorithm was able to use only a small amount of guidance and time from experienced inspection pilots to successfully identify the critical elements and defects and real-time navigate around the unstructured environment. The proposed digital twin framework and methodology is promising to be utilized for developing and testing fully autonomous inspection robots and its path planning and navigation and detection operation with greater cost- and time-efficiency

Design, implementation, and testing of advanced virtual coordinate-measuring machines

Copyright @ 2011 IEEE. This article has been made available through the Brunel Open Access Publishing Fund.Advanced virtual coordinate-measuring machines (CMMs) (AVCMMs) have recently been developed at Brunel University, which provide vivid graphical representation and powerful simulation of CMM operations, together with Monte-Carlo-based uncertainty evaluation. In an integrated virtual environment, the user can plan an inspection strategy for a given task, carry out virtual measurements, and evaluate the uncertainty associated with the measurement results, all without the need of using a physical machine. The obtained estimate of uncertainty can serve as a rapid feedback for the user to optimize the inspection plan in the AVCMM before actual measurements or as an evaluation of the measurement results performed. This paper details the methodology, design, and implementation of the AVCMM system, including CMM modeling, probe contact and collision detection, error modeling and simulation, and uncertainty evaluation. This paper further reports experimental results for the testing of the AVCMM

Development of a novel virtual coordinate measuring machine

Existing VCMMs (virtual coordinate measuring machine) have been mainly developed to either simulate the measurement process hence enabling the off-line programming, or to perform error analysis and uncertainty evaluation. Their capability and performance could be greatly improved if there is a complete solution to cover the whole process and provide an integrated environment. The aim of this study is to develop such a VCMM that not only supports measurement process simulation, but also performs uncertainty evaluation. It makes use of virtual reality techniques to provide an accurate model of a physical CMM, together with uncertainty evaluation. An interface is also provided to communicate with CMM controller, allowing the measuring programs generated and simulated in the VCMM to be executed or tested on the physical CMM afterwards. This paper discusses the proposal of a novel VCMM design and the preliminary results

Sensor integration for robotic laser welding processes

The use of robotic laser welding is increasing among industrial applications, because of its ability to weld objects in three dimensions. Robotic laser welding involves three sub-processes: seam detection and tracking, welding process control, and weld seam inspection. Usually, for each sub-process, a separate sensory system is required. The use of separate sensory systems leads to heavy and bulky tools, in contrast to compact and light sensory systems that are needed to reach sufficient accuracy and accessibility. In the solution presented in this paper all three subprocesses are integrated in one compact multipurpose welding head. This multi-purpose tool is under development and consists of a laser welding head, with integrated sensors for seam detection and inspection, while also carrying interfaces for process control. It can provide the relative position of the tool and the work piece in three-dimensional space. Additionally, it can cope with the occurrence of sharp corners along a three-dimensional weld path, which are difficult to detect and weld with conventional equipment due to measurement errors and robot dynamics. In this paper the process of seam detection will be mainly elaborated

Integrated sensors for robotic laser welding

A welding head is under development with integrated sensory systems for robotic laser welding applications. Robotic laser welding requires sensory systems that are capable to accurately guide the welding head over a seam in three-dimensional space and provide information about the welding process as well as the quality of the welding result. In this paper the focus is on seam tracking. It is difficult to measure three-dimensional parameters of a ream during a robotic laser welding task, especially when sharp corners are present. The proposed sensory system is capable to provide the three dimensional parameters of a seam in one measurement and guide robots over sharp corners