A Robotic Milling System Based on 3D Point Cloud

Industrial robots have advantages in the processing of large-scale components in the aerospace industry. Compared to CNC machine tools, robot arms are cheaper and easier to deploy. However, due to the poor consistency of incoming materials, large-scale and lightweight components make it difficult to automate robotic machining. In addition, the stiffness of the tandem structure is quite low. Therefore, the stability of the milling process is always a concern. In this paper, the robotic milling research is carried out for the welding pre-processing technology of large-scale components. In order to realize the automatic production of low-conformity parts, the on-site measurement–planning–processing method is adopted with the laser profiler. On the one hand, the laser profiler hand–eye calibration method is optimized to improve the measurement accuracy. On the other hand, the stiffness of the robot’s processing posture is optimized, combined with the angle of the fixture turntable. Finally, the experiment shows the feasibility of the on-site measurement–planning–processing method and verifies the correctness of the stiffness model.

UML knowledge model for measurement process including uncertainty of measurement

Measurement technology has made an enormous progress in the last decade. With the advent of knowledge representation, various object-oriented models for measurement systems have been developed in the past. Most common limitations of all these models were not incorporating the uncertainty in the measurement process. In this paper, we proposed an object-oriented model depicting the information and knowledge flow in the measurement process, including the measurement uncertainty. The model has three major object classes, namely measurement planning, measurement system and analysis & documentation. These are further classified into sub-classes and relationships amongst them. Attributes and operations are also defined within the classes. This gives a practical and conceptual view of knowledge in the form of object-model for measurement processes. A case study is presented which evaluates the uncertainty of the measurement of a 100 mm gauge block, using both Type A and Type B evaluation methods of the GUM approach.This case study is very similar to the evaluation of calibration uncertainty of CMM. This model can be converted into semantic knowledge representation such as ontology of measurement process domain. Other use of this model is to support the quality engineering in manufacturing industry and research.

An optimized and virtual on-machine measurement planning model

The specific needs of customers set requirements like flexibility and custom-made products, as well as quick placement of products on the markets. Mass customization responds to these requirements and imposes new demands inside manufacturing systems such as optimization and virtualization of machining and measurement processes. A contribution in that direction is presented in this paper, pertaining to development and verification an on-machine measurement planning model. The aim of the verification is to visualize collision check between the measuring head placed in the tool holder and the workpiece on the machine tool working table. The virtual on-machine measurement was realized on the configured virtual machine tool LOLA HBG80 in the CAD environment. The measurement path is generated by a new planning methodology, then optimized using ants colony, programed and verified by simulations through few examples of standard forms of tolerance. The output of the simulation process is the G-code for real on-machine measurement for prismatic parts of medium and rough dimensional accuracy.

Resource Leveraging to Achieve Large-Scale Implementation of Effective Educational Practices

We propose in this article that a central element in the large-scale implementation of evidence-based practices is the process by which initial investment in local demonstrations is leveraged into larger implementation efforts. We offer a definition of this “resource leveraging” and propose a process for both measuring and reporting the effects of leveraging. We suggest that resource leveraging become a valid focus of future research and that the intentional measurement, planning, and management of resource leveraging be used to improve the scaling-up of effective practices.

Application of process mapping for digitization of mechanical parts with 3D laser scanner

This work presents a systematization method for digitization of mechanical parts with three-dimensional (3D) laser scanner using the process mapping method. The application involves the use of the IDEFØ methodology of process mapping to address the sequence of steps required to obtain the computer-aided design (CAD) model of the measured part. The variables involved in the setup and measurement with 3D laser scanner were investigated and applied to regular and free-form parts, and the parameter geometry, texture, light reflection and procedure of data acquisition were considered in the analysis. The software commands used to create the CAD models were also included and the ones related to mesh and surface creation were detailed. The systematized measurement planning was graphi graphically presented, and it proved useful to operators during the digitization process.

A Software Measurement Pattern Language for Measurement Planning aiming at SPC

The growing interest of organizations in improving their software processes has led them to aim at achieving the high maturity, where statistical process control (SPC) is required. One of the challenges to perform SPC is selecting measures suitable for it. Measures used in SPC can be found in the literature and could be reused by organizations, but information is disperse and non-structured, not favoring reuse. This paper presents MePPLa (Measurement Planning Pattern Language), a pattern language developed based on the findings of a systematic mapping and a survey that investigated measures for SPC. An initial evaluation of MePPLa showed that it favors reuse, contributes to productivity in measurement planning and to the quality of the measurement plan.

COMPARISON OF ZEB1 AND LEICA C10 INDOOR LASER SCANNING POINT CLOUDS

We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the requirements of the project, it is important to have a vision about what to expect from different sensors. In this paper, we provide a detailed analysis of the point clouds of the same room interior acquired from Zeb1 and Leica C10 sensors. First, it is visually assessed how different features appear in both the Zeb1 and Leica C10 point clouds. Next, a quantitative analysis is given by comparing local point density, local noise level and stability of local normals. Finally, a simple 3D room plan is extracted from both the Zeb1 and the Leica C10 point clouds and the lengths of constructed line segments connecting corners of the room are compared. The results show that Zeb1 is far superior in ease of data acquisition. No heavy handling, hardly no measurement planning and no point cloud registration is required from the operator. The resulting point cloud has a quality in the order of centimeters, which is fine for generating a 3D interior model of a building. Our results also clearly show that fine details of for example ornaments are invisible in the Zeb1 data. If point clouds with a quality in the order of millimeters are required, still a high-end laser scanner like the Leica C10 is required, in combination with a more sophisticated, time-consuming and elaborative data acquisition and processing approach.