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About this book

This book examines an intelligent system for the inspection planning of prismatic parts on coordinate measuring machines (CMMs). The content focuses on four main elements: the engineering ontology, the model of inspection planning for prismatic parts on CMMs, the optimisation model of the measuring path based on an ant-colony approach, and the model of probe configuration and setup planning based on a genetic algorithm. The model of inspection planning for CMMs developed here addresses inspection feature construction, the sampling strategy, probe accessibility analysis, automated collision-free operation, and probe path planning. The proposed model offers a novel approach to intelligent inspection, while also minimizing human involvement (and thus the risk of human error) through intelligent planning of the probe configuration and part setup. The advantages of this approach include: reduced preparation times due to the automatic generation of a measuring protocol; potential optimisation of the measuring probe path, i.e., less time needed for the actual measurement; and increased planning process autonomy through minimal human involvement in the setup analysis and probe configuration.

Table of Contents

Frontmatter

Chapter 1. Introduction and Review of Inspection Planning Methods

Research and development of intelligent systems for inspection planning on coordinate measuring machines (CMMs) present a precondition for the development of a new generation of technological systems and their application in a digital quality concept, which is based on a global product interoperability model [15] where CAD-CAM-CAI information is integrated within a digital platform. This approach presents a basis for virtualisation, simulation and planning inside metrological systems, particularly for the inspection of prismatic parts (PMPs) on a CMM. Research conducted within this book relates to the field of inspection planning for the metrologically complex prismatic parts on a CMM. In a broad sense, the research is directed to the development of the local and global inspection plan for prismatic parts on a CMM. In a narrow sense, it encompasses determination of inspection sequences for metrological features, determination of the number and position of measuring points, as well as the optimal measuring probe path.
Slavenko M. Stojadinović, Vidosav D. Majstorović

Chapter 2. Ontological Knowledge Base for Integrating Geometry and Tolerance of PMPs

When engineering information is once created and applied, it is often stored and forgotten. Current approaches for information retrieval are not effective enough in understanding the engineering content, because they are not developed to share, reuse and represent information of the engineering domain [1]. This chapter presents the current state of engineering ontology (EO) development and proposes a new method for its development at conceptual level in order to reuse and share knowledge in the domain of coordinate metrology (CM) and inspection planning in that domain. More specifically, the method defines the development of ontology for the construction of knowledge base, as one of the basic components for integration of geometry and tolerance of PMPs.
Slavenko M. Stojadinović, Vidosav D. Majstorović

Chapter 3. The Model for Inspection Planning of PMPs on a CMM

This chapter presents a model of prismatic measurement parts (PMPs) inspection planning on CMMs, in terms of an intelligent system of inspection planning. The developed model is composed of mathematical model, inspection feature construction, sampling strategy, probe accessibility analysis, automated collision-free generation and probe path planning. The proposed model presents a novel approach for the automatic inspection and a basis for the development of an integrated, intelligent system of inspection planning. The advantages of this approach imply the reduction of preparation time due to an automatic generation of a measuring protocol, a possibility for the optimisation of measuring probe path, i.e. the reduction of time needed for the actual measurement and analysis of a workpiece setup, as well as an automatic configuration of measuring probes.
Slavenko M. Stojadinović, Vidosav D. Majstorović

Chapter 4. The Model of Probe Configuration and Setup Planning for Inspection of PMPs Based on GA

This chapter presents an approach of probe configuration and setup planning for inspection of PMPs. The developed model is composed of two main parts: the analysis of PMP setups and the probe configuration for inspection on a CMM. A set of possible PMP setups and probe configurations for two types of sensors (probe star and probe head) is reduced to optimal number using a modified, current GA-based methodology. For each part setup, the optimal probe configuration and optimal point-to-point measuring path are possible to obtain. The advantage of the model is reduction of the total measurement time as well as elimination of errors due to human factor (minimising human involvement) through intelligent planning of probe configuration and part setup. This setup model can be applied not only for inspection planning on a CMM but also for the setup of prismatic parts machining on machining centres.
Slavenko M. Stojadinović, Vidosav D. Majstorović

Chapter 5. Ant Colony Optimisation of the Measuring Path of PMPs on a CMM

This chapter presents optimisation of a measuring probe path in the inspection of prismatic parts on a CMM. The optimisation model is based on the mathematical model that establishes an initial path presented by the set of points, with defined sequence of measuring probe passes without collision, and the solution of the travelling salesman problem (TSP) obtained using ant colony optimisation (ACO). A mathematical model was developed, analysed and presented in Chap. 3, so that a brief reference will be made to it in this chapter in order to relate it to the measuring path optimisation. The problem of finding the shortest measuring probe path in inspection planning of PMP on a CMM is reduced into the TSP solution. TSP is solved by using the techniques of artificial intelligence (AI) such as genetic algorithms (GA), neural networks (NN) and recently the swarm theory (ST). In order to solve TSP, ACO algorithm that aims to find the shortest path of ant colony movement (i.e. the optimised path) is applied. Then, the optimised path is compared with the measuring path obtained by online programming on CMM ZEISS UMM500 and with the measuring path obtained in the CMM module for inspection in software Pro/ENGINEER version Wildfire 4.0 (PTC Creo).
Slavenko M. Stojadinović, Vidosav D. Majstorović

Chapter 6. Experiment, Results and Concluding Remarks

For verification of the developed model of inspection planning for prismatic parts on a CMM and measuring path simulation, to visually inspect the collision between the measuring probe and the workpiece, the programme was first written. Apart from verification and simulation, one of the major goals of the written programme is generation of the measuring protocol and a list of output control data, which are then used in the experimental planning process and as an input for experimental measurements. The simulation output is a measuring protocol for CMM ZEISS UMM500. An experiment was performed on two prismatic parts that have been produced for the purpose of this research. The inspection results show that all tolerances for both parts are within the specified limits. The proposed model presents a novel approach of the intelligent inspection planning. The advantages of this approach imply the reduction of preparation time due to an automatic generation of a measuring protocol, a possibility for the optimisation of measuring probe path, i.e. the reduction of a time needed for the actual measurement and increase the planning process autonomy through minimum human involvement in the process of part setups analysis and measuring probes configuration.
Slavenko M. Stojadinović, Vidosav D. Majstorović
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