scholarly journals Development of a Coordinate Measuring Machine—Based Inspection Planning System for Industry 4.0

2021 ◽  
Vol 11 (18) ◽  
pp. 8411
Author(s):  
Slavenko M. Stojadinovic ◽  
Vidosav D. Majstorovic ◽  
Adam Gąska ◽  
Jerzy Sładek ◽  
Numan M. Durakbasa
Keyword(s):  
Industry 4.0 ◽  
Production Efficiency ◽  
Coordinate Measuring Machine ◽  
Measurement Process ◽  
Planning System ◽  
Smart Manufacturing ◽  
Inspection Planning ◽  
New Paradigm ◽  
Measuring Machine ◽  
Measurement Verification

Industry 4.0 represents a new paradigm which creates new requirements in the area of manufacturing and manufacturing metrology such as to reduce the cost of product, flexibility, mass customization, quality of product, high level of digitalization, optimization, etc., all of which contribute to smart manufacturing and smart metrology systems. This paper presents a developed inspection planning system based on CMM as support of the smart metrology within Industry 4.0 or manufacturing metrology 4.0 (MM4.0). The system is based on the application of three AI techniques such as engineering ontology (EO), GA and ants colony optimization (ACO). The developed system consists of: the ontological knowledge base; the mathematical model for generating strategy of initial MP; the model of analysis and optimization of workpiece setups and probe configuration; the path simulation model in MatLab, PTC Creo and STEP-NC Machine software, and the model of optimization MP by applying ACO. The advantage of the model is its suitability for monitoring of the measurement process and digitalization of the measurement process planning, simulation carried out and measurement verification based on CMM, reduction of the preparatory measurement time as early as in the inspection planning phase and minimizing human involvement or human errors through intelligent planning, which directly influences increased production efficiency, competitiveness, and productivity of enterprises. The measuring experiment was performed using a machined prismatic workpiece (PW).

scholarly journals A frame for a computer aided inspection planning system

2015 ◽  
Vol 4 (1) ◽  
pp. 125 ◽  
Author(s):  
Wilma Polini ◽  
Giovanni Moroni
Keyword(s):  
Measurement Techniques ◽  
Coordinate Measuring Machine ◽  
Planning System ◽  
Inspection Planning ◽  
Coordinate Measurement ◽  
Measurement Results ◽  
Measuring Machine ◽  
Set Up ◽  
Almost All ◽  
Computer Aided Inspection

Coordinate Measuring Machine (CMM) inspection planning is an activity performed by well-trained operators, but different measurement techniques, using the same data analysis algorithms yield in different measurement results. This is a well-recognized source of uncertainty in coordinate measurement. A CMM, provided with an automatic inspection planning (CAIP) system, permits to implement more accurate and efficient operating procedures and to fit higher quality assurance standards and tighter production timings.In this paper we present a frame of a CAIP system, able to deal with almost all the decisional stages of CMM inspection. Moreover, original approaches have been developed and presented in inspection feature selection, part set-up, probe configuration, and path planning.

scholarly journals Application of 3D CAD in the Design of Inspection and Planning System of Intelligent Three-coordinate Measuring Machine

2020 ◽  
Vol 18 (S3) ◽  
pp. 141-152
Author(s):  
Jin Guang ◽  
Fan Li
Keyword(s):  
Information Integration ◽  
Coordinate Measuring Machine ◽  
Planning System ◽  
Sampling Point ◽  
Inspection Planning ◽  
Point Distribution ◽  
General Surface ◽  
Sampling Points ◽  
Measuring Machine ◽  
Specific Implementation

Computer aided inspection planning based on CAD coordinate measuring machine is the basic key technology, which occupies a very important position in the quality system. Nowadays, the research of integration technology has made a lot of achievements, but the research on information integration of system and system lags far behind the information integration of machining. How to use the part information and measurement-related knowledge provided by the product model to automatically generate optimal testing procedures and testing instructions for use is the basic task of the oriented intelligent system. This paper aims at the development of intelligent CMM inspection planning system based on 3D, from the overall analysis and design of the system to the extraction of detection geometric information, sampling planning, detection path planning and automatic generation of quack measurement program and other related key technologies will be studied. This paper briefly analyzes the relevant factors that determine the number of sampling points and summarizes the point requirements for the distribution of sampling points, and in view of the shortcomings and limitations of various methods of sampling point distribution on the general surface, a sampling strategy with adaptive step size is proposed, which solves the problem of sampling planning on the general surface. In the specific implementation of sampling planning, it is divided into two ways: edge-based and face-based geometric element measurement and sampling. Considering the requirements of distribution points, specific sampling algorithms are designed respectively, focusing on the analysis of the differences between edges and faces.

A PLM-based automated inspection planning system for coordinate measuring machine

2006 ◽  
Author(s):  
Haibin Zhao ◽  
Junying Wang ◽  
Boxiong Wang ◽  
Jianmei Wang ◽  
Huacheng Chen
Keyword(s):  
Coordinate Measuring Machine ◽  
Planning System ◽  
Automated Inspection ◽  
Inspection Planning ◽  
Measuring Machine

scholarly journals Defining SMEs’ 4.0 Readiness Indicators

2020 ◽  
Vol 10 (24) ◽  
pp. 8998
Author(s):  
Nilubon Chonsawat ◽  
Apichat Sopadang
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Cloud Manufacturing ◽  
Smart Manufacturing ◽  
Increase Production Efficiency ◽  
Five Dimensions ◽  
High Stage ◽  
Industrial Internet ◽  
Infrastructure System

Industry 4.0 revolution offers smart manufacturing; it systematically incorporates production technology and advanced operation management. Adopting these high-state strategies can increase production efficiency, reduce energy consumption, and decrease manufacturer costs. Simultaneously, small and medium-sized enterprises (SMEs) were the backbone of economic growth and development. They still lack both the knowledge and decision-making to verify this high-stage technology’s performance and implementation. Therefore, the research aims to define the readiness indicators to assess and support SMEs toward Industry 4.0. The research begins with found aspects that influence the SME 4.0 readiness by using Bibliometric techniques. The result shows the aspects which were the most occurrences such as the Industrial Internet, Cloud Manufacturing, Collaborative Robot, Business Model, and Digital Transformation. They were then grouped into five dimensions by using the visualization of similarities (VOS) techniques: (1) Organizational Resilience, (2) Infrastructure System, (3) Manufacturing System, (4) Data Transformation, and (5) Digital Technology. Cronbach’s alpha then validated the composite dimensions at a 0.926 level of reliability and a significant positive correlation. After that, the indicators were defined from the dimension and aspects approach. Finally, the indicators were pilot tested by small enterprises. It appeared that 23 indicators could support SMEs 4.0 readiness indication and decision-making in the context of Industry 4.0.

An Initial Framework for Implementation of Industry 4.0 in the High Technological Manufacturing Sector in Southern California

2019 ◽  
Author(s):  
Sagil James ◽  
Anupam Shetty
Keyword(s):  
Industry 4.0 ◽  
Southern California ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Smart Manufacturing ◽  
New Paradigm ◽  
Manufacturing Sectors ◽  
Southern California Region ◽  
The Internet Of Things ◽  
Initial Framework

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several industries have started early initiatives of implementing these technologies. As the industries are evaluating their readiness for implementing the Industry 4.0 concepts, there are several challenges which need to be addressed including high initial investment, lack of standardization, data security and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the industry as well as in academia. This research develops an initial framework for the effective implementation of Industry 4.0 in the high technology manufacturing sectors in the Southern California region. The results of this study are expected to provide a platform to expand the opportunities of Industry 4.0 further and facilitate worldwide adoption.

A Virtual CMM Inspection Tool for Capturing Planning Strategies

2017 ◽  
Author(s):  
Dimitrios Anagnostakis ◽  
James Ritchie ◽  
Theodore Lim ◽  
Raymond Sung ◽  
Richard Dewar
Keyword(s):  
Motion Tracking ◽  
Coordinate Measuring Machine ◽  
Assembly Planning ◽  
Training Methods ◽  
Inspection Planning ◽  
Sources Of Knowledge ◽  
Challenging Tasks ◽  
Measuring Machine ◽  
Planning Strategies ◽  
Product Verification

One of the most challenging tasks throughout the development and manufacturing of a product is the capturing and formalization of engineering knowledge and expertise. In the past, many researchers have successfully proposed different techniques for capturing knowledge during the design, process and assembly planning of a product. However, few efforts have focused on applying knowledge capture to the task of product verification for Coordinate Measuring Machine (CMM) inspection; most of these are manual, obtrusive for the user and time consuming since the main sources of knowledge come from documentation such as handbooks, guides or interview transcripts. This paper describes a tool for the automated logging of a planner’s actions while carrying out an inspection planning task in a virtual CMM measurement environment. The tool involves a combination of 3D motion tracking and a post-processor to decipher the context strategy in the form of an inspection plan. Various representations of a captured strategy will benefit CMM operators by providing them a tool for: understanding planning strategies, better training methods for inexperienced users and producing more efficient part programs in a shorter time.

Coordinate Measuring Machine with Large Working Volume Based on Laser Technological System

2010 ◽  
Vol 437 ◽  
pp. 453-457 ◽  
Author(s):  
Ignat A. Vykhristyuk
Keyword(s):  
Coordinate Measuring Machine ◽  
Measurement Process ◽  
Technological System ◽  
3D Measurement ◽  
Uncertainty Of Measurement ◽  
Preliminary Measurement ◽  
Working Volume ◽  
Measuring Machine

Description of coordinate measuring machine (CMM) with large working volume ( ) based on Laser technological system LSP-2000 is presented. Preliminary measurement process is described. Analysis of uncertainty of measurement is presented. Prospect of CMM’s upgrade for 3D measurement functions is given.

Design Framework for Preparing Workforce Towards Industry 4.0 Implementation in Small and Medium-Sized Enterprises

2020 ◽  
Author(s):  
Sagil James ◽  
Anupam Shetty
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Implementation Process ◽  
Secondary Data ◽  
Smart Manufacturing ◽  
New Paradigm ◽  
Skill Gaps ◽  
Adoption And Implementation ◽  
The Internet Of Things

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several large companies industries have started early initiatives for implementing these technologies. However, small and medium-sized enterprises (SMEs) face massive challenges in adopting Industry 4.0 technologies. As the SMEs are evaluating their readiness for implementing the Industry 4.0 concepts, several challenges need to be addressed, including high initial investment, lack of standardization, data security, and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the SME sector as well as in academia. This research focuses on designing a framework for training/retraining the strong workforce for SMEs to enable Industry 4.0 adoption and implementation. The framework is created using qualitative research methods followed by the secondary data collection approach. The study suggests the use of a three-step implementation process consisting of 1) creating new jobs, 2) recruiting, and 3) retraining and retaining the talent. The results of this study are expected to create a platform to train the workforce for Industry 4.0, reduce skill gaps, and retain incumbent workers in the manufacturing sector.

scholarly journals Path Planning and Setup Orientation for Automated Dimensional Inspection Using Coordinate Measuring Machines

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Osama Abdulhameed ◽  
Abdulrahman Al-Ahmari ◽  
Syed Hammad Mian ◽  
Mohamed K. Aboudaif
Keyword(s):  
Coordinate Measuring Machine ◽  
Fine Tuning ◽  
Machine Language ◽  
Inspection Planning ◽  
Suggested Approach ◽  
Inspection Plan ◽  
Inspection Process ◽  
Measuring Machine ◽  
Part Inspection ◽  
Artificial Neural Network Ann

Inspection planning is considered an essential practice in the manufacturing industries because it ensures enhanced product quality and productivity. A reasonable inspection plan, which can reduce inspection costs and achieve high customer satisfaction, is therefore very important in the production industry. Considerations such as preparations for part inspection, measuring machines, and their setups as well as the measurement path are described in an inspection plan which is subsequently translated into part inspection machine language. Therefore, the measurement of any component using a coordinate measuring machine (CMM) is the final step preceded by several other procedures, such as the preparation of the part setup and the generation of the probe path. Effective measurement of components using CMM can only be done if the preceding steps are properly optimized to automate the whole inspection process. This paper has proposed a method based on artificial intelligence techniques, namely, artificial neural network (ANN) and genetic algorithm (GA), for fine-tuning output from the different steps to achieve an efficient inspection plan. A case study to check and validate the suggested approach for producing effective inspection plans for CMMs is presented. A decrease of nearly 50% was observed in the travel path of the probe, whereas the CMM measurement time was reduced by almost 25% during the actual component measurement. The proposed method yielded the optimum part setup and the most appropriate measuring sequence for the part considered.

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