Systematic review of STEP-NC-based inspection

Saif, Yazid; Yusof, Yusri; Latif, Kamran; Kadir, Aini Zuhra Abdul; Ahmed, Maznah lliyas

doi:10.1007/s00170-020-05468-7

Cited by 11 publications

(5 citation statements)

References 144 publications

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“…The purpose of the Computer-Assisted Inspection Planning (CAIP) framework is to determine the best possible sequences of inspection steps and the comprehensive inspection technique for each feature. Some surveys intend to discuss the planning process inspection [21][22][23][24], while some conducted with o ine inspection used Coordinate Measuring Machine (CMM) [25][26][27][28][29] and other research discussed online inspection during process. [30][31][32][33].…”

Section: Inspection Process Planningmentioning

confidence: 99%

A Case Study- Monitoring and Inspection Based on IoT for STEP-NC Data Model

Ahmad

Saif

Yusof³

et al. 2021

Preprint

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Cyber-Physical Machine Tools (CPMT) is currently recognized as a new generation of machine tools that align with Industry 4.0 needs as a smart, well connected, advanced accessibility, more adaptive and autonomous solution. It can be achieved through standardized design method and communication protocols. This article presents a case study on monitoring and inspection based on Internet of Things (IoT) for STEP-NC data model toward a CPMT. More specifically, the monitoring approach utilizing an IoT based monitoring architecture for machining process monitoring, while the inspection approach using a coordinate measuring machine for machined part inspection. The monitoring and inspection approaches can achieve high accuracy of machining process condition detection and enable measurement of machined parts to fulfil CPMT needs and I4.0. The case study validated that the developed monitoring approach performed well and was highly sensitive to any changes during the machining process, specifically on the tool condition. As per the inspection approach, the reliability of the machined model was 99.97%. Based on the results of both the approaches, it is confirmed that both tasks can be designed and support digital factory and other manufacturing process stages in the future such as preventive maintenance, inspecting, sizing, assembling, and others.

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Section: Inspection Process Planningmentioning

confidence: 99%

A Case Study- Monitoring and Inspection Based on IoT for STEP-NC Data Model

Ahmad

Saif

Yusof³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Benefitting from its enormous paradigm size, the sophisticated network architecture, and appropriate genetic algorithm, the configured image recognition of the neural network can decide the importance of being able to draw directly and consistently standard features hierarchical structure from valid images obtained in a closely monitored or unmonitored manner. The critical systematic analysis of the gap for the development platform structure of software and hardware configurations that interfaces with the Raspbian computer has been implemented by (Saif et al, 2020). This research will lead to the measuring of the part21 based on the STEP-NC standard by the implementation of a new measurement approach using the Vision Inspection System(VIS).…”

Section: Related Workmentioning

confidence: 99%

A Framework to Develop Intelligent System for Capturing Product Features Using Open Cv Technique

Saif

Yusof

Ahmed

et al. 2020

JTOM

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This research aims to propose an innovative framework using ISO14649 standard to detect defects in manufactured shaped objects or geometric surfaces of non-linear products of the CNC machine. The significant importance in order to recognize the potential to improve industry product quality inspection and encourage the waste of timing machines and product rejection. Open Computer Vision (Open CV) offers a smart, non-contact measurement and cost-effective technique to fulfil the requirements. The framework depends on the new technique of Open CV, which includes two parts: an intelligent selection of work-piece capturing the image for a particular inspection of the planar interfaces such as the hole, rectangular, pocket one, and the symmetric lighting model comparison approach for measurement of defects in the matched images. The contribution of this study is to build a structure in the computer vision method with a convolution neural network that predicts the classification of the feature for better accuracy and emphasizes the significant characteristics of the image processing technique coupled with experimental data on demanding image datasets and quality inspection measures.

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“…Furthermore, machine vision can conduct non-contact inspections of products, whereas most instruments used to measure roundness require physical contact. As a consequence, there has been significant interest in developing machine vision systems for inspection in the industrial sector [2,[26][27][28][29][30][31]. A machine vision-based inspection system has been addressed for real-time geometric inspection of A-grade nuts to ensure their quality.…”

Section: Introductionmentioning

confidence: 99%

Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques

Saif,

Rus,

Yusof

et al. 2023

Applied Sciences

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In the era of Industry 4.0, the digital capture of products has become a critical aspect, which prompts the need for reliable inspection methods. In the current technological landscape, the Internet of Things (IoT) holds significant value, especially for industrial devices that require seamless communication with local and cloud computing servers. This research focuses on the advancements made in roundness measurement techniques for industrial automation by leveraging an IoT architecture, computer vision, and image processing. The interconnectedness enables the efficient collection of feedback information, meeting the demands of closed-loop manufacturing. The accuracy and performance of assemblies heavily rely on the roundness of specific workpiece components. In order to address this problem, automated inspection methods are needed. A new method of computer vision for measuring and inspecting roundness is proposed in this paper. This method uses a non-contact method that takes into account all points on the contours of measured objects, making it more accurate and practical than conventional methods. The system developed by AMMC Laboratory captures Delrin work images and analyzes them using a specially designed 3SMVI system based on Open CV with Python script language. The system can measure and inspect several rounded components in the same part, including external frames and internal holes. It is calibrated to accommodate various units of measurement and has been tested using sample holes within the surface feature of the workpiece. According to the results of both techniques, there is a noticeable difference ranging from 2.9 µm to 11.6 µm. However, the accuracy of the measurements can be enhanced by utilizing a high-resolution camera with proper lighting. The results were compared to those obtained using a computer measurement machine (CMM), with a maximum difference of 8.7%.

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Systematic review of STEP-NC-based inspection

Cited by 11 publications

References 144 publications

A Case Study- Monitoring and Inspection Based on IoT for STEP-NC Data Model

A Case Study- Monitoring and Inspection Based on IoT for STEP-NC Data Model

A Framework to Develop Intelligent System for Capturing Product Features Using Open Cv Technique

Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques

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