In-process Quality Inspection Research Articles

Optimizing efficiency and zero-defect manufacturing with in-process inspection: challenges, benefits, and aerospace application

In this paper, we present a comprehensive study on the implementation of machine vision-enabled in-process quality inspection systems in machining operations. Our objective is to enable zero-defect manufacturing by maximizing efficiency and effectiveness in production processes. We utilize machine vision technology as a transformative tool, playing a vital role in our comparative analysis which reveals its superiority over traditional in-situ approaches in both ideal and challenging real-world scenarios. Through simulation, we demonstrate how machine vision improves the performance of in-line process systems. We also discuss substantial challenges of implementation, such as managing environmental contamination, optimizing machine coordination, accommodating a range of part sizes, and configuring effective coolant delivery systems. Our in-depth analysis of essential factors includes the robustness of machine vision equipment, operator training for machine vision technology, and cost-benefit analysis of its implementation. The research emphasizes machine vision's crucial role in transforming manufacturing setups and enhancing advanced automation systems. The study underscores the immense potential of machine vision in in-process quality inspection to significantly reduce production costs and time, fostering higher manufacturing sustainability and competitive advantage in the era of Industry 4.0.

Snapshot hyperspectral imaging for quality assurance in Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) is widely considered a key enabling technology of the future. In order to realize its full potential, however, reproducibility and in-process quality inspection capabilities have to meet industrial requirements. The application of novel sensor technologies such as hyperspectral cameras and intelligent data evaluation methods like machine learning models will allow more reliable manufacturing processes.This article discusses the value of snapshot hyperspectral imaging as a means to predict process states and defects with the help of machine learning algorithms. The imaging technology is presented and its characteristic advantage of providing spectral as well as spatial resolution is weighed against the drawbacks of low temporal resolution and reduced spatial resolution. Besides, different methods and configurations for in- process data acquisition and subsequent data labeling are explained. Finally, the utilization of this monitoring approach to the LPBF-processing of magnesium alloys is discussed and results are presented.

In‐Process Quality Inspection of Rolling Element Bearings Based on the Measurement of Microelastic Deformation of Outer Ring

Quality inspection is the necessary procedure before bearings leaving manufacturing factories. A testing machine with low shaft speed and light radial load condition is generally used to test the dynamic quality of bearings, which avoids creating any potential damages to testing bearings. However, the signal of defective bearings is easily polluted by very weak noise using the traditional vibration‐based measurement method due to the low shaft speed and light radial load condition specified for nondestructive inspection, which needs complicated and time‐consuming calculation and is not suitable for online inspection. Thus, there are problems about special operating conditions and weak fault severity in quality inspection of bearings, which is quite different from the fault diagnosis of bearings. In this paper, a novel dynamic quality evaluation technique is proposed based on the measurement of Hertz deformations. The measurement system is mainly composed of an eddy current sensor, sensor fixture, and data acquisition platform with less transfer path than the vibration‐based measurement system. The sensor fixture is optimized through numerical simulations to obtain signals with a high signal‐to‐noise ratio. Accurate evaluation of dynamic quality can be implemented reliably with simple signal processing. The proposed method can be used with a rotating speed of 100 rev/min and test load of 100 N, which is remarkably lower than the traditional quality inspection machineries with a rotating speed of around 1000 rev/min and the test load of 400 N. Both simulation and experiment studies have verified the proposed method.

Direct Metal Laser Sintering

AbstractA few years ago, 3D printing and additive manufacturing (AM) were next generation technologies and well known as methods for rapid prototyping. Less rapid manufacturing applications were on the market (e. g. manufacturing of dental crowns and bridges). Today, AM is on the step to serial production, industries ranging from aerospace and medical to energy and automotive benefit from the possibility to design and manufacture products in a completely new way. These industries require a detailed documentation of the process including automated in‐process quality inspection. Several technologies are used for quality assurance of the process and quality inspection of the parts. This paper describes how to setup an in‐process monitoring system to detect a process phenomenon called “splashy process” for the DMLS process.

Optical In‐Process Monitoring of Direct Metal Laser Sintering (DMLS)

AbstractAdditive Manufacturing (AM) is a revolutionary technology enabling the users to design and manufacture products in a completely new way. As the AM technology is proceeding from rapid prototyping to rapid manufacturing, industries ranging from aerospace and medical (Fig. 1) to energy and automotive require detailed documentation of the process. The market demands automated in‐process quality inspection. The goal is to get a better understanding of the process and assure repetitive high‐end part quality. Plasmo, a worldwide leading engineering partner for quality inspection systems in the field of laser and joining technologies cooperates with EOS, the technology and market leader for the DMLS technology, and with selected industrial partners to develop a diode based in‐process monitoring system.

A Strategy for Logistic Quality Control in Micro Bulk Production

A continuous trend to function integration, miniaturization and densification opens new opportunities in industry and research. To manufacture micro products, tools, materials and technologies have to be scaled down from the macro to the micro domain. Thereby, a downscaling of classical processes leads to unexpected process behavior, so called size effects. Additionally, new challenges arise for in-process quality inspection based on the dimension of the micro products which requires microscopic solutions for reliable quality control. To handle these challenges in mass production, new strategies for the planning of logistic processes with a focus on logistic quality parameters are necessary. This contribution introduces a closed-loop quality control strategy for bulk production in micro cold forming. A discrete event simulation model incorporating characteristics of optical quality inspection and general process parameters allows the quantification of the system's performance.

Laser ultrasonic propagation imaging method in the frequency domain based on wavelet transformation

A wavelet-transformed ultrasonic propagation imaging method capable of ultrasonic propagation imaging in the frequency domain was developed and applied as a new structural damage or flaw visualization algorithm. Since the wavelet-transformed ultrasonic propagation imaging method has strong frequency selectivity, it can visualize the propagation of ultrasonic waves of a specific frequency (for example, to isolate ultrasonic mode of interest and a damage-related ultrasonic wave). The strong frequency selectivity of the wavelet-transformed ultrasonic propagation imaging method was demonstrated, isolating only the zeroth-order asymmetrical mode of the fundamental Lamb wave modes in an anisotropic carbon fiber-reinforced plastic plate with a thickness of 5 mm. The wavelet-transformed ultrasonic propagation imaging method can also convert a complex time domain multiple wavefield into a simple frequency domain single wavefield. This feature enables easy interpretation of the results, and facilitates the precise evaluation of the location and size of structural damage or flaws. We demonstrated this capability by detecting a disbond in a sandwich structure made of Al-alloy skins and a foam core. A disbond with a diameter of 20 mm, which is representative of a common manufacturing flaw, was successfully detected, localized, and evaluated. Since a method to determine the allowable maximum pulse repetition frequency depending on target materials and structures was found by investigating the residual wave caused from the previous laser impinging, our laser ultrasonic system can scan rapidly the target with an optimal pulse repetition rate. In addition, the proposed wavelet-transformed ultrasonic propagation imaging method can visualize damage or flaw without the need for reference data from the intact state of the structure. Hence, we propose the wavelet-transformed ultrasonic propagation imaging approach for automatic inspection of in-service engineering structures, or in-process quality inspection in manufacturing.