InsightPub Date : 2023-10-01DOI: 10.1784/insi.2023.65.10.541
M Blankschän, D Kanzler, R Liebich
{"title":"Approaches to assess reliability in visual inspection","authors":"M Blankschän, D Kanzler, R Liebich","doi":"10.1784/insi.2023.65.10.541","DOIUrl":"https://doi.org/10.1784/insi.2023.65.10.541","url":null,"abstract":"Non-destructive testing (NDT) plays an important role in quality assurance and ensuring reliable ongoing operations in many industries. Thus, the importance of reliability assessment of inspection results is increasing. Current standards and regulations provide several approaches for this purpose. For example, DIN EN ISO/IEC 17025:2018-03 provides general requirements to determine measurement uncertainty. In contrast, method-related standards such as DIN ISO 19828:2021-03 specify detailed requirements for visual inspection (VT), considering environmental conditions and other factors (for example experience of the inspection personnel). In contrast, VDA Volume 5 defines visual inspection as an attributive method, making measurement uncertainty determinations unnecessary. Instead, the reliability of the inspection process is evaluated by proficiency tests. This paper examines approaches of regulations, based on previous experiments, for their applicability and suitability for considering the reliability of visual inspections. It is shown that individual measurement values (for example illuminance) are not suitable for this purpose. Furthermore, it is shown that human factors (HFs) (for example training or experience of the inspector), considered in isolation, are also not sufficiently suitable. Hence, the combination of the qualification of inspection methods, by means of proficiency tests on reference objects, and the application of Cohen's kappa for evaluating human factors appeared to be more suitable for the investigated issue.","PeriodicalId":13956,"journal":{"name":"Insight","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-10-01DOI: 10.1784/insi.2023.65.10.559
Zhiwu Shang, Hu Liu, Baoren Zhang, Zehua Feng, Wanxiang Li
{"title":"Multi-view feature fusion fault diagnosis method based on an improved temporal convolutional network","authors":"Zhiwu Shang, Hu Liu, Baoren Zhang, Zehua Feng, Wanxiang Li","doi":"10.1784/insi.2023.65.10.559","DOIUrl":"https://doi.org/10.1784/insi.2023.65.10.559","url":null,"abstract":"This paper addresses the problem of fault identification in rotating machinery by analysing vibration data using a neural network approach. Temporal convolutional networks (TCNs) have attracted a lot of focus in the domain of fault identification; however, TCN convolution kernels are small and susceptible to high-frequency noise interference. Furthermore, the default weight coefficient of the internal residual connection is 1. When there are few residual blocks, the residual block characteristic extraction ability is suppressed and only the vibration signal collected at a single location is utilised for fault diagnosis as it contains incomprehensive fault information. To tackle the above issues, this paper proposes a multi-view feature fusion fault diagnosis algorithm with an adaptive residual coefficient assignment TCN with wide first-layer kernels (WD-ARCATCN). Firstly, a WD-ARCATCN feature extraction network is designed to extract deep state features from different views and the first layer of the TCN is set as a wide-kernel (WD) convolutional layer to suppress high-frequency noise. An adaptive residual coefficient assignment (ARCA) unit is designed in the residual connection to increase the characteristic learning capability of the residual blocks and the residual blocks with ARCA units are stacked to further extract multi-view deep fault features. In this paper, acceleration signals collected at different positions are used as the multi-view feature source for the first time and the fault information contained is more comprehensive. Then, based on a self-attention mechanism, the multi-view feature fusion method is improved and the view weights are adaptively assigned to effectively fuse different view characteristics and enhance the identification of the fault characteristics. Finally, the mapping between the multi-view fusion features and the labels is achieved using a softmax classifier. The algorithm has been tested using experimental data from the bearing vibration database at Case Western Reserve University (CWRU) and it performed much better compared to other diagnostic algorithms.","PeriodicalId":13956,"journal":{"name":"Insight","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135708229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-10-01DOI: 10.1784/insi.2023.65.10.545
K Mohamed Bak, K Kalaichelvan, M Abdur Rahman, S Haque, S Shaul Hameed, A S Selvakumar
{"title":"Analysis of acoustic emission testing on the adherent layer thickness of lap joints under tensile loading","authors":"K Mohamed Bak, K Kalaichelvan, M Abdur Rahman, S Haque, S Shaul Hameed, A S Selvakumar","doi":"10.1784/insi.2023.65.10.545","DOIUrl":"https://doi.org/10.1784/insi.2023.65.10.545","url":null,"abstract":"This paper aims to investigate the bonding strength of lap joints under tensile loading by altering the thickness of the adherent layer. The results show that increasing the adherent layer thickness of the bonded lap joint reduced stress concentration, indicating a higher stress transmission between the overlapping regions. Acoustic emission (AE) signals were used to identify the different failure modes and their frequency ranges by subjecting the AE signals to parametric analysis, fast Fourier transform (FFT) analysis, continuous wavelet transform (CWT) analysis and discrete wavelet transform (DWT) analysis. FFT analysis identified the frequency ranges of adhesive failure, fibre tear failure and mixed failure. At the same time, DWT was more effective at identifying the frequency ranges of the failure modes associated with varying adherent layer thicknesses in lap joints. Adhesive failure was characterised by low amplitudes, low frequency ranges and low energy levels. In contrast, delamination displayed moderate amplitudes, moderate frequency ranges and medium energy levels. High amplitudes, high frequency ranges, high energy levels and strong signal strength indicated mixed failures.","PeriodicalId":13956,"journal":{"name":"Insight","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135708175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-10-01DOI: 10.1784/insi.2023.65.10.551
Xianghong Wang, Zezhong He, Jun Liu, Xiaoqiang Xu, Hongwei Hu
{"title":"Binocular vision vibration measurement based on pixel coordinate matching of inner corner points in a chequerboard","authors":"Xianghong Wang, Zezhong He, Jun Liu, Xiaoqiang Xu, Hongwei Hu","doi":"10.1784/insi.2023.65.10.551","DOIUrl":"https://doi.org/10.1784/insi.2023.65.10.551","url":null,"abstract":"A binocular vision measurement system provides a simple method for obtaining three-dimensional vibration data from moving objects, which is suitable for vibration monitoring of large structures such as bridges. Aiming to address the problem that the feature selection process for binocular visual inspection affects the measurement accuracy, chequerboard feature points are selected in this paper for carrying out a visual displacement measurement method. Firstly, pixel coordinate matching of the inner corner points in the chequerboard is completed and then a binocular vision measurement system is established. The measurement results are compared with using circular feature points. Secondly, the binocular vision measurement model is applied to the vibration measurement of a cantilever beam. Using comparisons with a three-axis acceleration sensor, the effectiveness and accuracy of this method are evaluated. Finally, the method is applied to measure the vibration of the cantilever beam under different load conditions and its vibration characteristics are analysed. The results show that the accuracy of the binocular vision measurement method based on pixel coordinate matching of the inner corner points in the chequerboard is higher than that using circular feature points. From comparisons with the acceleration sensor, the measurement error of this method is found to be small. In addition, the method can effectively analyse the vibration performance of a cantilever beam under different load conditions. Therefore, this measurement method is effective and provides a theoretical basis for the identification of vibration characteristics in large engineering structures.","PeriodicalId":13956,"journal":{"name":"Insight","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135708226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-10-01DOI: 10.1784/insi.2023.65.10.570
J Susai Mary, M A Sai Balaji, D Dinakaran
{"title":"Hybrid adaptive control of CNC drilling for enhancement of tool life and surface quality","authors":"J Susai Mary, M A Sai Balaji, D Dinakaran","doi":"10.1784/insi.2023.65.10.570","DOIUrl":"https://doi.org/10.1784/insi.2023.65.10.570","url":null,"abstract":"Intelligent machining requires the online adaptation of the machining parameters to improve tool life and product quality and to reduce machining costs. This article presents a novel hybrid adaptive control (HAC) system for a drilling process. The HAC system is a combination of two adaptive controls: geometric adaptive control (GAC) and adaptive control by optimisation (ACO). It keeps the roughness of the holes within tolerance without compromising tool life. A response surface model (RSM) is used for modelling the drill wear and surface roughness with speed, feed, acceleration and force signals as inputs. The model predicts the wear and roughness with prediction accuracies of 97.1% and 93.6%, respectively. The roughness control is achieved through a Massachusetts Institute of Technology rule and tool wear is minimised by genetic algorithm optimisation. The adaptive algorithms are simulated and validated for the machining conditions given by the adaptive algorithms. The results show an improved tool life of 7% and surface roughness of 11%.","PeriodicalId":13956,"journal":{"name":"Insight","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-09-27DOI: 10.1002/inst.12453
Jaime Sly, David Crowne
{"title":"Systems Engineering in Technology Development","authors":"Jaime Sly, David Crowne","doi":"10.1002/inst.12453","DOIUrl":"https://doi.org/10.1002/inst.12453","url":null,"abstract":"<div>\u0000 \u0000 <p>Technology development is the crucial first step in designing new products and systems. It is a unique phase of product development in that it incorporates both scientific exploration and reduction to an engineered result. Too often, systems thinking and systems engineering principles aren't applied at this stage, leading to technologies that solve the wrong problems, inability to progress to higher maturity levels, and unworkable implementation architectures. In practice, this means higher development costs, extended timelines, and failed technology development projects. This article presents a framework for and provides guidance on systems engineering activities that add value and improve outcomes if applied during early stages of product development.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"26 3","pages":"26-32"},"PeriodicalIF":1.1,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-09-27DOI: 10.1002/inst.12451
Michael DiMario PhD, Ann Hodges
{"title":"Systems Engineering Management in Research and Development Valley of Death","authors":"Michael DiMario PhD, Ann Hodges","doi":"10.1002/inst.12451","DOIUrl":"https://doi.org/10.1002/inst.12451","url":null,"abstract":"<div>\u0000 \u0000 <p>A failure of a great many early research and development programs is the result of encountering the traditional valley of death that shadows early research and technology development. The elements that create the valley of death leads to research and technology development high risk and poor return on investment for a great many research and development organizations. This leads eventually to avoiding research and technology development all together because the organizations cannot viably manage the outcome of their early-stage research and development (ESR&D) efforts. Unfortunately, there are few established frameworks and processes for enabling smooth transitions to avoid failure and manage risk across fundamental research, applied research, development, and productization. Many leaders, program managers, and scientists are unwilling to involve systems engineering because of the perception that systems engineering is heavily process oriented, adds unnecessary costs, and should be applied only to mature technologies. The value of systems engineering as applied to ESR&D is unclear to these key individuals. The unfortunate result is that systems engineering is not applied to ESR&D. This article discusses the potential of application of systems engineering to ESR&D to improve return on investment and decrease risk.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"26 3","pages":"8-14"},"PeriodicalIF":1.1,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InsightPub Date : 2023-09-27DOI: 10.1002/inst.12456
Arno Granados, Celia Tseng
{"title":"Digital Engineering Enablers for Systems Engineering in Early-Stage Research and Development","authors":"Arno Granados, Celia Tseng","doi":"10.1002/inst.12456","DOIUrl":"https://doi.org/10.1002/inst.12456","url":null,"abstract":"<div>\u0000 \u0000 <p>Robust systems engineering is perceived as an unnecessary cost and schedule burden when the goal is proof of concept in an early-stage project (TRL 1-5). In reality the majority of industry, as opposed to academic, early-stage research and development (ESR&D) efforts are generally not “pure research”, but instead focus on technology development for the purpose of technology transition to applied development and technology insertion into new or existing products. To overcome the barriers, an early and active end-user focused system engineering approach is needed to build the use cases to support the transition from fundamental research to applied development. Digital engineering (DE) enablers can lower the transition investment cost through the use of agile methodologies, reference architectures, and model-based design and manufacturing capabilities. End-to-end digital continuity from ESR&D to manufacturing and sustainment facilitates early discoveries of transition risks, which enable informed decision-making to mitigate pitfalls leading to the “valley of death.”</p>\u0000 <p>This article leverages efforts associated with Industry 4.0, digital engineering transformation and INCOSE working group efforts to illustrate how a systems engineering approach based on DE concepts facilitates rapid instantiation of key systems engineering process and elements in ESR&D projects. This approach is both enabling to foundational ESR&D efforts, and transformational in building a bridge across the valley of death to foster success in technology transition to product. An agnostic tool, standards-based framework is presented, and specific tools are used to illustrate ESR&D transformation.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"26 3","pages":"47-55"},"PeriodicalIF":1.1,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}