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4 pages, 3360 KiB

Open AccessProceeding Paper

Investigating the Impact of Declination Angle on the Side Milling Process of Additively Manufactured Ti6Al4V Using a 3D Milling Finite Element Model

by Surinder Pal, Xavier Velay and Waqas Saleem

Eng. Proc. 2024, 65(1), 1; https://doi.org/10.3390/engproc2024065001 - 27 Feb 2024

Viewed by 327

Abstract

This study investigates the impact of declination angles (at 5, 10, and 15°) on the side milling process of additively manufactured Ti6Al4V. The finite element modelling (FEM) simulations are conducted using the Abaqus software and the Johnson–Cook (J-C) model. The main focus is [...] Read more.

This study investigates the impact of declination angles (at 5, 10, and 15°) on the side milling process of additively manufactured Ti6Al4V. The finite element modelling (FEM) simulations are conducted using the Abaqus software and the Johnson–Cook (J-C) model. The main focus is on characterizing the relationship between the declination angles and the cutting forces. The findings demonstrate the significant effects of the declination angle, with noticeable variations observed in the milling forces. By employing the 3D milling finite element model of Abaqus, accurate analyses and predictions of the machining process dynamics are achieved. The insights gained from this research are valuable for optimizing machining parameters and enhancing efficiency, as well as for improving the surface quality of milled additively manufactured Ti6Al4V components. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 550 KiB

Open AccessProceeding Paper

Development of an Automated Downtime System for Small and Medium sized Enterprises

by Alastair Long, Andrew Johnston and Danielle Soban

Eng. Proc. 2024, 65(1), 2; https://doi.org/10.3390/engproc2024065002 - 27 Feb 2024

Viewed by 270

Abstract

The implementation of Industry 4.0 can be a challenge for SMEs as often the existing equipment cannot be simply replaced or data cannot be easily extracted from existing equipment. A system that automatically records downtime with minimal operator interaction can be beneficial by [...] Read more.

The implementation of Industry 4.0 can be a challenge for SMEs as often the existing equipment cannot be simply replaced or data cannot be easily extracted from existing equipment. A system that automatically records downtime with minimal operator interaction can be beneficial by giving a clear picture of how a manufacturing process is running, along with providing information on duration, frequency and reasons for stoppages. When this information is available, further analysis can be performed to identify the main reasons for downtime and identify which sections of the production line are more prone to stopping; therefore, corrective actions can be put in place to reduce this. Off-the-shelf IoT equipment was used to develop this system, which reads the status from the signal towers of the line. These data were recorded in an SQL database and an interactive user interface was developed so that downtime codes could be assigned to stoppages and downtime data could be presented in different ways. This case study has shown that a small investment in IoT can make a huge improvement on the ability to monitor and analyse the downtime of a machining line for an SME. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 574 KiB

Open AccessProceeding Paper

A Review of the Image Classification Models Used for the Prediction of Bed Defects in the Selective Laser Sintering Process

by Matthew Colville, Emmett Kerr and Sagar Nikam

Eng. Proc. 2024, 65(1), 3; https://doi.org/10.3390/engproc2024065003 - 27 Feb 2024

Viewed by 256

Abstract

Defects formed during the spreading of powder, known as powder bed defects, are a major issue in additive manufacturing processes. Deep learning (DL)-based image classification models can be utilised to detect defects caused by the powder spreading process. The aim of this research [...] Read more.

Defects formed during the spreading of powder, known as powder bed defects, are a major issue in additive manufacturing processes. Deep learning (DL)-based image classification models can be utilised to detect defects caused by the powder spreading process. The aim of this research was to review and compare the performance of the EfficientNet_v2 deep learning image classification model against the commonly used VGG-16 model on a selective laser sintering powder bed defects (SLS PBDs) dataset. It was observed that the EfficientNet_v2 model achieved higher performance than the commonly used VGG-16 model, with a defect prediction accuracy of 97.54% and model sensitivity of 96.3%. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 581 KiB

Open AccessProceeding Paper

Demystifying the Electrocardiogram—A Printed Circuit Board for Use in a Biomedical Electronics Laboratory

by Pádraig Herbert

Eng. Proc. 2024, 65(1), 4; https://doi.org/10.3390/engproc2024065004 - 27 Feb 2024

Viewed by 225

Abstract

The electrocardiogram is a widely used clinical diagnostic tool and is studied in biomedical engineering and electrophysiology courses. Modern electrocardiograms are complex, requiring some knowledge in many domains of engineering to comprehend their operation. This project develops an ECG laboratory for learners enrolled [...] Read more.

The electrocardiogram is a widely used clinical diagnostic tool and is studied in biomedical engineering and electrophysiology courses. Modern electrocardiograms are complex, requiring some knowledge in many domains of engineering to comprehend their operation. This project develops an ECG laboratory for learners enrolled in biomedical electronics or biomedical instrumentation modules, who are exposed to a steep learning curve in electronics, intended to allow learners to uncover the fundamental processes of data capture, analysis, and presentation. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 688 KiB

Open AccessProceeding Paper

Smart Manufacturing in Timber Production

by Anup Kumar, Emmett Kerr and Wesley McKnight

Eng. Proc. 2024, 65(1), 5; https://doi.org/10.3390/engproc2024065005 - 27 Feb 2024

Viewed by 234

Abstract

Traditional manufacturing units face a lot of challenges in coping with growing demand. With the more demand, maintaining the quality of the product is another challenge. Industry 4.0 can be utilized to meet the growing demand without sacrificing the quality of the product. [...] Read more.

Traditional manufacturing units face a lot of challenges in coping with growing demand. With the more demand, maintaining the quality of the product is another challenge. Industry 4.0 can be utilized to meet the growing demand without sacrificing the quality of the product. The aim of this research is to analyse the improvement in production capabilities when implementing smart manufacturing. Woodford Timber Products has streamlined its production processes and increased its operational efficiency by embracing innovative technology and techniques. The digitisation of manufacturing processes through sophisticated software is capable of designing, rendering, analysing, and converting to machine language for multi axis CNC machines. The organisation derives significant insights from enormous volumes of data using product data management optimising manufacturing schedules, minimising waste, and improving product quality. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 784 KiB

Open AccessProceeding Paper

Visual Analytics Enabling Optimisation of Downtime

by Andrew Johnston, Danielle Soban and Alastair Long

Eng. Proc. 2024, 65(1), 6; https://doi.org/10.3390/engproc2024065006 - 27 Feb 2024

Viewed by 228

Abstract

Manufacturing is critical to the global economy and is a key sector of businesses in today’s world. The pressures of manufacturing mean that companies are often fighting to survive instead of investing in new technologies and factories in order to implement novel equipment [...] Read more.

Manufacturing is critical to the global economy and is a key sector of businesses in today’s world. The pressures of manufacturing mean that companies are often fighting to survive instead of investing in new technologies and factories in order to implement novel equipment that utilises industry 4.0 technology. This is particularly relevant for many SMEs who need solutions that can provide large benefits to their efficiency without requiring a large financial and/or time investment. The data that machinery produces is an often neglected vital resource that could hold the key to solving this problem, especially if this can be analysed in conjunction with production information. By using novel techniques, new discoveries that provide a wealth of knowledge and give a deeper understanding can be learnt. This allows for more informed decisions to be made and new hypotheses to be tested. This will lead to overall increases in process efficiency whilst still being cost and time effective. This paper will explore and propose examples of how visual analytics can be used to optimise manufacturing processes. The potential impact of analysing data, such as part quality, machine downtime and component life in conjunction, is discussed. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 1063 KiB

Open AccessProceeding Paper

Exploring the Mechanical Properties of the Gyroid Sheet Network for the Additive Manufacturing of Biomedical Structures: A Numerical Analysis Approach

by Babak Ziaie, Xavier Velay and Waqas Saleem

Eng. Proc. 2024, 65(1), 7; https://doi.org/10.3390/engproc2024065007 - 27 Feb 2024

Viewed by 252

Abstract

Using additive manufacturing (AM) techniques like SLM and EBM provides a valuable opportunity for manufacturing biomedical devices with precise porous structures that can mitigate adverse implant complications. Gyroid sheet network structures exhibit an excellent performance among porous structures due to their bioinspired morphology [...] Read more.

Using additive manufacturing (AM) techniques like SLM and EBM provides a valuable opportunity for manufacturing biomedical devices with precise porous structures that can mitigate adverse implant complications. Gyroid sheet network structures exhibit an excellent performance among porous structures due to their bioinspired morphology and mechanical properties. This study investigates the mechanical behavior of gyroid sheet networks with different morphological parameters suitable for biomedical implants. The results show that gyroid sheet networks with 1 to 2.5 mm unit cell sizes and porosities between 50% and 85% are ideal for biomedical implants. Additionally, porous implants made of gyroid sheet networks and mentioned morphologies can be produced using SLM with a layer thickness of 30 µm, spot size of 90 µm, and powder size of around 50 µm. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 879 KiB

Open AccessProceeding Paper

Computing the Orientation of Hardware Components from Images Using Traditional Computer Vision Methods

by Antonio Gambale, Emmett Kerr, Dermot Kerr and Sonya Coleman

Eng. Proc. 2024, 65(1), 8; https://doi.org/10.3390/engproc2024065008 - 01 Mar 2024

Viewed by 238

Abstract

This paper introduces a methodology for precise object orientation determination using principal component analysis, with robust performance under significant noise conditions. It validates the potential to mitigate the challenges associated with axis-aligned bounding boxes in smart manufacturing environments. The proposed approach paves the [...] Read more.

This paper introduces a methodology for precise object orientation determination using principal component analysis, with robust performance under significant noise conditions. It validates the potential to mitigate the challenges associated with axis-aligned bounding boxes in smart manufacturing environments. The proposed approach paves the way for improved alignment in robotic grasping tasks, positioning it as a computationally efficient alternative to ML methods employing oriented bounding boxes. the methodology demonstrated a maximum angle deviation of 3.5 degrees under severe noise conditions through testing with bolts in orientations of 0 to 180 degrees. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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3 pages, 169 KiB

Open AccessProceeding Paper

Analysis and Reconfiguration of the EM106-Project and Technical Drawing for the Purpose of Second-Level Gifted Education

by Jacob Baneham, Paul Young and Catriona Ledwith

Eng. Proc. 2024, 65(1), 9; https://doi.org/10.3390/engproc2024065009 - 01 Mar 2024

Viewed by 315

Abstract

Goldberg and Somerville write of the “missed revolutions” that have had a massive impact on industry but have failed to translate to universities. The literature shows how alternative approaches can modernise curricula and improve motivation and trust, such as student-led design of course [...] Read more.

Goldberg and Somerville write of the “missed revolutions” that have had a massive impact on industry but have failed to translate to universities. The literature shows how alternative approaches can modernise curricula and improve motivation and trust, such as student-led design of course content. Aligning what is taught to students to improve their experience rather than performance is a method discussed by Obada as constructive alignment. This paper outlines the potential challenges facing engineering education, including a lack of motivation and trust between students and educators and the lack of development of communication skills in graduates. This research aims to use the EM106-Project and Technical Drawing, an undergraduate module at DCU, as a framework by which to test novel curriculum design and pedagogical methods. A modified version of the module will be delivered to second-level students taking part in a dual enrolment programme, with first-year undergraduate engineers taking the standard version of the module. Their experiences will be compared to understand the impact that changes have on student’s views of engineering. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

4 pages, 1302 KiB

Open AccessProceeding Paper

Examining the Feasibility of Acoustic Resonance Testing (ART) for Quality Control in Manufacturing

by Niklas Braun, John Kennedy, Natalia Lishchenko and Garret E. O’Donnell

Eng. Proc. 2024, 65(1), 10; https://doi.org/10.3390/engproc2024065010 - 04 Mar 2024

Viewed by 266

Abstract

In the age of digitalization and Industry 4.0, the novel use of sensor technology is enabling much greater insight into manufacturing processes and presents new opportunities for more efficient process chains. For example, the use of sound measurement and low-cost microphones to infer [...] Read more.

In the age of digitalization and Industry 4.0, the novel use of sensor technology is enabling much greater insight into manufacturing processes and presents new opportunities for more efficient process chains. For example, the use of sound measurement and low-cost microphones to infer the quality/integrity of part quality can be more widely applied in production. Specifically, this paper investigates the suitability of Acoustic Resonance Testing (ART) for quality detection considering the detection of cracks/defects in metal plates and joints. A methodology involving a combination of finite element analysis (FEA) and experimental tests was developed and results demonstrate that ART has the potential for defect detection with modest- to low-cost measurement hardware. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 346 KiB

Open AccessProceeding Paper

You Can Engineer It: Engineering Outreach for Females Aged 4–12

by Aine McGreeghan

Eng. Proc. 2024, 65(1), 11; https://doi.org/10.3390/engproc2024065011 - 06 Mar 2024

Viewed by 192

Abstract

This document discusses a delivery method employed by South Eastern Regional College (SERC) to provide engineering outreach opportunities for young females, funded by the Institution of Engineering and Technology (IET). College students developed resources and assisted on the day, making the event more [...] Read more.

This document discusses a delivery method employed by South Eastern Regional College (SERC) to provide engineering outreach opportunities for young females, funded by the Institution of Engineering and Technology (IET). College students developed resources and assisted on the day, making the event more engaging for participants. Feedback from the event showed that parents and children gained a greater understanding of engineering and that there is a need for sustained engineering extra-curricular events in the local area. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 447 KiB

Open AccessProceeding Paper

ASL Fingerspelling Classification for Use in Robot Control

by Kevin McCready, Dermot Kerr, Sonya Coleman and Emmett Kerr

Eng. Proc. 2024, 65(1), 12; https://doi.org/10.3390/engproc2024065012 - 06 Mar 2024

Viewed by 224

Abstract

This paper proposes a gesture-based control system for industrial robots. To achieve that goal, the performance of an image classifier trained on three different American Sign Language (ASL) fingerspelling image datasets is considered. Then, the three are combined into a single larger dataset, [...] Read more.

This paper proposes a gesture-based control system for industrial robots. To achieve that goal, the performance of an image classifier trained on three different American Sign Language (ASL) fingerspelling image datasets is considered. Then, the three are combined into a single larger dataset, and the classifier is trained on that. The result of this process is then compared with the original three. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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5 pages, 5917 KiB

Open AccessProceeding Paper

Study on 3D Computer-Aided Feature Inspection for Product Design and Analysis

by Chengsi Lin, Muhamad Arfauz A. Rahman and Paul G. Maropoulos

Eng. Proc. 2024, 65(1), 13; https://doi.org/10.3390/engproc2024065013 - 11 Mar 2024

Viewed by 203

Abstract

The aim of this project is to verify the suitability of three-dimensional (3D) scanners with computer-aided systems as a new method of geometric feature inspection. Three-dimensional scanners are widely used for field recording and model reconstruction. However, at present, 3D scanning is rarely [...] Read more.

The aim of this project is to verify the suitability of three-dimensional (3D) scanners with computer-aided systems as a new method of geometric feature inspection. Three-dimensional scanners are widely used for field recording and model reconstruction. However, at present, 3D scanning is rarely used in the field of inspection in the production process. This paper uses the Artec Leo 3D scanner as the basic equipment, randomly selects three different shapes of products for scanning, and then uses computer-aided software to optimize and feature the model. The analysis of the characteristics of the measurement data shows that the scanner has the potential to be used as an inspection tool in industrial production processes. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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4 pages, 847 KiB

Open AccessProceeding Paper

Additive Manufacturing Powder Particle Size Distributions: Comparison of Histogram Binning Methods

by Courtney Gallagher, Emmett Kerr and Shaun McFadden

Eng. Proc. 2024, 65(1), 14; https://doi.org/10.3390/engproc2024065014 - 25 Mar 2024

Viewed by 241

Abstract

Additive manufacturing powders require a well-defined particle size distribution (PSD) and spherical morphology to ensure good flowability. To simplify characterisation, powders can be prepared using standard metallurgical techniques followed by optical imaging of the cross-sectioned particles. Measured PSDs of particle sections are typically [...] Read more.

Additive manufacturing powders require a well-defined particle size distribution (PSD) and spherical morphology to ensure good flowability. To simplify characterisation, powders can be prepared using standard metallurgical techniques followed by optical imaging of the cross-sectioned particles. Measured PSDs of particle sections are typically underestimates of the true PSD; hence, stereological corrections are required. Variations arise in the histogram binning methods (central binning versus upper limit binning) of commonly used stereological corrections. Although the results show some sensitivity to the binning method used, the GCO method seemed reasonably robust to changes in the binning method. However, authors are encouraged to follow the method as it is intended within the literature, which was found to be especially true when using Saltykov’s method. Full article

(This article belongs to the Proceedings of The 39th International Manufacturing Conference)

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