Applied Sciences

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17 pages, 7126 KiB

Open AccessArticle

Enhancing Vibration Analysis in Hydraulic Presses: A Case Study Evaluation

by Daniel Jancarczyk, Ireneusz Wróbel, Piotr Danielczyk and Marcin Sidzina

Appl. Sci. 2024, 14(7), 3097; https://0-doi-org.brum.beds.ac.uk/10.3390/app14073097 - 07 Apr 2024

Viewed by 499

Vibration monitoring is essential for maintaining the optimal performance and reliability of industrial machinery, which experiences dynamic forces and vibrations during operation. This study delved into a comprehensive analysis of vibration monitoring in hydraulic presses, utilizing advanced measurement systems equipped with accelerometers. The [...] Read more.

Vibration monitoring is essential for maintaining the optimal performance and reliability of industrial machinery, which experiences dynamic forces and vibrations during operation. This study delved into a comprehensive analysis of vibration monitoring in hydraulic presses, utilizing advanced measurement systems equipped with accelerometers. The proposed system included a three-axis accelerometer, data acquisition unit, and dedicated measurement software, facilitating the precise monitoring and analysis of vibrations. The influence of the sensor placement and sampling frequency on the measurement results was examined. A time and frequency analysis of the recorded measurements was performed. The results demonstrated the correlation between vibration levels and various production parameters, such as the number of parts simultaneously produced and press pressure. These findings underscore the potential for vibration measurement as a pivotal component in controlling production parameter settings. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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17 pages, 609 KiB

Open AccessArticle

Towards Hyper-Relevance in Marketing: Development of a Hybrid Cold-Start Recommender System

by Leonor Fernandes, Vera Miguéis, Ivo Pereira and Eduardo e Oliveira

Appl. Sci. 2023, 13(23), 12749; https://0-doi-org.brum.beds.ac.uk/10.3390/app132312749 - 28 Nov 2023

Viewed by 669

Abstract

Recommender systems position themselves as powerful tools in the support of relevance and personalization, presenting remarkable potential in the area of marketing. The cold-start customer problematic presents a challenge within this topic, leading to the need of distinguishing user features and preferences based [...] Read more.

Recommender systems position themselves as powerful tools in the support of relevance and personalization, presenting remarkable potential in the area of marketing. The cold-start customer problematic presents a challenge within this topic, leading to the need of distinguishing user features and preferences based on a restricted set of transactional information. This paper proposes a hybrid recommender system that aims to leverage transactional and portfolio information as indicating characteristics of customer behaviour. Four independent systems are combined through a parallelised weighted hybrid design. The first individual system utilises the price, target age, and brand of each product to develop a content-based recommender system, identifying item similarities. Secondly, a keyword-based content system uses product titles and descriptions to identify related groups of items. The third system utilises transactional data, defining similarity between products based on purchasing patterns, categorised as a collaborative model. The fourth system distinguishes itself from the previous approaches by leveraging association rules, using transactional information to establish antecedent and precedence relationships between items through a market basket analysis. Two datasets were analysed: product portfolio and transactional datasets. The product portfolio had 17,118 unique products and the included 4,408,825 instances from 2 June 2021 until 2 June 2022. Although the collaborative system demonstrated the best evaluation metrics when comparing all systems individually, the hybridisation of the four systems surpassed each of the individual systems in performance, with a 8.9% hit rate, 6.6% portfolio coverage, and with closer targeting of customer preferences and smaller bias. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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22 pages, 446 KiB

Open AccessArticle

Evaluating the Effectiveness of Designs for Low-Cost Digital Manufacturing Systems

by Jan Kaiser, Gregory Hawkridge, Anandarup Mukherjee and Duncan McFarlane

Appl. Sci. 2023, 13(23), 12618; https://0-doi-org.brum.beds.ac.uk/10.3390/app132312618 - 23 Nov 2023

Cited by 1 | Viewed by 774

Abstract

There are many well-known systematic approaches to design the digital systems used in manufacturing. However, there are only a few approaches that specifically deal with low-cost components. Such components may not provide the same level of completeness as more expensive industrial alternatives and [...] Read more.

There are many well-known systematic approaches to design the digital systems used in manufacturing. However, there are only a few approaches that specifically deal with low-cost components. Such components may not provide the same level of completeness as more expensive industrial alternatives and may need to be combined with other components to become comparable. Consequently, common design challenges for systems comprising such low-cost components revolve around extendability and interface standardisation. There is a need for analysing the capability of the existing approaches to design these systems. This study aims to evaluate the effectiveness of designs for low-cost digital manufacturing systems that have been derived from a particular design approach. The proposed evaluation methodology is used for the special case of designs that are directly based on reference architectures and for the development of specific metrics for that purpose. To quantify the effectiveness, these metrics are applied to a number of design scenarios. Although focusing on reference-architecture-based designs, the proposed methodology can also be used for other design approaches. The evaluation and structured implementation comparison helps practitioners in selecting an effective design approach to low-cost digital manufacturing systems and provides insights into how a particular design approach can become more effective. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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10 pages, 514 KiB

Open AccessArticle

Perspectives on Digital Transformation Initiatives in the Mechanical Engineering Industry

by Andrej Miklosik and Alexander Bernhard Krah

Appl. Sci. 2023, 13(22), 12386; https://0-doi-org.brum.beds.ac.uk/10.3390/app132212386 - 16 Nov 2023

Viewed by 854

Abstract

Companies from the mechanical engineering industry are eager to embrace new technologies in their pursuit of a competitive advantage. However, the complete digitalization of the sector encounters limitations, as certain aspects necessitate human supervision or manual labor. This is where the concepts of [...] Read more.

Companies from the mechanical engineering industry are eager to embrace new technologies in their pursuit of a competitive advantage. However, the complete digitalization of the sector encounters limitations, as certain aspects necessitate human supervision or manual labor. This is where the concepts of Industry 4.0, Industry 5.0, and digital transformation become relevant. The aim of the research presented in this paper was to gather and extract valuable insights and lessons from the experiences of German companies in the plastic extrusion machinery sector with digital transformation (DT). Qualitative interpretative research was used, using in-depth expert interviews with C-level executives. We organized the findings into three categories: (i) DT communication initiatives, including the elimination of paper, CRM solutions, messenger services, home office, and online procurement platforms; (ii) departments and areas most involved, including accounting and procurement, sales and production, and construction; and (iii) cost–benefit perception, including positive assessment, long-term impacts, and variation from company to company. The results provide valuable insights into the progress of DT initiatives in companies operating in the pipe extrusion sector in Germany. Additionally, several DT misconceptions were identified, thereby enriching the DT misconceptions framework that has been intensely discussed in the DT literature. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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24 pages, 13418 KiB

Open AccessArticle

DAMP-YOLO: A Lightweight Network Based on Deformable Features and Aggregation for Meter Reading Recognition

by Sichao Zhuo, Xiaoming Zhang, Ziyi Chen, Wei Wei, Fang Wang, Quanlong Li and Yufan Guan

Appl. Sci. 2023, 13(20), 11493; https://0-doi-org.brum.beds.ac.uk/10.3390/app132011493 - 20 Oct 2023

Cited by 2 | Viewed by 2501

Abstract

With the development of Industry 4.0, although some smart meters have appeared on the market, traditional mechanical meters are still widely used due to their long-standing presence and the difficulty of modifying or replacing them in large quantities. Most meter readings are still [...] Read more.

With the development of Industry 4.0, although some smart meters have appeared on the market, traditional mechanical meters are still widely used due to their long-standing presence and the difficulty of modifying or replacing them in large quantities. Most meter readings are still manually taken on-site, and some are even taken in high-risk locations such as hazardous chemical storage. However, existing methods often fail to provide real-time detections or result in misreadings due to the complex nature of natural environments. Thus, we propose a lightweight network called DAMP-YOLO. It combines the deformable CSP bottleneck (DCB) module, aggregated triplet attention (ATA) mechanism, meter data augmentation (MDA), and network pruning (NP) with the YOLOv8 model. In the meter reading recognition dataset, the model parameters decreased by 30.64% while mAP50:95 rose from 87.92% to 88.82%, with a short inference time of 129.6 ms for the Jetson TX1 intelligent car. In the VOC dataset, our model demonstrated improved performance, with mAP50:95 increasing from 41.03% to 45.64%. The experimental results show that the proposed model is competitive for general object detection tasks and possesses exceptional feature extraction capabilities. Additionally, we have devised and implemented a pipeline on the Jetson TX1 intelligent vehicle, facilitating real-time meter reading recognition in situations where manual interventions are inconvenient and hazardous, thereby confirming its feasibility for practical applications. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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15 pages, 6583 KiB

Open AccessArticle

Application of Digital Engineering Methods in Order to Improve Processes in Heterogeneous Companies

by Jozef Trojan, Peter Trebuňa and Marek Mizerák

Appl. Sci. 2023, 13(13), 7681; https://0-doi-org.brum.beds.ac.uk/10.3390/app13137681 - 29 Jun 2023

Cited by 1 | Viewed by 715

Abstract

In the presented article, the initial phase is focused mainly on familiarization with the production focus of individual enterprises and their financial security, which provides a basis for the proposal of possible solutions to shortcomings. A more detailed study of production through simulation [...] Read more.

In the presented article, the initial phase is focused mainly on familiarization with the production focus of individual enterprises and their financial security, which provides a basis for the proposal of possible solutions to shortcomings. A more detailed study of production through simulation studies using Process Simulate software provides a more comprehensive view of production in the assessed enterprises, where the current course of production at workplaces is evaluated in detail, and suggestions are then offered to improve the revealed shortcomings. In the end, there is an assessment of the companies from the point of view of homogeneity, so that it is then possible to make an inter-industry comparison of the revealed errors and shortcomings, with the result of finding common recommendations for a wide industrial spectrum. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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32 pages, 1083 KiB

Open AccessArticle

Autonomous Navigation of Robots: Optimization with DQN

by Juan Escobar-Naranjo, Gustavo Caiza, Paulina Ayala, Edisson Jordan, Carlos A. Garcia and Marcelo V. Garcia

Appl. Sci. 2023, 13(12), 7202; https://0-doi-org.brum.beds.ac.uk/10.3390/app13127202 - 16 Jun 2023

Cited by 4 | Viewed by 3144

Abstract

In the field of artificial intelligence, control systems for mobile robots have undergone significant advancements, particularly within the realm of autonomous learning. However, previous studies have primarily focused on predefined paths, neglecting real-time obstacle avoidance and trajectory reconfiguration. This research introduces a novel [...] Read more.

In the field of artificial intelligence, control systems for mobile robots have undergone significant advancements, particularly within the realm of autonomous learning. However, previous studies have primarily focused on predefined paths, neglecting real-time obstacle avoidance and trajectory reconfiguration. This research introduces a novel algorithm that integrates reinforcement learning with the Deep Q-Network (DQN) to empower an agent with the ability to execute actions, gather information from a simulated environment in Gazebo, and maximize rewards. Through a series of carefully designed experiments, the algorithm’s parameters were meticulously configured, and its performance was rigorously validated. Unlike conventional navigation systems, our approach embraces the exploration of the environment, facilitating effective trajectory planning based on acquired knowledge. By leveraging randomized training conditions within a simulated environment, the DQN network exhibits superior capabilities in computing complex functions compared to traditional methods. This breakthrough underscores the potential of our algorithm to significantly enhance the autonomous learning capacities of mobile robots. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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18 pages, 884 KiB

Open AccessArticle

Overlap in Automatic Root Cause Analysis in Manufacturing: An Information Theory-Based Approach

by Eduardo e Oliveira, Vera L. Miguéis and José L. Borges

Appl. Sci. 2023, 13(6), 3416; https://0-doi-org.brum.beds.ac.uk/10.3390/app13063416 - 08 Mar 2023

Cited by 3 | Viewed by 1450

Abstract

Automatic Root Cause Analysis solutions aid analysts in finding problems’ root causes by using automatic data analysis. When trying to locate the root cause of a problem in a manufacturing process, an issue-denominated overlap can occur. Overlap can impede automated diagnosis using algorithms, [...] Read more.

Automatic Root Cause Analysis solutions aid analysts in finding problems’ root causes by using automatic data analysis. When trying to locate the root cause of a problem in a manufacturing process, an issue-denominated overlap can occur. Overlap can impede automated diagnosis using algorithms, as the data make it impossible to discern the influence of each machine on the quality of products. This paper proposes a new measure of overlap based on an information theory concept called Positive Mutual Information. This new measure allows for a more detailed analysis. A new approach is developed for automatically finding the root causes of problems when overlap occurs. A visualization that depicts overlapped locations is also proposed to ease practitioners’ analysis. The proposed solution is validated in simulated and real case-study data. Compared to previous solutions, the proposed approach improves the capacity to pinpoint a problem’s root causes. Full article

(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)

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