Applied Sciences

Research

19 pages, 4122 KiB

Open AccessArticle

Poka Yoke in Smart Production Systems with Pick-to-Light Implementation to Increase Efficiency

by Justyna Trojanowska, Jozef Husár, Stella Hrehova and Lucia Knapčíková

Appl. Sci. 2023, 13(21), 11715; https://doi.org/10.3390/app132111715 - 26 Oct 2023

Cited by 7 | Viewed by 5939

Product assembly is often the last step in the manufacturing process. This task is usually performed by an assembly worker who needs to have practical experience and expertise. For complex products, the assembly may require a long time to study assembly plans. This [...] Read more.

Product assembly is often the last step in the manufacturing process. This task is usually performed by an assembly worker who needs to have practical experience and expertise. For complex products, the assembly may require a long time to study assembly plans. This paper presents a custom-designed Pick-to-Light system using Poka Yoke principles to make this activity easier. The created modular system with two-stage verification serves to guide the assembler precisely. It shows him on the display which parts he should use in a strictly defined assembly step. Our proposal aims to shorten assembly time and reduce the number of errors, which was supported by a case study in a small company with 30 employees. After analysing the data, we can declare that the proposed system significantly reduces the time required for assembly from 7 to 35% and reduces the error rate by 35%. The solution is scalable and flexible, as it can be easily adapted to display assembly steps for a different product. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

17 pages, 7700 KiB

Open AccessArticle

Cyberphysical System Modeled with Complex Networks and Hybrid Automata to Diagnose Multiple and Concurrent Faults in Manufacturing Systems

by Alejandro Velazquez, Fernando Martell, Irma Y. Sanchez and Carlos A. Paredes

Appl. Sci. 2023, 13(19), 10603; https://doi.org/10.3390/app131910603 - 22 Sep 2023

Cited by 2 | Viewed by 1483

Abstract

Cyber–physical systems use digital twins to provide advanced monitoring and control functions, including self-diagnosis. The digital twin is often conceptualized as a 3D model, but mathematical models implemented in numerical simulations are required to reproduce the dynamical and functional characteristics of physical systems. [...] Read more.

Cyber–physical systems use digital twins to provide advanced monitoring and control functions, including self-diagnosis. The digital twin is often conceptualized as a 3D model, but mathematical models implemented in numerical simulations are required to reproduce the dynamical and functional characteristics of physical systems. In this work, a cyber–physical system scheme is proposed to monitor and diagnose failures. The virtual system, embedded at the supervisory control level, combines concepts from complex networks and hybrid automata to detect failures in the hardware components and in the execution of the sequential logic control. An automated storage and retrieval system is presented as a case study to show the applicability of the proposed scheme. The functional test and the obtained results validate the implemented system that is shown to be capable of fault diagnosis and location in real time. The online execution of the digital twin present several advantages for diagnosing multiple concurrent failures in sensors, actuators, and the control unit. This approach can be incorporate into diverse manufacturing systems. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

16 pages, 8563 KiB

Open AccessArticle

Development and Verification of a Simulation Model of an Automated Assembly Line

by Karolina Bendowska and Przemysław Zawadzki

Appl. Sci. 2023, 13(18), 10142; https://doi.org/10.3390/app131810142 - 8 Sep 2023

Cited by 7 | Viewed by 1572

Abstract

Simulation models are integral to IT solutions built according to the Industry 4.0 concept. They are often the basis for developing digital twin solutions, which is why development environments are constantly developed and improved to meet the growing requirements of manufacturing enterprises. This [...] Read more.

Simulation models are integral to IT solutions built according to the Industry 4.0 concept. They are often the basis for developing digital twin solutions, which is why development environments are constantly developed and improved to meet the growing requirements of manufacturing enterprises. This work presents the development and verification of a simulation model of an automated assembly line located in the Smart Factory laboratory of the Poznań University of Technology. One of the criteria for designing the assembly process on this line is the time it takes for transport pallets to pass through individual stations. The work is a response to the need to quickly analyze the designed product assembly scenarios to choose the best one. The operation of the automated line with six assembly stations and allowing for the simultaneous transport of six pallets were considered. The main purpose of the work was to build a simulation model that would allow us to obtain assembly times close to real. The model was created using the Tecnomatix Plant Simulation 16.0 software, and verification work was carried out through a comparative analysis of the results of the simulation time of various assembly scenarios in relation to the actual operation of the line. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

23 pages, 2147 KiB

Open AccessFeature PaperArticle

A Two-Step Matheuristics for Order-Picking Process Problems with One-Directional Material Flow and Buffers

by Kateryna Czerniachowska, Radosław Wichniarek and Krzysztof Żywicki

Appl. Sci. 2023, 13(18), 10099; https://doi.org/10.3390/app131810099 - 7 Sep 2023

Cited by 1 | Viewed by 1136

Abstract

The necessity for undertaking this research is driven by the prevailing challenges encountered in logistic centers. This study addresses a logistic order-picking issue involving unidirectional conveyors and buffers, which are assigned to racks and pickers with the objective of minimizing the makespan. Subsequently, [...] Read more.

The necessity for undertaking this research is driven by the prevailing challenges encountered in logistic centers. This study addresses a logistic order-picking issue involving unidirectional conveyors and buffers, which are assigned to racks and pickers with the objective of minimizing the makespan. Subsequently, two variations of a two-step matheuristic approach are proposed as solution methodologies. These matheuristics entail decomposing the primary order-picking problem into two subproblems. In the initial step, the problem of minimizing the free time for pickers/buffers is solved, followed by an investigation into minimizing order picking makespan. An experimentation phase is carried out across three versions of a distribution center layout, wherein one or more pickers are allocated to one or more buffers, spanning 120 test instances. The research findings indicate that employing a mathematical programming-based technique holds promise for yielding solutions within reasonable computational timeframes, particularly when distributing products to consumers with limited product variety within the order. Furthermore, the proposed technique offers the advantages of expediency and simplicity, rendering it suitable for adoption in the process of designing and selecting order-picking systems. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

21 pages, 8800 KiB

Open AccessArticle

Design and Research of Intelligent Assembly and Welding Equipment for Three-Dimensional Circuit

by Zihang Wang, Xiaodong Du, Changrui Wang, Wei Tian, Chao Deng, Ke Li, Yifan Ding and Wenhe Liao

Appl. Sci. 2023, 13(16), 9359; https://doi.org/10.3390/app13169359 - 17 Aug 2023

Viewed by 1273

Abstract

The processing of the three-dimensional circuit on the surface of conformal antennas is mainly performed via manual processing. At present, there is no automatic intelligent equipment for the processing of a similar small-sized circuit with variable curvature in China. Therefore, a high-precision, automated, [...] Read more.

The processing of the three-dimensional circuit on the surface of conformal antennas is mainly performed via manual processing. At present, there is no automatic intelligent equipment for the processing of a similar small-sized circuit with variable curvature in China. Therefore, a high-precision, automated, full-process manufacturing method for three-dimensional circuits with flexible surfaces on conformal antennas of radar equipment has been proposed to improve processing quality and manufacturing efficiency. The processing relationship between solder paste spraying, resistor mounting, and laser welding in the flexible three-dimensional circuit manufacturing process was analyzed. The structure of the new conformal antenna three-dimensional circuit intelligent manufacturing equipment was determined, and simulation verification of the three-dimensional circuit processing was performed using Vericut. The optimal processing parameters were selected based on solid experiments. This method meets the electronic assembly requirements of radar equipment and fills the domestic gap. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

29 pages, 3522 KiB

Open AccessArticle

Development and Integration of a Workpiece-Based Calibration Method for an Optical Assistance System

by Julian Koch, Christopher Büchse and Thorsten Schüppstuhl

Appl. Sci. 2023, 13(13), 7369; https://doi.org/10.3390/app13137369 - 21 Jun 2023

Viewed by 1484

Abstract

Assistance systems utilize a broad range of technologies to provide information and guidance to workers in manufacturing. The use of light projectors, as of today, has seldom been catalogued in the relevant literature, and the implementation of such is yet to be found [...] Read more.

Assistance systems utilize a broad range of technologies to provide information and guidance to workers in manufacturing. The use of light projectors, as of today, has seldom been catalogued in the relevant literature, and the implementation of such is yet to be found in production environments. However, light projectors may offer a cost effective enhancement for production processes, especially within the context of large-scale workpieces. Of the pertaining literature, only one calibration algorithm is currently considered applicable, thus acting as a framework of motivation for this paper. A novel calibration algorithm based on Newton’s method is presented and validated in conjunction with a proof-of-concept demonstration of the resulting accuracy, as well as the integration of such into an interface based on Node-RED, with MQTT as the main protocol. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

18 pages, 3207 KiB

Open AccessArticle

Digitalization Trend and Its Influence on the Development of the Operational Process in Production Companies

by Michal Adamczak, Adam Kolinski, Justyna Trojanowska and Jozef Husár

Appl. Sci. 2023, 13(3), 1393; https://doi.org/10.3390/app13031393 - 20 Jan 2023

Cited by 15 | Viewed by 2283

Abstract

The subject of digitization is currently very widely described. Implementing digitization is a complex task and there are many variants of its implementation. The authors of this article asked themselves what current trends affect the digitization of processes and what factors resulting from [...] Read more.

The subject of digitization is currently very widely described. Implementing digitization is a complex task and there are many variants of its implementation. The authors of this article asked themselves what current trends affect the digitization of processes and what factors resulting from the characteristics of production enterprises affect the development of operational processes. The CAWI method was used in the study. In the analysis of the results, the following methods were used: Partial Least Squares Path Modeling (PLS), Mood’s Median Test, or visualization using a box plot. The analysis of the results allowed us to conclude that the development of operational processes of production enterprises is related to digitization trends, but this relationship is not direct. It is necessary to link digitalization trends with software development trends. The conducted research also indicated that there are company characteristics that determine the degree of use (absorption) and the perception of significance for digitalization trends. These characteristics are the type of a company and the age of a company. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

20 pages, 5130 KiB

Open AccessArticle

Zero-Trust Model for Smart Manufacturing Industry

by Biplob Paul and Muzaffar Rao

Appl. Sci. 2023, 13(1), 221; https://doi.org/10.3390/app13010221 - 24 Dec 2022

Cited by 14 | Viewed by 4635

Abstract

Traditional security architectures use a perimeter-based security model where everything internal to the corporate network is trusted by default. This type of architecture was designed to protect static servers and endpoints; however, we need to adapt to emerging technologies where serverless applications are [...] Read more.

Traditional security architectures use a perimeter-based security model where everything internal to the corporate network is trusted by default. This type of architecture was designed to protect static servers and endpoints; however, we need to adapt to emerging technologies where serverless applications are running on containers, mobile endpoints, IoT, and cyber-physical systems. Since the beginning of the fourth industrial revolution (Industry 4.0), there has been a massive investment in smart manufacturing which responds in real-time to the supply chain and connects the digital and physical environments using IoT, cloud computing, and data analytics. The zero-trust security model is a concept of implementing cybersecurity techniques considering all networks and hosts to be hostile irrespective of their location. Over the past few years, this model has proven to be a remarkably effective security solution in conventional networks and devices. In this paper, the zero-trust approach will be fully explored and documented explaining its principles, architecture, and implementation procedure. It will also include a background of the smart manufacturing industry and a review of the existing cyber security solutions followed by a proposed design of the zero-trust model along with all the enabling factors for on-premises and cloud-hosted infrastructure. Various security solutions such as micro-segmentation of the industrial network, device discovery, and compliance management tools that are essential in achieving complete zero-trust security are considered in the proposed architecture. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

26 pages, 3393 KiB

Open AccessArticle

Poka Yoke Meets Deep Learning: A Proof of Concept for an Assembly Line Application

by Matteo Martinelli, Marco Lippi and Rita Gamberini

Appl. Sci. 2022, 12(21), 11071; https://doi.org/10.3390/app122111071 - 1 Nov 2022

Cited by 7 | Viewed by 5533

Abstract

In this paper, we present the re-engineering process of an assembly line that features speed reducers and multipliers for agricultural applications. The “as-is” line was highly inefficient due to several issues, including the age of the machines, a non-optimal arrangement of the shop [...] Read more.

In this paper, we present the re-engineering process of an assembly line that features speed reducers and multipliers for agricultural applications. The “as-is” line was highly inefficient due to several issues, including the age of the machines, a non-optimal arrangement of the shop floor, and the absence of process standards. The assembly line issues were analysed with Lean Manufacturing tools, identifying irregularities and operations that require effort (Mura), overload (Muri), and waste (Muda). The definition of the “to-be” line included actions to update the department layout, modify the assembly process, and design the line feeding system in compliance with the concepts of Golden Zone (i.e., the horizontal space more ergonomically and easily accessible by the operator) and Strike Zone (i.e., the vertical workspace setup in accordance to ergonomics specifications). The re-engineering process identified a critical problem in the incorrect assembly of the oil seals, mainly caused by the difficulty in visually identifying the correct side of the component, due to different reasons. Convolutional neural networks were used to address this issue. The proposed solution resulted to be a Poka Yoke. The whole re-engineering process induced a productivity increase that is estimated from 46% to 80%. The study demonstrates how Lean Manufacturing tools together with deep learning technologies can be effective in the development of smart manufacturing lines. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

27 pages, 9180 KiB

Open AccessArticle

Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry

by Minjae Ko, Changho Lee and Yongju Cho

Appl. Sci. 2022, 12(18), 9381; https://doi.org/10.3390/app12189381 - 19 Sep 2022

Cited by 6 | Viewed by 4188

Abstract

Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional [...] Read more.

Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional value chain (RVC) and reshoring. With the advent of Industry 4.0, many manufacturing companies are introducing smart factories. A new type of manufacturing execution system (MES), a core system of smart factories, is necessary, owing to the new technologies and the increase in collaboration between companies. Here, we present the framework, development, and application processes of a “cloud-based collaborative MES System” to support the value chain of “order-design-production-delivery” for the manufacture of personalized sportswear products in the fashion industry in Korea. To this end, first, nine future MES deployment directions and frameworks are presented. Second, we present the UML modeling, conceptual framework, and functional framework for MES system development, considering six future MES establishment directions such as cloud and collaboration. Third, the application and effect of the designed and developed cloud-based collaborative MES system are analyzed for design, fabric, printing, and sewing companies that play a role in each stage of the sportswear value chain. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

17 pages, 2854 KiB

Open AccessArticle

An Evaluation Model of Smart Manufacturing System Configurations Prior to Implementation Using Fuzzy Logic

by Jennifer Grace, Moamin A. Mahmoud, Mohammed Najah Mahdi and Salama A. Mostafa

Appl. Sci. 2022, 12(5), 2560; https://doi.org/10.3390/app12052560 - 1 Mar 2022

Viewed by 4997

Abstract

Several research works have addressed the different aspects and technologies associated with Smart Manufacturing Systems (SMS); however, the evaluation challenges while establishing a new SMS that requires pre-implementation planning and assessment have given little attention. To overcome this limitation, this paper formulates an [...] Read more.

Several research works have addressed the different aspects and technologies associated with Smart Manufacturing Systems (SMS); however, the evaluation challenges while establishing a new SMS that requires pre-implementation planning and assessment have given little attention. To overcome this limitation, this paper formulates an evaluation framework by identifying apparent evaluation factors to measure the effectiveness of a particular SMS configuration before implementation. Three factors from the literature studies have been used as inputs to control the final output of the configuration modal. Compositions were manipulated based on how factors affected the manufacturing cost justification in multiple setups. Different configurations were analyzed based on the trained Fuzzy Logic model by configurations and based on the trained Fuzzy Logic model using MATLAB’s Fuzzy Logic Designer tool. Results obtained from the evaluation performed by various configuration experiments were later presented to actual field engineers from the manufacturing industry to evaluate the satisfaction level of the evaluation framework. The result showed that this proposed configuration model has a satisfactory rate of 83.7%, as this was achieved by significant feedback from field engineers. This study has significantly facilitated the identification of influential factors and the measured relationship of the factors in the formulated configurations, enabling the best configuration approach to be identified. Therefore, it can be concluded that a visualized and measured configuration system can influence decision-making in the manufacturing industry, thus allowing manufacturers to stay competitive by making well-versed decisions proactively. Exclusively, this research has staged a framework for the industry to follow suit and adapt for future research work related to the SMS field. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

11 pages, 2231 KiB

Open AccessArticle

Profit-Driven Methodology for Servo Press Motion Selection under Material Variability

by Nozomu Okuda, Luke Mohr, Hyunok Kim and Alex Kitt

Appl. Sci. 2021, 11(20), 9530; https://doi.org/10.3390/app11209530 - 14 Oct 2021

Cited by 3 | Viewed by 2287

Abstract

Servo presses enable new types of forming motion profiles that can be used to stamp difficult materials, such as high strength steels. This paper presents an application of Bayesian statistics to intelligently select which motion profile maximizes the expected utility given the properties [...] Read more.

Servo presses enable new types of forming motion profiles that can be used to stamp difficult materials, such as high strength steels. This paper presents an application of Bayesian statistics to intelligently select which motion profile maximizes the expected utility given the properties of the incoming material. Bayesian logistic regression was used in conjunction with expected utility to estimate manufacturing returns, which can be used to make informed process decisions. A use case is presented, which demonstrates that the Smart Forming Algorithm can increase expected returns by more than 20%. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

19 pages, 7924 KiB

Open AccessArticle

A Mixed Reality Interface for a Digital Twin Based Crane

by Xinyi Tu, Juuso Autiosalo, Adnane Jadid, Kari Tammi and Gudrun Klinker

Appl. Sci. 2021, 11(20), 9480; https://doi.org/10.3390/app11209480 - 12 Oct 2021

Cited by 23 | Viewed by 6265

Abstract

Digital twin technology empowers the digital transformation of the industrial world with an increasing amount of data, which meanwhile creates a challenging context for designing a human–machine interface (HMI) for operating machines. This work aims at creating an HMI for digital twin based [...] Read more.

Digital twin technology empowers the digital transformation of the industrial world with an increasing amount of data, which meanwhile creates a challenging context for designing a human–machine interface (HMI) for operating machines. This work aims at creating an HMI for digital twin based services. With an industrial crane platform as a case study, we presented a mixed reality (MR) application running on a Microsoft HoloLens 1 device. The application, consisting of visualization, interaction, communication, and registration modules, allowed crane operators to both monitor the crane status and control its movement through interactive holograms and bi-directional data communication, with enhanced mobility thanks to spatial registration and tracking of the MR environment. The prototype was quantitatively evaluated regarding the control accuracy in 20 measurements following a step-by-step protocol that we defined to standardize the measurement procedure. The results suggested that the differences between the target and actual positions were within the 10 cm range in three dimensions, which were considered sufficiently small regarding the typical crane operation use case of logistics purposes and could be improved with the adoption of robust registration and tracking techniques in our future work. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Graphical abstract

19 pages, 3436 KiB

Open AccessArticle

A Model for Working Environment Monitoring in Smart Manufacturing

by Dalibor Dobrilovic, Vladimir Brtka, Zeljko Stojanov, Gordana Jotanovic, Dragan Perakovic and Goran Jausevac

Appl. Sci. 2021, 11(6), 2850; https://doi.org/10.3390/app11062850 - 23 Mar 2021

Cited by 23 | Viewed by 4521

Abstract

The growing application of smart manufacturing systems and the expansion of the Industry 4.0 model have created a need for new teaching platforms for education, rapid application development, and testing. This research addresses this need with a proposal for a model of working [...] Read more.

The growing application of smart manufacturing systems and the expansion of the Industry 4.0 model have created a need for new teaching platforms for education, rapid application development, and testing. This research addresses this need with a proposal for a model of working environment monitoring in smart manufacturing, based on emerging wireless sensor technologies and the message queuing telemetry transport (MQTT) protocol. In accordance with the proposed model, a testing platform was developed. The testing platform was built on open-source hardware and software components. The testing platform was used for the validation of the model within the presented experimental environment. The results showed that the proposed model could be developed by mainly using open-source components, which can then be used to simulate different scenarios, applications, and target systems. Furthermore, the presented stable and functional platform proved to be applicable in the process of rapid prototyping, and software development for the targeted systems, as well as for student teaching as part of the engineering education process. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Smart Manufacturing Systems in Industry 4.0

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (14 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI