Special Issue "Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019)"

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: closed (30 November -0001).

Special Issue Editors

Prof. Eva M. Rubio
E-Mail Website
Guest Editor
Department of Manufacturing Engineering, Universidad Nacional de Educación a Distancia (UNED), Juan del Rosal 12, E28040-Madrid, Spain
Interests: machining; lightweight materials (magnesium alloys, aluminum alloys, titanium alloys); metal forming technology and processing; sustainable manufacturing; industrial metrology; virtual reality; e-learning; innovation in distance teaching
Special Issues and Collections in MDPI journals
Prof. Ana M. Camacho
E-Mail Website
Guest Editor
Department of Manufacturing Engineering, Universidad Nacional de Educación a Distancia (UNED), Juan del Rosal 12, E28040-Madrid, Spain
Interests: metal forming of metallic materials (lightweight alloys, advanced high-strength steels); additive manufacturing; industrial metrology; materials technology; development of virtual labs
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Due to the success of the first Special Edition, and encouraged by the Manufacturing Engineering Society (MES), a new Special Edition called “The Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019)” is launched as a joint issue of the journals Materials and Applied Sciences.

The first edition collected 48 contributions on emerging methods and technologies, such as those related to additive manufacturing and 3D printing, advances and innovations in manufacturing processes in different areas (machining, forming, molding, welding, and nontraditional manufacturing processes), manufacturing systems (machines, equipment and tooling), metrology and quality in manufacturing, product lifecycle management (PLM) technologies, and risks in manufacturing engineering and society.

This second edition involves the aforementioned journals with the aim of covering the wide range of research lines developed by the members and collaborators of the MES and other researchers within the field of Manufacturing Engineering.

Similarly to the first one, the main objective of “The Special Issue of the Manufacturing Engineering Society 2019” is to publish outstanding papers presenting cutting-edge advances in the field of Manufacturing Engineering, focusing on materials processing, as well as on experimental and theoretical results within applied sciences.

The Special Issue aims to explore the evolution of traditional manufacturing models towards the new requirements of the Manufacturing Industry 4.0 and how manufacturing professionals should face the resulting competitive challenges in the context of an ever-increasing use of digital information systems and communication technologies.

Contributions on emerging methods and technologies such as those related to additive manufacturing will have special relevance within this Special Issue, as well as those ones where sustainability and environmental issues play a fundamental role in manufacturing.

The main topics covered by this Special Issue are scientific contributions on the following manufacturing research topics:

  • Additive manufacturing and 3D printing
  • Advances and innovations in manufacturing processes
  • Sustainable and green manufacturing
  • Micro and nanomanufacturing
  • Manufacturing of new materials
  • Manufacturing systems: machines, equipment and tooling
  • Robotics, mechatronics and manufacturing automation
  • Metrology and quality in manufacturing
  • Industry 4.0
  • Product lifecycle management (PLM) technologies
  • Design, modeling, and simulation in manufacturing engineering
  • Production planning
  • Manufacturing engineering and society

The above list is not exhaustive, and papers on other topics associated with advances in manufacturing engineering are also welcome.

Excellent papers selected from the Manufacturing Engineering Society International Conference 2019 can also be part of this Special Issue, provided that the degree of novelty of the contribution is guaranteed and the paper has been not published elsewhere.

Especially welcome are all the works with a clear application to the manufacturing field related to nanotechnology and applied nanoscience; optics and lasers; energy savings in manufacturing systems and processes; mechanical engineering; computer science and manufacturing engineering; applied biosciences and bioengineering; applied industrial technologies.

It is our pleasure to invite professionals from Industry, Academic Institutions and Research Centers from around the world to submit their contributions to this Special Issue.

We hope this second edition of the Special Issue is as successful as the first one.

text

Prof. Eva M. Rubio
Prof. Ana M. Camacho
Guest Editors

  • Members of the Manufacturing Engineering Society will benefit from a 15% discount (approx. 200 €) on the article processing charges. If you are not a member yet, please find more information on how to join the society (here). Regular individual member fee 75 €/year, student fee 35 €/year.

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords


  • 3D printing
  • Additive manufacturing
  • Assembly processes
  • Bioengineering
  • Computer science
  • Digital manufacturing
  • Energy savings
  • Ergonomy
  • Forming
  • Friction
  • Green manufacturing
  • Industrial technologies
  • Industry 4.0
  • Joining
  • Machining
  • Manufacturing automation
  • Manufacturing systems
  • Mechatronics
  • Metrology
  • Micro-manufacturing
  • Modeling and simulation
  • Moulding
  • Nano-manufacturing
  • Non-traditional manufacturing processes
  • Optics and lasers
  • Processing of materials
  • Product Lifecycle Management 
  • Production planning
  • Quality in manufacturing
  • Robotics
  • Safety and risks
  • Smart manufacturing
  • Sustainable manufacturing
  • Technological and Industrial Heritage
  • Virtual manufacturing
  • Wear
  • Welding

Published Papers (11 papers)

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Editorial

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Open AccessEditorial
Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019)
Appl. Sci. 2020, 10(5), 1590; https://doi.org/10.3390/app10051590 (registering DOI) - 27 Feb 2020
Abstract
The Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019) has been launched as a joint issue of the journals “Applied Sciences” and “Materials”. The 10 contributions published in this Special Issue of Applied Sciences present cutting-edge advances in production planning, sustainability, metrology, [...] Read more.
The Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019) has been launched as a joint issue of the journals “Applied Sciences” and “Materials”. The 10 contributions published in this Special Issue of Applied Sciences present cutting-edge advances in production planning, sustainability, metrology, cultural heritage, and materials processing with experimental and numerical results. It is worth mentioning how the topic “production planning” has attracted a great number of contributions in this journal, due to their applicative approach. Full article

Research

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Open AccessArticle
Cutting Speed and Feed Influence on Surface Microhardness of Dry-Turned UNS A97075-T6 Alloy
Appl. Sci. 2020, 10(3), 1049; https://doi.org/10.3390/app10031049 - 05 Feb 2020
Abstract
In this work, an analysis of the cutting speed and feed influence on surface roughness and microhardness of UNS A97075-T6 alloy, turned under dry conditions, was carried out. The results were compared before and after a corrosion process. The influence of these cutting [...] Read more.
In this work, an analysis of the cutting speed and feed influence on surface roughness and microhardness of UNS A97075-T6 alloy, turned under dry conditions, was carried out. The results were compared before and after a corrosion process. The influence of these cutting parameters on each of these variables was analyzed, as well as the possible interrelation between them. The microgeometrical deviations showed a general trend to increase with feed. However, no significant modifications were observed as a function of the cutting speed. This trend was softer after the corrosion process, due to the surface alterations produced by pitting corrosion, which resulted in higher dispersion of the experimental data. In addition, a surface microhardness increment was observed in all samples, after machining and before corrosion, regardless of the cutting parameter values. The experimental results revealed that the mechanical effects, produced by the feed, should not be neglected against the thermal effects, produced by the cutting speed, within the range of the tested cutting speed. Finally, the corrosion process negatively affected the microhardness, but it was not possible to establish a direct relationship between the cutting parameters, surface roughness, and microhardness after a corrosion process. Full article
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Open AccessArticle
Smart Multi-Sensor Monitoring in Drilling of CFRP/CFRP Composite Material Stacks for Aerospace Assembly Applications
Appl. Sci. 2020, 10(3), 758; https://doi.org/10.3390/app10030758 - 21 Jan 2020
Abstract
Composite material parts are typically laid out in near-net-shape, i.e., very close to the finished product configuration. However, further machining processes are often required to meet dimensional and tolerance requirements. Drilling, edge trimming and slotting are the main cutting processes employed for carbon [...] Read more.
Composite material parts are typically laid out in near-net-shape, i.e., very close to the finished product configuration. However, further machining processes are often required to meet dimensional and tolerance requirements. Drilling, edge trimming and slotting are the main cutting processes employed for carbon fiber-reinforced plastic (CFRP) composite materials. In particular, drilling stands out as the most widespread machining process of CFRP composite parts, chiefly in the aerospace industrial sector, due to the extensive use of mechanical joints, such as rivets, rather than welded or bonded joints. However, CFRP drilling is markedly challenging: due to CFRP abrasiveness, inhomogeneity and anisotropic properties, tool wear rates are inherently high leading to superior cutting forces and detrimental effects on workpiece surface quality and material integrity. Damage such as delamination, cracks or matrix thermal degradation is often observed as the result of uncontrolled tool wear or improper machining conditions. Sensor monitoring of drilling operations is, therefore, highly desirable for process conditions’ optimization and tool life maximization. The development of this kind of automated control technologies for process and tool state evaluation can notably contribute to the reduction of scraps and tool costs as well as to the improvement of process productivity in the drilling of CFRP composite material parts. In this paper, multi-sensor process monitoring based on thrust force and torque signal detection and analysis was applied during drilling of CFRP/CFRP laminate stacks for the assembly of aircraft fuselage panels with the scope to evaluate the tool wear state. Different signal-processing methods were utilised to extract diverse types of features from the detected sensor signals. A machine-learning approach based on an artificial neural network (ANN) was implemented to make smart decisions on the timely execution of tool change, which is highly functional for CFRP drilling process automation. Full article
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Open AccessArticle
Experimental and Numerical Simulation Investigation on Deep Drawing Process of Inconel 718 with and without Intermediate Annealing Thermal Treatments
Appl. Sci. 2020, 10(2), 581; https://doi.org/10.3390/app10020581 - 13 Jan 2020
Abstract
The aeronautical industry is moving from high-capacity large-airplane construction to low-capacity small-airplane construction. With the change in the production volume, there is a need for more efficient manufacturing processes, such as stamping/deep drawing. However, the streamlined shape and exotic materials of airplanes pose [...] Read more.
The aeronautical industry is moving from high-capacity large-airplane construction to low-capacity small-airplane construction. With the change in the production volume, there is a need for more efficient manufacturing processes, such as stamping/deep drawing. However, the streamlined shape and exotic materials of airplanes pose a challenge to accurate numerical simulation of the manufacturing processes. In the case of the Inconel 718 material, researchers previously proposed numerical models; however, these models failed to take account of some key parameters, such as the degradation of the elastic modulus and intermediate annealing thermal processes. The aim of the present study was to characterize the Inconel 718 material, with and without intermediate annealing thermal treatment (TT) and to propose a suitable model. To evaluate the accuracy of the proposed model, a U-drawing benchmark test was used. Full article
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Open AccessArticle
Development of a Pull Production Control Method for ETO Companies and Simulation for the Metallurgical Industry
Appl. Sci. 2020, 10(1), 274; https://doi.org/10.3390/app10010274 - 30 Dec 2019
Abstract
At the moment, many engineer-to-order manufacturers are under pressure, the overcapacity in many sectors erodes prices and many companies, especially in Europe have gone into recent years in bankruptcy. Due to the increasing competition as well as the new customer requirements, the internal [...] Read more.
At the moment, many engineer-to-order manufacturers are under pressure, the overcapacity in many sectors erodes prices and many companies, especially in Europe have gone into recent years in bankruptcy. Due to the increasing competition as well as the new customer requirements, the internal processes of an ETO company play an essential role in order to achieve a unique selling proposition (USP). Therefore this paper exposes how the production planning and control of an engineer-to-order manufacturer can be designed in order to increase its OTD (order-to-delivery) rate as well as decrease the WIP (work-in-progress) and the production lead times. To prove the optimized planning logic, it was applied in a simulation case study and based on the results; the conclusions about its potential are derived. Full article
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Open AccessArticle
Value Stream Analysis in Military Logistics: The Improvement in Order Processing Procedure
Appl. Sci. 2020, 10(1), 106; https://doi.org/10.3390/app10010106 - 21 Dec 2019
Abstract
Military logistics is a complex process where response times, demand uncertainty, wide variety of material references, and cost-effectiveness are decisive for combat capability. The demanding flexibility can only be achieved by improving supply chain management (SCM) to minimize lead times. To cope with [...] Read more.
Military logistics is a complex process where response times, demand uncertainty, wide variety of material references, and cost-effectiveness are decisive for combat capability. The demanding flexibility can only be achieved by improving supply chain management (SCM) to minimize lead times. To cope with these requirements, lean thinking can be extended to military organizations. This research justifies and proposes the use of lean methodologies to improve logistics processes with the case study of a military unit. In particular, the article presents the results obtained using value stream mapping (VSM) and value stream design (VSD) tools to improve the order processing lead time of spare items. The procedure starts with an order generation from a military unit that requests the material and ends before transportation to the final destination. The whole project was structured, considering the define–measure–analyze–improve–control (DMAIC) problem-solving methodology. The results show that the future state map might increase added-value activities from 44% to 70%. After implementation, it was demonstrated that the methodology applied reduced the lead-time average and deviation up to 69.6% and 61.9%, respectively. Full article
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Open AccessArticle
Design and Simulation of a Capacity Management Model Using a Digital Twin Approach Based on the Viable System Model: Case Study of an Automotive Plant
Appl. Sci. 2019, 9(24), 5567; https://doi.org/10.3390/app9245567 - 17 Dec 2019
Abstract
Matching supply capacity and customer demand is challenging for companies. Practitioners often fail due to a lack of information or delays in the decision-making process. Moreover, researchers fail to holistically consider demand patterns and their dynamics over time. Thus, the aim of this [...] Read more.
Matching supply capacity and customer demand is challenging for companies. Practitioners often fail due to a lack of information or delays in the decision-making process. Moreover, researchers fail to holistically consider demand patterns and their dynamics over time. Thus, the aim of this study is to propose a holistic approach for manufacturing organizations to change or manage their capacity. The viable system model was applied in this study. The focus of the research is the clustering of manufacturing and assembly companies. The goal of the developed capacity management model is to be able to react to all potential demand scenarios by making decisions regarding labor and correct investments and in the right moment based on the needed information. To ensure this, demand data series are analyzed enabling autonomous decision-making. In conclusion, the proposed approach enables companies to have internal mechanisms to increase their adaptability and reactivity to customer demands. In order to prove the conceptual model, a simulation of an automotive plant case study was performed, comparing it to classical approaches. Full article
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Open AccessArticle
A Hybrid Machine Learning and Population Knowledge Mining Method to Minimize Makespan and Total Tardiness of Multi-Variety Products
Appl. Sci. 2019, 9(24), 5286; https://doi.org/10.3390/app9245286 - 04 Dec 2019
Abstract
Nowadays, the production model of many enterprises is multi-variety customized production, and the makespan and total tardiness are the main metrics for enterprises to make production plans. This requires us to develop a more effective production plan promptly with limited resources. Previous research [...] Read more.
Nowadays, the production model of many enterprises is multi-variety customized production, and the makespan and total tardiness are the main metrics for enterprises to make production plans. This requires us to develop a more effective production plan promptly with limited resources. Previous research focuses on dispatching rules and algorithms, but the application of the knowledge mining method for multi-variety products is limited. In this paper, a hybrid machine learning and population knowledge mining method to minimize makespan and total tardiness for multi-variety products is proposed. First, through offline machine learning and data mining, attributes of operations are selected to mine the initial population knowledge. Second, an addition–deletion sorting method (ADSM) is proposed to reprioritize operations and then form the rule-based initial population. Finally, the nondominated sorting genetic algorithm II (NSGA-II) hybrid with simulated annealing is used to obtain the Pareto solutions. To evaluate the effectiveness of the proposed method, three other types of initial populations were considered under different iterations and population sizes. The experimental results demonstrate that the new approach has a good performance in solving the multi-variety production planning problems, whether it is the function value or the performance metric of the acquired Pareto solutions. Full article
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Open AccessArticle
Use of 3D Printing in Model Manufacturing for Minor Surgery Training of General Practitioners in Primary Care
Appl. Sci. 2019, 9(23), 5212; https://doi.org/10.3390/app9235212 - 30 Nov 2019
Abstract
In order to increase the efficiency of the Spanish health system, minor surgery programs are currently carried out in primary care centers. This organizational change has led to the need to train many general practitioners (GPs) in this discipline on a practical level. [...] Read more.
In order to increase the efficiency of the Spanish health system, minor surgery programs are currently carried out in primary care centers. This organizational change has led to the need to train many general practitioners (GPs) in this discipline on a practical level. Due to the cost of the existing minor surgery training models in the market, pig’s feet or chicken thighs are used to practice the removal of figured lesions and the suture of wounds. In the present work, the use of 3D printing is proposed, to manufacture models that reproduce in a realistic way the most common lesions in minor surgery practice, and that allow doctors to be trained in an adequate way. Four models with the most common dermal lesions have been designed and manufactured, and then evaluated by a panel of experts. Face validity was demonstrated with four items on a five-point Likert scale that was completed anonymously. The models have obtained the following results: aesthetic recreation, 4.6 ± 0.5; realism during anesthesia infiltration, 4.8 ± 0.4; realism during lesion removal, 2.8 ± 0.4; realism during surgical wound closure, 1.2 ± 0.4. The score in this last section could be improved if a more elastic skin-colored filament were found on the market. Full article
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Open AccessArticle
Hyperspectral Imaging Techniques for the Study, Conservation and Management of Rock Art
Appl. Sci. 2019, 9(23), 5011; https://doi.org/10.3390/app9235011 - 21 Nov 2019
Abstract
Paleolithic rock art is one of the most important cultural phenomena in the history of mankind. It was made by making incisions and/or applying natural pigments mixed with water or organic elements on a rock surface, which for millennia has been subjected to [...] Read more.
Paleolithic rock art is one of the most important cultural phenomena in the history of mankind. It was made by making incisions and/or applying natural pigments mixed with water or organic elements on a rock surface, which for millennia has been subjected to different factors of natural and anthropogenic alteration that have caused its deterioration and/or disappearance. The present paper shows a methodology that employs hyperspectral technology in the range of visible light and the near infrared spectrum, providing a scientific and non-destructive way to study, conserve and manage such a valuable cultural heritage. Recognition of coloring matter, formal recognition of the figures, superposition of forms and documentation of the state of conservation are relevant topics in rock art, and hyperspectral imaging technology is an efficient way to study them. The aim is to establish a method of creating pigment cartography and enhancing the visualization of rock art panels. Illumination sources, spectroradiometry measurements and camera adjustments must be taken into account to generate accurate results that later will be pre-processed to derive reflectance data, and then pigment analysis and enhanced visualization methods are applied. This methodology has allowed us to obtain 76% more figures than using traditional techniques throughout the case study area. Full article
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Open AccessArticle
2D Positioning Control System for the Planar Motion of a Nanopositioning Platform
Appl. Sci. 2019, 9(22), 4860; https://doi.org/10.3390/app9224860 - 13 Nov 2019
Abstract
A novel nanopositioning platform (referred as NanoPla) in development has been designed to achieve nanometre resolution in a large working range of 50 mm × 50 mm. Two-dimensional (2D) movement is performed by four custom-made Halbach linear motors, and a 2D laser system [...] Read more.
A novel nanopositioning platform (referred as NanoPla) in development has been designed to achieve nanometre resolution in a large working range of 50 mm × 50 mm. Two-dimensional (2D) movement is performed by four custom-made Halbach linear motors, and a 2D laser system provides positioning feedback, while the moving part of the platform is levitating and unguided. For control hardware, this work proposes the use of a commercial generic solution, in contrast to other systems where the control hardware and software are specifically designed for that purpose. In a previous paper based on this research, the control system of one linear motor implemented in selected commercial hardware was presented. In this study, the developed control system is extended to the four motors of the nanopositioning platform to generate 2D planar movement in the whole working range of the nanopositioning platform. In addition, the positioning uncertainty of the control system is assessed. The obtained results satisfy the working requirements of the NanoPla, achieving a positioning uncertainty of ±0.5 µm along the whole working range. Full article
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