Special Issue "2019 Smart Manufacturing on Production System, Quality Assurance, Process optimization, and Digital Modeling"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (30 September 2019).

Special Issue Editors

Prof. Dr. Chien-Hung Liu
E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 402, Taiwan
Fax: +886 4 2287 7170
Interests: high precision instrument design; laser engineering; smart sensors and actuators; optical device; optical measurement; metrology
Special Issues and Collections in MDPI journals
Prof. Dr. Jyh-Horng Chou
E-Mail
Guest Editor
(1) Department of Electrical Engineering, National Kaohsiung University of Science and Technology, 415 Chien-Kung Road, Kaohsiung 807, Taiwan (2) Department of Mechanical Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 402, Taiwan
Interests: artificial intelligence; information technology and system integration; system modeling and simulation; system dynamics and control; integration technology of automation systems; numerical analysis and computational mathematics; robust optimization technology
Special Issues and Collections in MDPI journals
Prof. Dr. Chih Jer Lin
E-Mail
Guest Editor
Graduate Institute of Automation Technology, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan
Interests: numerical simulation; nonlinear control; mechatronics; precision motion control; system identification; sliding-mode control; robotics; evolutionary algorithms
Special Issues and Collections in MDPI journals
Prof. Dr. Cheng-Chi Wang
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Guest Editor
Ph.D. Program, Graduate Institute of Precision Manufacturing, National Chin-Yi University of Technology, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung 41170, Taiwan
Interests: numerical simulation; chaos; nonlinear control; gas bearing system; advanced manufacturing process
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Global manufacturing industries emphasize on Smart Manufacturing/Industry 4.0 research issues, which include: Production systems, quality assurance, process optimization, and digital modeling. The application and integration of statistical methods, computational intelligence, artificial intelligence, and control technology provide such solutions. This Special Issue invites authors to submit their high-quality papers in 2019 related to following topics:

(1) Production systems:
Production schedule, production facilities (condition sensing and monitoring, predictive maintenance, condition measurement and estimation, automatic calibration and Compensation, online adjustment, automatic control technology);

(2) Quality assurance:
Quality examination, quality estimation, quality prognosis, diagnosis, and analysis of process condition;

(3) Process optimization:
Process capability optimization, process parameter optimization, process proficiency optimization, energy usage optimization, and process stability optimization;

(4) Digital modeling:
Creating digital twin and twin model.

Prof. Dr. Chien-Hung Liu
Prof. Dr. Jyh-Horng Chou
Prof. Dr. Chih Jer Lin
Prof. Dr. Cheng-Chi Wang
Guest Editors

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

  • Production system
  • Quality assuranc
  • Process optimization
  • Digital modeling
  • Statistical methods
  • Computational intelligence
  • Artificial intelligence
  • Control technology

Published Papers (18 papers)

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Research

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Open AccessArticle
A Deep-Learning-Based Vehicle Detection Approach for Insufficient and Nighttime Illumination Conditions
Appl. Sci. 2019, 9(22), 4769; https://doi.org/10.3390/app9224769 - 08 Nov 2019
Cited by 1
Abstract
Most object detection models cannot achieve satisfactory performance under nighttime and other insufficient illumination conditions, which may be due to the collection of data sets and typical labeling conventions. Public data sets collected for object detection are usually photographed with sufficient ambient lighting. [...] Read more.
Most object detection models cannot achieve satisfactory performance under nighttime and other insufficient illumination conditions, which may be due to the collection of data sets and typical labeling conventions. Public data sets collected for object detection are usually photographed with sufficient ambient lighting. However, their labeling conventions typically focus on clear objects and ignore blurry and occluded objects. Consequently, the detection performance levels of traditional vehicle detection techniques are limited in nighttime environments without sufficient illumination. When objects occupy a small number of pixels and the existence of crucial features is infrequent, traditional convolutional neural networks (CNNs) may suffer from serious information loss due to the fixed number of convolutional operations. This study presents solutions for data collection and the labeling convention of nighttime data to handle various types of situations, including in-vehicle detection. Moreover, the study proposes a specifically optimized system based on the Faster region-based CNN model. The system has a processing speed of 16 frames per second for 500 × 375-pixel images, and it achieved a mean average precision (mAP) of 0.8497 in our validation segment involving urban nighttime and extremely inadequate lighting conditions. The experimental results demonstrated that our proposed methods can achieve high detection performance in various nighttime environments, such as urban nighttime conditions with insufficient illumination, and extremely dark conditions with nearly no lighting. The proposed system outperforms original methods that have an mAP value of approximately 0.2. Full article
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Open AccessArticle
Detection and Classification of Advanced Persistent Threats and Attacks Using the Support Vector Machine
Appl. Sci. 2019, 9(21), 4579; https://doi.org/10.3390/app9214579 - 28 Oct 2019
Cited by 1
Abstract
Traditional network attack and hacking models are constantly evolving to keep pace with the rapid development of network technology. Advanced persistent threat (APT), usually organized by a hacker group, is a complex and targeted attack method. A long period of strategic planning and [...] Read more.
Traditional network attack and hacking models are constantly evolving to keep pace with the rapid development of network technology. Advanced persistent threat (APT), usually organized by a hacker group, is a complex and targeted attack method. A long period of strategic planning and information search usually precedes an attack on a specific goal. Focus is on a targeted object and customized specific methods are used to launch the attack and obtain confidential information. This study offers an attack detection system that enables early discovery of the APT attack. The system uses the NSL-KDD database for attack detection and verification. The main method uses principal component analysis (PCA) for feature sampling and the enhancement of detection efficiency. The advantages and disadvantages of using the classifiers are then compared to detect the dataset, the classifier supports the vector machine, naive Bayes classification, the decision tree and neural networks. Results of the experiments show the support vector machine (SVM) to have the highest recognition rate, reaching 97.22% (for the trained subdata A). The purpose of this study was to establish an APT early warning model mechanism, that could be used to reduce the impact and influence of APT attacks. Full article
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Open AccessArticle
A Cloud Information Monitoring and Recommendation Multi-Agent System with Friendly Interfaces for Tourism
Appl. Sci. 2019, 9(20), 4385; https://doi.org/10.3390/app9204385 - 17 Oct 2019
Abstract
The tourism statistics of Taiwan’s government state that the tourism industry is one of the fastest growing economic sources in the world. Therefore, the demand for a tourism information system with a friendly interface is growing. This research implemented the construction of a [...] Read more.
The tourism statistics of Taiwan’s government state that the tourism industry is one of the fastest growing economic sources in the world. Therefore, the demand for a tourism information system with a friendly interface is growing. This research implemented the construction of a cloud information service platform based on numerous practical developments in the Dr. What-Info system (i.e., a master multi-agent system on what the information is), which developed universal application interface (UAI) technology based on the Taiwan government’s open data with the aim of connecting different application programming interfaces (APIs) according to different data formats and intelligence through local GPS location retrieval, in support of three-stage intelligent decision-making and a three-tier address-based UAI technology comparison. This paper further developed a novel citizen-centric multi-agent information monitoring and recommendation system for the tourism sector. The proposed system was experimentally demonstrated as a successful integration of technology, and stands as an innovative piece of work in the literature. Although there is room for improvement in experience and maybe more travel-related agents, the feasibility of the proposed service architecture has been proven. Full article
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Open AccessArticle
Limited Search Space-Based Algorithm for Dual Resource Constrained Scheduling Problem with Multilevel Product Structure
Appl. Sci. 2019, 9(19), 4005; https://doi.org/10.3390/app9194005 - 25 Sep 2019
Abstract
This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we propose an algorithm for the DRCFJSP [...] Read more.
This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we propose an algorithm for the DRCFJSP with a multilevel product structure to minimize the lateness, makespan, and deviation of the workload with preemptive priorities. To efficiently solve the problem within a limited time, the search space is limited based on the possible start and end time, and focus is placed on the intensification rather than diversification, which can help the algorithm spend more time to find an optimal solution in a reasonable solution space. The performance of the proposed algorithm is compared with those of a genetic algorithm and a hybrid genetic algorithm with variable neighborhood search. The numerical experiments demonstrate that the strategy limiting the search space is effective for large and complex problems. Full article
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Open AccessArticle
The Role of Advanced Manufacturing Technologies in Production Process Performance: A Causal Model
Appl. Sci. 2019, 9(18), 3741; https://doi.org/10.3390/app9183741 - 07 Sep 2019
Abstract
Advanced manufacturing technologies (AMT) require considerable investments that managers often avoid, which makes it difficult to link their production operations with the benefits reported in literature review. The present paper shows a structural equation model that integrates four latent variables to measure the [...] Read more.
Advanced manufacturing technologies (AMT) require considerable investments that managers often avoid, which makes it difficult to link their production operations with the benefits reported in literature review. The present paper shows a structural equation model that integrates four latent variables to measure the relationship between the levels of advanced manufacturing technologies implementation (Stand-Alone Intermediate and Integrated Systems), as well as the benefits obtained in the productive systems. The variables are related to each other using six hypotheses in order to realise how the AMT implementation level affects the benefits obtained from a quantitative and statistical point of view. The model is evaluated through the partial least square technique with data from 383 responses to a survey. Findings show that Stand-Alone Systems contribute more to obtaining Production Benefits, followed by Integrated Systems and Intermediate Systems. Finally, a sensitivity analysis based on conditional probabilities was performed to evaluate scenarios at different implementation levels in AMT to know how they facilitate the acquisition of the benefits offered. Full article
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Open AccessArticle
A Business Process Analysis Methodology Based on Process Mining for Complaint Handling Service Processes
Appl. Sci. 2019, 9(16), 3313; https://doi.org/10.3390/app9163313 - 12 Aug 2019
Abstract
To improve the service quality of complaint handling service in a manufacturing company, it is key to analyze the business processes. Process mining is quite a useful approach to diagnose complaint handling service process problems, such as bottlenecks and deviations. However, the current [...] Read more.
To improve the service quality of complaint handling service in a manufacturing company, it is key to analyze the business processes. Process mining is quite a useful approach to diagnose complaint handling service process problems, such as bottlenecks and deviations. However, the current business process analysis methodologies based on process mining mainly focus on operational process analysis and neglect other system level analysis. In this study, we introduce the method of Accimap from the discipline of accident analysis to analyze the diagnosis results of process mining. By creating a complaint handling service process management Accimap model, the process mining results analysis can be carried out across different system levels. A case study in a big manufacturing company in China is implemented to verify our approach. In the case study, 42 complaint handling process management factors are identified and the complaint handling process management Accimap model is created. The testing results by Rasmussen’s seven predictions in his risk management framework show that Accimap method presents a systematic approach to analyze the process diagnosis results based on process mining. Full article
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Open AccessArticle
A Hybrid Two-Phase Recommendation for Group-Buying E-commerce Applications
Appl. Sci. 2019, 9(15), 3141; https://doi.org/10.3390/app9153141 - 02 Aug 2019
Abstract
The last two decades have witnessed an explosive growth of e-commerce applications. Existing online recommendation systems for e-commerce applications, particularly group-buying applications, suffer from scalability and data sparsity problems when confronted with exponentially increasing large-scale data. This leads to a poor recommendation effect [...] Read more.
The last two decades have witnessed an explosive growth of e-commerce applications. Existing online recommendation systems for e-commerce applications, particularly group-buying applications, suffer from scalability and data sparsity problems when confronted with exponentially increasing large-scale data. This leads to a poor recommendation effect of traditional collaborative filtering (CF) methods in group-buying applications. In order to address this challenge, this paper proposes a hybrid two-phase recommendation (HTPR) method which consists of offline preparation and online recommendation, combining clustering and collaborative filtering techniques. The user-item category tendency matrix is constructed after clustering items, and then users are clustered to facilitate personalized recommendation where items are generated by collaborative filtering technology. In addition, a parallelized strategy was developed to optimize the recommendation process. Extensive experiments on a real-world dataset were conducted by comparing HTPR with other three recommendation methods: traditional CF, user-clustering based CF, and item-clustering based CF. The experimental results show that the proposed HTPR method is effective and can improve the accuracy of online recommendation systems for group-buying applications. Full article
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Open AccessArticle
A Model for Evaluating the Performance of the Bearing Manufacturing Process
Appl. Sci. 2019, 9(15), 3105; https://doi.org/10.3390/app9153105 - 31 Jul 2019
Cited by 1
Abstract
Reliability and product process quality are essential in meeting market demand and enhancing competitiveness in the machine tool industry. In addition, manufacturing time performance is also one of the important indices. Therefore, this paper focuses on process quality and manufacturing time and defines [...] Read more.
Reliability and product process quality are essential in meeting market demand and enhancing competitiveness in the machine tool industry. In addition, manufacturing time performance is also one of the important indices. Therefore, this paper focuses on process quality and manufacturing time and defines a manufacturing time performance index to feedback the acceptance rate of the manufacturing time. The process performance evaluation chart delineated the observations of variations in various workstations, and, hence, in controlling the stability of the work process. The Six Sigma quality indices are constructed by the process accuracy indices and precision indices are represented by X-axis and Y-axis respectively. The process quality evaluation chart evaluates the level of the process quality, as well as proposes the direction of improvement. The manufacturing time performance—Z-axis is used to assess whether the manufacturing time performance meets the requirements. The process performance evaluation chart constructed by this paper makes it easier for researchers to observe which workstations have a process variation in the process, to control the stability of the process effectively, to provide the improvement reference for staff on the scene and to enhance the competitiveness of the industry. Full article
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Open AccessArticle
Optimal Maintenance Thresholds to Perform Preventive Actions by Using Multi-Objective Evolutionary Algorithms
Appl. Sci. 2019, 9(15), 3068; https://doi.org/10.3390/app9153068 - 29 Jul 2019
Cited by 1
Abstract
Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the “Industry 4.0” or “fourth industrial revolution”. There are more and more complex systems to maintain, and maintenance management must [...] Read more.
Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the “Industry 4.0” or “fourth industrial revolution”. There are more and more complex systems to maintain, and maintenance management must gain efficiency and effectiveness in order to keep all these devices in proper conditions. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, even though often these programs are complex to manage and understand. For this reason, several research papers propose approaches that are as simple as possible and can be understood by users and modified by experts. In this context, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. In this work, a cost-benefit mathematical model is developed. It considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case. Full article
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Open AccessArticle
Research on Collaborative Optimization of Green Manufacturing in Semiconductor Wafer Distributed Heterogeneous Factory
Appl. Sci. 2019, 9(14), 2879; https://doi.org/10.3390/app9142879 - 18 Jul 2019
Abstract
Production scheduling of semiconductor wafer manufacturing is a challenging research topic in the field of industrial engineering. Based on this, the green manufacturing collaborative optimization problem of the semiconductor wafer distributed heterogeneous factory is first proposed, which is also a typical NP-hard problem [...] Read more.
Production scheduling of semiconductor wafer manufacturing is a challenging research topic in the field of industrial engineering. Based on this, the green manufacturing collaborative optimization problem of the semiconductor wafer distributed heterogeneous factory is first proposed, which is also a typical NP-hard problem with practical application value and significance. To solve this problem, it is very important to find an effective algorithm for rational allocation of jobs among various factories and the production scheduling of allocated jobs within each factory, so as to realize the collaborative optimization of the manufacturing process. In this paper, a scheduling model for green manufacturing collaborative optimization of the semiconductor wafer distributed heterogeneous factory is constructed. By designing a new learning strategy of initial population and leadership level, designing a new search strategy of the predatory behavior for the grey wolf algorithm, which is a new swarm intelligence optimization algorithm proposed in recent years, the diversity of the population is expanded and the local optimum of the algorithm is avoided. In the experimental stage, two factories’ and three factories’ test cases are generated, respectively. The effectiveness and feasibility of the algorithm proposed in this paper are verified through the comparative study with the improved Grey Wolf Algorithms—MODGWO, MOGWO, the fast and elitist multi-objective genetic algorithm—NSGA-II. Full article
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Open AccessArticle
A Comparative Study of the Fitness and Trueness of a Three-Unit Fixed Dental Prosthesis Fabricated Using Two Digital Workflows
Appl. Sci. 2019, 9(14), 2778; https://doi.org/10.3390/app9142778 - 10 Jul 2019
Cited by 2
Abstract
The purpose of this study was to measure and correlate the fitness and trueness of a 3-unit fixed dental prosthesis (FDP) fabricated using two digital workflows. The 3-unit FDPs were fabricated using two digital workflows (N = 15). The digital workflows were [...] Read more.
The purpose of this study was to measure and correlate the fitness and trueness of a 3-unit fixed dental prosthesis (FDP) fabricated using two digital workflows. The 3-unit FDPs were fabricated using two digital workflows (N = 15). The digital workflows were divided into chairside (closed type) and in-lab (open type) groups. The scanning, computer-aided design (CAD), and computer-aided manufacturing (CAM) processes were conducted with 3shape E1 scanner, exocad CAD software, and DDS EZIS HM, respectively, in the in-lab group; and with CEREC omnicam intraoral scanner, CEREC CAD software, and CEREC MC XL, respectively, in the chairside group. The fitness of the fabricated 3-unit FDPs was evaluated by scanning the silicone replica of the cement space and analyzing the thickness of the silicone replica in the three-dimensional (3D) inspection software (Geomagic control X). The trueness of the milling unit was analyzed by 3D analysis of the CAD reference model, which is the design file of the 3-unit FDP, and the CAD test model, which is the scanned file of the 3-unit FDP. In the statistical analysis, comparison of the two groups was conducted by Mann–Whitney U test, and the correlation between the fitness and trueness was conducted by Pearson correlation test (α = 0.05). The marginal and internal fit were significantly lower in the in-lab group at all measurement positions (p < 0.001). The trueness of the milling unit was significantly higher in the in-lab group compared to the chairside group (p < 0.001). There was a positive correlation between the trueness and internal fit (correlation coefficient = 0.621) in the in-lab group (p = 0.013). The use of appropriate equipment in an in-lab (open type) digital workflow enables a better fabrication of 3-unit FDPs than a chairside (closed type) digital workflow, and poor trueness on the inner surface of the crown adversely affects the internal fit. Full article
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Open AccessArticle
Confidence Interval Based Fuzzy Evaluation Model for an Integrated-Circuit Packaging Molding Process
Appl. Sci. 2019, 9(13), 2623; https://doi.org/10.3390/app9132623 - 28 Jun 2019
Cited by 4
Abstract
The electronics industry in Taiwan has achieved a complete information and communication technology chain with a firm position in the global electronics industry. The integrated-circuit (IC) packaging industry chain adopts a professional division of labor model, and each process (including wafer dicing, die [...] Read more.
The electronics industry in Taiwan has achieved a complete information and communication technology chain with a firm position in the global electronics industry. The integrated-circuit (IC) packaging industry chain adopts a professional division of labor model, and each process (including wafer dicing, die bonding, wire bonding, molding, and other subsequent processes) must have enhanced process capabilities to ensure the quality of the final product. Increasing quality can also lower the chances of waste and rework, lengthen product lifespan, and reduce maintenance, which means fewer resources invested, less pollution and damage to the environment, and smaller social losses. This contributes to the creation of a green process. This paper developed a complete quality evaluation model for the IC packaging molding process from the perspective of a green economy. The Six Sigma quality index (SSQI), which can fully reflect process yield and quality levels, is selected as a primary evaluation tool in this study. Since this index contains unknown parameters, a confidence interval based fuzzy evaluation model is proposed to increase estimation accuracy and overcome the issue of uncertainties in measurement data. Finally, a numerical example is given to illustrate the applicability and effectiveness of the proposed method. Full article
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Open AccessArticle
Multiple Convolutional Neural Networks Fusion Using Improved Fuzzy Integral for Facial Emotion Recognition
Appl. Sci. 2019, 9(13), 2593; https://doi.org/10.3390/app9132593 - 26 Jun 2019
Cited by 2
Abstract
Facial expressions are indispensable in human cognitive behaviors since it can instantly reveal human emotions. Therefore, in this study, Multiple Convolutional Neural Networks using Improved Fuzzy Integral (MCNNs-IFI) were proposed for recognizing facial emotions. Since effective facial expression features are difficult to design; [...] Read more.
Facial expressions are indispensable in human cognitive behaviors since it can instantly reveal human emotions. Therefore, in this study, Multiple Convolutional Neural Networks using Improved Fuzzy Integral (MCNNs-IFI) were proposed for recognizing facial emotions. Since effective facial expression features are difficult to design; deep learning CNN is used in the study. Each CNN has its own advantages and disadvantages, thus combining multiple CNNs can yield superior results. Moreover, multiple CNNs combined with improved fuzzy integral, in which its fuzzy density value is optimized through particle swarm optimization (PSO), overcomes the majority decision drawback in the traditional voting method. Two Multi-PIE and CK+ databases and three main CNN structures, namely AlexNet, GoogLeNet, and LeNet, were used in the experiments. To verify the results, a cross-validation method was used, and experimental results indicated that the proposed MCNNs-IFI exhibited 12.84% higher accuracy than that of the three CNNs. Full article
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Open AccessArticle
Development of High-Efficiency, High-Speed and High-Pressure Ambient Temperature Filling System Using Pulse Volume Measurement
Appl. Sci. 2019, 9(12), 2491; https://doi.org/10.3390/app9122491 - 19 Jun 2019
Abstract
Adjusting the filling pressure is essential to fit the final gas volume when charging a carbonated beverage with high pressure. However, in the previous mechanical carbonated ambient filling system, it was difficult to control and monitor the charging conditions such as pressure, temperature [...] Read more.
Adjusting the filling pressure is essential to fit the final gas volume when charging a carbonated beverage with high pressure. However, in the previous mechanical carbonated ambient filling system, it was difficult to control and monitor the charging conditions such as pressure, temperature and flow rate. In this study, we have developed a high efficiency carbonated ambient filling system capable of high speed and high pressure filling, by using a pulse type electronic flow-meter. The response speed characteristics of the M(BC) and F(MH) series valves were investigated. LMS Imagine.Lab Amesim (Siemens PLM Software) was used to calculate the charging and discharging time of the system under a high CO2 gas pressure condition. The quantitative and precise charging system was implemented with the change of filling time and monitoring/controlling/correction of flow rate. Moreover, a dual controller of the high-speed pulse output was established and a high-speed data processing/flow rate charging algorithm was applied in the system. The filling variation of the system was in the range of ±3 gram(gr) (standard deviation 0.57). The developed system could be applied to improve the quality of goods and economic feasibility at various industrial sectors. Full article
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Open AccessArticle
A Pattern Based Method for Simplifying a BPMN Process Model
Appl. Sci. 2019, 9(11), 2322; https://doi.org/10.3390/app9112322 - 05 Jun 2019
Abstract
BPMN (Business Process Model and Notation) is currently the preferred standard for the representation and analysis of business processes. The elaboration of these BPMN diagrams is usually carried out in an entirely manual manner. As a result of this human-driven process, it is [...] Read more.
BPMN (Business Process Model and Notation) is currently the preferred standard for the representation and analysis of business processes. The elaboration of these BPMN diagrams is usually carried out in an entirely manual manner. As a result of this human-driven process, it is not uncommon to find diagrams that are not in their most simplified version possible (regarding the number of elements). This work presents a fully automatic method to simplify a BPMN process model document. A two-phase iterative algorithm to achieve this simplification is described in detail. This algorithm follows a heuristic approach that makes intensive use of a Pattern Repository. This software element is concerned with the description of feasible reductions and its enactment. The critical concept lies in the discovery of small reducible patterns in the whole model and their substitution with optimised versions. This approach has been verified through a double validation testing in total 8102 cases taken from real world BPMN process models. Details for its implementation and usage by practitioners are provided in this paper along with a comparison with other existing techniques concerned with similar goals. Full article
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Open AccessArticle
Comparative Study of the Trueness of the Inner Surface of Crowns Fabricated from Three Types of Lithium Disilicate Blocks
Appl. Sci. 2019, 9(9), 1798; https://doi.org/10.3390/app9091798 - 29 Apr 2019
Cited by 1
Abstract
This study set out to compare the three-dimensional (3D) trueness of crowns produced from three types of lithium disilicate blocks. The working model was digitized, and single crowns (maxillary left second molar) were designed using computer-aided design (CAD) software. To produce a crown [...] Read more.
This study set out to compare the three-dimensional (3D) trueness of crowns produced from three types of lithium disilicate blocks. The working model was digitized, and single crowns (maxillary left second molar) were designed using computer-aided design (CAD) software. To produce a crown design model (CDM), a crown design file was extracted from the CAD software. In addition, using the CDM file and a milling machine (N = 20), three types of lithium disilicate blocks (e.max CAD, HASS Rosetta, and VITA Suprinity) were processed. To produce a crown scan model (CSM), the inner surface of each fabricated crown was digitized using a touch-probe scanner. In addition, using 3D inspection software, the CDM was partitioned (into marginal, axis, angular, and occlusal regions), the CDM and CSM were overlapped, and a 3D analysis was conducted. A Kruskal–Wallis test (α = 0.05) was conducted with all-segmented teeth with the root mean square (RMS), and they were analyzed using the Mann–Whitney U-test and the Bonferroni correction method as a post hoc test. There was a significant difference in the trueness of the crowns according to the type of lithium disilicate block (p < 0.001). The overall RMS value was at a maximum for e.max (42.9 ± 4.4 µm), followed by HASS (30.1 ± 9.0 µm) and then VITA (27.3 ± 7.9 µm). However, there was no significant difference between HASS and VITA (p = 0.541). There were significant differences in all regions inside the crown (p < 0.001). There was a significantly high trueness in the angular region inside the crown (p < 0.001). A correction could thus be applied in the CAD process, considering the differences in the trueness by the type of lithium disilicate block. In addition, to attain a crown with an excellent fit, it is necessary to provide a larger setting space for the angular region during the CAD process. Full article
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Open AccessArticle
An Improved SPEA2 Algorithm with Local Search for Multi-Objective Investment Decision-Making
by Xi Liu and Dan Zhang
Appl. Sci. 2019, 9(8), 1675; https://doi.org/10.3390/app9081675 - 23 Apr 2019
Abstract
Enterprise investment decision-making should not only consider investment profits, but also investment risks, which is a complex nonlinear multi-objective optimization problem. However, traditional investment decisions often only consider profit as a goal, resulting in an incorrect decision. Facing the high complexity of investment [...] Read more.
Enterprise investment decision-making should not only consider investment profits, but also investment risks, which is a complex nonlinear multi-objective optimization problem. However, traditional investment decisions often only consider profit as a goal, resulting in an incorrect decision. Facing the high complexity of investment decision-making space, traditional multi-objective optimization methods pay too much attention to global search ability because of pursuing convergence speed and avoiding falling into local optimum, while local search ability is insufficient, which makes it difficult to converge to the Pareto optimal boundary. To solve this problem, an improved SPEA2 algorithm is proposed to optimize the multi-objective decision-making of investment. In the improved method, an external archive set is set up separately for local search after genetic operation, which guarantees the global search ability and also has strong local search ability. At the same time, the new crossover operator and individual update strategy are used to further improve the convergence ability of the algorithm while maintaining a strong diversity of the population. The experimental results show that the improved method can converge to the Pareto optimal boundary and improve the convergence speed, which can effectively realize the multi-objective decision-making of investment. Full article
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Review

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Open AccessReview
The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review
Appl. Sci. 2019, 9(18), 3865; https://doi.org/10.3390/app9183865 - 14 Sep 2019
Cited by 7
Abstract
Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, [...] Read more.
Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations. Full article
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