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Processes
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Big Data in Manufacturing, Biology, Healthcare and Life Sciences
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Big Data in Manufacturing, Biology, Healthcare and Life Sciences

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 45166

Special Issue Editors

Dr. Jun-Ho Huh

E-Mail Website1 Website2
Guest Editor
Department of Data Science, National Korea Maritime and Ocean University, Busan 49112, Republic of Korea
Interests: AI; big data; virtualization; shipbuilding industry; shipping industry; Industry 4.0
Special Issues, Collections and Topics in MDPI journals
Dr. Yeong-Seok Seo

E-Mail Website
Guest Editor
Department of Computer Engineering, Yeungnam University, Gyeongsan 38541, Gyeongbuk, Republic of Korea
Interests: data analysis; artificial intelligence; software engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

An individual’s genetic information amounts to just about 3 MB (megabytes), and the genetic information of the global population could reach up to 24 billion MB. The necessity of a Big Data processing system that can handle such a volume is clear, and the future of life science research depends on acquiring or developing such a system. This Special Issue aims to collect research and discussion on Big Data processing systems in the field of bioinformatics or biostatics, which involves visualization of life science Big Data using IRB-approved Big Data processing methodologies and visualization techniques.

This Special Issue will also present studies discussing how to apply these methodologies to understand the issues involved with diverse social phenomena or businesses.

For example, the paradigms of shipbuilding and shipping industries are shifting to the design and manufacture of autonomous surface ships. A (whole) life-cycle smartification is increasingly adopted in these industries, and yet a variety of accidents or problems (DNA analysis for the identification of fatal accidents in shipbuilding; environmental pollution from ballast water; environmental pollution and protection; safety and protection in the manufacturing industry; healthcare) occurring in shipbuilding or operation processes remain to be solved. Additionally, most of the data such as wind directions or wave heights are being utilized for the operation of ship prediction systems, but the lack of available real-time data needed to compensate or correct prediction results has to be dealt with, especially when it is necessary to perform digital forensics.

In this regard, this Special Issue attempts to focus on the generation and construction of Big Data to take initiative in the development of advanced detection equipment/systems, tools/materials, and intelligent systems and deal with international standards, expecting to lay a foundation for the commercialization of autonomous surface ships.

Topics of interested include but are not limited to:

  • Big Data in Manufacturing.
  • Big Data in Biology.
  • Big Data in Healthcare.
  • Big Data in Life Sciences.
  • Generation and construction of Big Data to take initiative in the development of advanced detection equipment/systems, tools/materials, and intelligent systems in response to international standards.
  • Classification of Big Data Sets into ‘Big Data Collection’ and ‘Analyzed Data’, standardization and quality test techniques.
  • Collection and analysis of the Big Data that can correct positions or predict marine accidents in addition to the conditions of shipbuilding materials based on the database constructed.
  • Establishment of Big Data generation, analysis, and distribution plans considering the life cycle of data.
  • Establishment of a ground for data fusion between the data platforms to be linked together after constructing a system for data generation, analysis, and distribution.
  • Ethical solutions to artificial intelligence and Big Data.

Prof. Dr. Jun-Ho Huh
Prof. Dr. Yeong-Seok Seo
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. Processes is an international peer-reviewed open access monthly 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 2000 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.

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14 pages, 1132 KiB  
Article
A Feasible Framework for Maintenance Digitalization
by Umair Ahmed, Silvia Carpitella, Antonella Certa and Joaquín Izquierdo
Processes 2023, 11(2), 558; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11020558 - 11 Feb 2023
Cited by 6 | Viewed by 2058
Abstract
The entire industry is changing as a result of new developments in digital technology, and maintenance management is a crucial procedure that may take advantage of the opportunities brought about by industrial digitalization. To support digital innovation in maintenance management, this study intends [...] Read more.
The entire industry is changing as a result of new developments in digital technology, and maintenance management is a crucial procedure that may take advantage of the opportunities brought about by industrial digitalization. To support digital innovation in maintenance management, this study intends to meet the cutting-edge necessity of addressing a transformation strategy in industrial contexts. Setting up a customized pathway with adequate methodologies, digitalization tools, and collaboration between the several stakeholders involved in the maintenance environment is the first step in this process. The results of a previous conference contribution, which revealed important digitalization variables in maintenance management, served as the foundation for the research approach herein suggested. We lead a thorough assessment of the literature to categorize the potential benefits and challenges in maintenance digitalization to be assessed in conjunction with the important digitalization aspects previously stated. As a starting point for maintenance management transformation, we offer a feasible framework for maintenance digitalization that businesses operating in a variety of industries can use. As industrial processes and machines have become more sophisticated and complex and as there is a growing desire for more secure, dependable, and safe systems, we see that this transition needs to be tailored to the specific application context. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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11 pages, 4276 KiB  
Article
Coarse X-ray Lumbar Vertebrae Pose Localization and Registration Using Triangulation Correspondence
by Watcharaphong Yookwan, Sornsupha Limchareon, Sang-Hun Lee, Jun-Su Jang, Daesung Lee and Krisana Chinnasarn
Processes 2023, 11(1), 61; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11010061 - 27 Dec 2022
Cited by 2 | Viewed by 1482
Abstract
Plain film X-ray scanners are indispensable for medical diagnostics and clinical procedures. This type of device typically produces two radiographic images of the human spine, including the anteroposterior and lateral views. However, these two photographs presented perspectives that were distinct. The proposed procedure [...] Read more.
Plain film X-ray scanners are indispensable for medical diagnostics and clinical procedures. This type of device typically produces two radiographic images of the human spine, including the anteroposterior and lateral views. However, these two photographs presented perspectives that were distinct. The proposed procedure consists of three fundamental steps. For automated cropping, the grayscale lumbar input image was initially projected vertically using its vertical pattern. Then, Delaunay triangulation was performed with the SURF features serving as the triangle nodes. The posture area of the vertebrae was calculated by utilizing the edge density of each node. The proposed method provided an automated estimation of the position of the human lumbar vertebrae, thereby decreasing the radiologist’s workload, computing time, and complexity in a variety of bone-clinical applications. Numerous applications can be supported by the results of the proposed method, including the segmentation of lumbar vertebrae pose, bone mineral density examination, and vertebral pose deformation. The proposed method can estimate the vertebral position with an accuracy of 80.32 percent, a recall rate of 85.37 percent, a precision rate of 82.36%, and a false-negative rate of 15.42 percent. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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13 pages, 546 KiB  
Article
The Effect of Medical Device Regulations on Deploying a Lean Six Sigma Project
by Vincent McGrane, Olivia McDermott, Anna Trubetskaya, Angelo Rosa and Michael Sony
Processes 2022, 10(11), 2303; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10112303 - 05 Nov 2022
Cited by 4 | Viewed by 3730
Abstract
This paper investigates the differences in timelines involved in Lean Six Sigma (LSS) project deployment in a regulated industry versus in an unregulated one. Two case studies utilising Lean Six Sigma methods—in order to compare the transfer of manual manufacturing lines within a [...] Read more.
This paper investigates the differences in timelines involved in Lean Six Sigma (LSS) project deployment in a regulated industry versus in an unregulated one. Two case studies utilising Lean Six Sigma methods—in order to compare the transfer of manual manufacturing lines within a medical device and electronics manufacturing site—are discussed and utilised. This research aims to show the effects of regulatory procedures on LSS project implementation and timelines. This study particularly highlights how a regulatory environment can be a barrier, or bottleneck, to project management, continuous improvement, and engineering changes in the MedTech or medical device manufacturing industry. The results of this study represent an important first step towards a full understanding of the influence of regulations on operations in medical devices and, by extension, on pharmaceutical manufacturing industries on a global scale. The research limitations are that the data collected were from two specific case study comparisons alone. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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14 pages, 446 KiB  
Article
“Song of Life”: A Comprehensive Evaluation of Biographical Music Therapy in Palliative Care by the EMW-TOPSIS Method
by Zhiyuan Zhang, Zhihao Jiang, Biju Yin, Zhongxiang Chen and Xiaoyang Peng
Processes 2022, 10(10), 1962; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10101962 - 29 Sep 2022
Cited by 1 | Viewed by 1880
Abstract
The “Song of Life (SOL)” is a kind of music therapy in palliative care for addressing emotional and existential needs in terminally ill patients nearing the end of life. Few previous studies focus on objective data analysis methods to validate the effectiveness of [...] Read more.
The “Song of Life (SOL)” is a kind of music therapy in palliative care for addressing emotional and existential needs in terminally ill patients nearing the end of life. Few previous studies focus on objective data analysis methods to validate the effectiveness of psychotherapy therapy for patients’ overall state. This article combines the entropy weighting method (EWM) and the technique for order preference by similarity to the ideal solution (TOPSIS) method to evaluate the effectiveness of SOL music therapy and the treatment satisfaction of the patients and family members. Firstly, the collaborative filtering algorithm (CFA) machine learning algorithm is used to predict the missing ratings a patient might have given to a variable. Secondly, the EWM determines the weights of quality of life, spiritual well-being, ego-integrity, overall quality of life, and momentary distress. Thirdly, the EWM method is applied for the TOPSIS evaluation model to evaluate the patient’s state pre- and post-intervention. Finally, we obtain the state change in patients and recognition based on the feedback questionnaire. The multiple criteria decision making (MCDM) comprehensive evaluation method objectively validated the overall effectiveness of SOL music therapy. Based on MCDM method, we provide a new approach for judging the overall effect of psychological intervention and accurately recommend psychotherapy that fits the symptoms of psychological disorders. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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15 pages, 1328 KiB  
Article
Managing Engineering Change within the Paradigm of Product Lifecycle Management
by Hassan Habib, Rashid Menhas and Olivia McDermott
Processes 2022, 10(9), 1770; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10091770 - 03 Sep 2022
Cited by 3 | Viewed by 2972
Abstract
Managing change in organizations is a laborious task that consumes value added time in various segments of the product lifecycle including design and development, production, delivery, and product disposition. Product lifecycle management plays an important role in minimizing the time required for managing [...] Read more.
Managing change in organizations is a laborious task that consumes value added time in various segments of the product lifecycle including design and development, production, delivery, and product disposition. Product lifecycle management plays an important role in minimizing the time required for managing engineering changes. This research aims to perform an extensive survey of the literature in this area. There is no consolidated review available in this area summarizing advances in engineering change management vis-à-vis product lifecycle management. Thus, the paper gives an overview of product lifecycle management-based thinking and change management. This review puts forward the most relevant research regarding the practices and frameworks developed for managing engineering change in an organization. These include model-based definition, digital twin, process-based semantic approach, service-oriented architecture, Unified Modeling Language, and unified feature modeling. The gaps between the extents of conformance to success factors have been identified as extent of integration, standardization, versatility of application, support of existing systems, and the extent of product lifecycle management support. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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22 pages, 14834 KiB  
Article
A DEM-Based Modeling Method and Simulation Parameter Selection for Cyperus esculentus Seeds
by Tianyue Xu, Ruxin Zhang, Fengwu Zhu, Weizhi Feng, Yang Wang and Jingli Wang
Processes 2022, 10(9), 1729; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10091729 - 31 Aug 2022
Cited by 3 | Viewed by 1084
Abstract
To build a DEM model of Cyperus esculentus seed particles, the shape and size of the Cyperus esculentus seed particles were measured and analyzed. The results showed that the dispersity in size had a normal distribution. Additionally, a certain functional relationship between the [...] Read more.
To build a DEM model of Cyperus esculentus seed particles, the shape and size of the Cyperus esculentus seed particles were measured and analyzed. The results showed that the dispersity in size had a normal distribution. Additionally, a certain functional relationship between the primary dimension and secondary dimensions was determined. The width of the seed was the primary dimension, and the other secondary dimensions (length and thickness) were calculated based on their relationships with the primary dimension. On this basis, an approach for modeling Cyperus esculentus seed particles based on the multi-sphere (MS) method was proposed. The discrete element analysis models of three varieties of Cyperus esculentus seeds were established with different numbers of filing spheres. Moreover, to obtain more accurate simulation parameters, first, a range of values of the simulation parameters was obtained by the experimental method. Second, the Plackett–Burman (PB) test and the path of steepest ascent method were both adopted to correct and calibrate the simulation parameters, which were difficult to obtain through experiments, and simulation of the direct shear test was used for calibration. All of the methods guaranteed that the selected parameters were reasonable. The test results showed that the static friction coefficient of seed–seed had a significant effect on the simulation results. Finally, piling tests and the bulk density test were used for modeling verification. By comparing the simulated results and experimental results in the piling tests and bulk density test, when the number of filing spheres increased, the simulated results were close to those obtained experimentally. Therefore, the feasibility and validity of the modeling method for Cyperus esculentus seed particles that we proposed and the simulation parameters that were obtained were verified. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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11 pages, 3330 KiB  
Article
A Digital Process for Manufacturing Customized Trays for Dental-Whitening Treatments
by Francesco Tamburrino, Beatrice Aruanno, Armando V. Razionale, Sandro Barone, Marco Martini and Monica Bordegoni
Processes 2022, 10(7), 1232; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10071232 - 21 Jun 2022
Cited by 2 | Viewed by 1456
Abstract
This study presents an alternative process for designing and manufacturing customized trays for dental-whitening treatments. The process is based on a digitized approach consisting of three main stages: design of a reference model, its manufacturing by AM, and thermoforming of the tray. The [...] Read more.
This study presents an alternative process for designing and manufacturing customized trays for dental-whitening treatments. The process is based on a digitized approach consisting of three main stages: design of a reference model, its manufacturing by AM, and thermoforming of the tray. The aim of the study was to develop a high-performance tray, able to guarantee comfort, safety, and efficacy for whitening treatments. To evaluate the patient’s experience, some tests under real operating conditions were performed. Twenty people carried out a nighttime treatment of 14 days. Each patient was asked to assess the overall level of satisfaction and the comfort of the tray and its ability to retain the gel. Tooth whitening was also determined according to the VITAPAN scale. All patients involved in the study were satisfied and provided positive feedback about comfort and tightness of the tray. At the end of the treatment, 15 out of 20 patients achieved shade A1 on the VITAPAN scale. The mean improvement in color shades was about 7. These results confirmed the great potential of the proposed dental tray. Its use was proven to guarantee a high level of quality, flexibility, and customization of dental-whitening treatments, improving comfort, safety, and efficacy. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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15 pages, 6057 KiB  
Article
Simulation and Analysis of the Working Process of Soil Covering and Compacting of Precision Seeding Units Based on the Coupling Model of DEM with MBD
by Tianyue Xu, Ruxin Zhang, Yang Wang, Xinming Jiang, Weizhi Feng and Jingli Wang
Processes 2022, 10(6), 1103; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10061103 - 01 Jun 2022
Cited by 7 | Viewed by 1723
Abstract
In precision seeding, the final displacements of the seeds are determined as a working result of the profiling mechanism, opener, seed-metering device, covering apparatus and compacting machine. For a better understanding of the disturbance of seed displacement during soil covering and compaction in [...] Read more.
In precision seeding, the final displacements of the seeds are determined as a working result of the profiling mechanism, opener, seed-metering device, covering apparatus and compacting machine. For a better understanding of the disturbance of seed displacement during soil covering and compaction in the actual working process, experiments and simulations have been performed. In this paper, a type of soybean seeding monomer was taken as the research object, and a soil bin test of soil covering and compacting was executed. The experimental results showed that the traction velocity and the open angle of the covering discs had a significant influence on the changes in the horizontal and vertical displacements of seeds during the soil covering processing. With an increasing traction velocity, the vertical displacements of seeds increased after soil covering; in contrast, the horizontal displacements decreased. When the covering apparatus had a larger open angle it had a smaller disturbance influence on the soil. Therefore, with an increase in the opening angle, the changes in the vertical and horizontal displacements of seeds showed a decreasing trend. Inversely, in the process of compacting, the forward velocity had little effect on the three-dimensional displacement change in the seeds after compacting. The analysis model of the precision seeding unit was established based on the coupling model of the DEM (discrete element method) with MBDs (multi-body dynamics). The process of soil covering and compacting was simulated and analyzed. The comparison between the experimental results and the simulated results showed that the trend was similar, and the two results were close. Thus, the feasibility and applicability of the coupling method were verified. It also provided a new method for the design and optimization of covering and compacting components of a precise seeding monomer. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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13 pages, 6137 KiB  
Article
Time-Jerk optimal Trajectory Planning of Industrial Robots Based on a Hybrid WOA-GA Algorithm
by Fang Wang, Zhijun Wu and Tingting Bao
Processes 2022, 10(5), 1014; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10051014 - 19 May 2022
Cited by 13 | Viewed by 2273
Abstract
An optimal and smooth trajectory for industrial robots has a positive impact on reducing the execution time in an operation and the vibration in their joints. In this paper, a methodology for the time-optimal and jerk-continuous trajectory planning of industrial robots is proposed. [...] Read more.
An optimal and smooth trajectory for industrial robots has a positive impact on reducing the execution time in an operation and the vibration in their joints. In this paper, a methodology for the time-optimal and jerk-continuous trajectory planning of industrial robots is proposed. The entire trajectory is interpolated in the joint space utilizing fifth-order B-splines and then optimized by a hybrid whale optimization algorithm and genetic algorithm (WOA-GA). Two objective functions, including the integral of the squared jerk along the entire trajectory and the total execution time, are minimized to obtain the optimal entire trajectory. A fifth-order B-spline interpolation technique enables the achievement of a jerk-continuous trajectory, while respecting the kinematic limits of jerk, acceleration and velocity. WOA-GA is utilized to solve the time-jerk optimal trajectory planning problem with nonlinear constraints. The proposed hybrid optimization algorithm yielded good results and achieved the time-jerk optimal trajectory better under kinematic constraints compared to the genetic algorithm, whale optimization algorithm, improved whale optimization algorithm with particle swarm optimization and adaptive cuckoo search algorithm. The numerical results show the competent performances of the proposed methodology to generate trajectories with high smooth curves and short total execution time. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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14 pages, 8851 KiB  
Article
Structural Analysis and Optimization of Heavy Vehicle Chassis Using Aluminium P100/6061 Al and Al GA 7-230 MMC
by Abhishek Agarwal and Linda Mthembu
Processes 2022, 10(2), 320; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10020320 - 08 Feb 2022
Cited by 6 | Viewed by 4583
Abstract
A chassis is one of the vital parts of a heavy motor vehicle, which provides rigidity to the vehicle and improves structural stability and rigidity for accurate handling. The design and material of a chassis structure significantly affects its strength and weight. Optimization [...] Read more.
A chassis is one of the vital parts of a heavy motor vehicle, which provides rigidity to the vehicle and improves structural stability and rigidity for accurate handling. The design and material of a chassis structure significantly affects its strength and weight. Optimization techniques can be used in systematic design improvement of chassis to meet industry requirements. The current research is intended to optimize the design of chassis using the Box–Behnken design scheme and the material tested is P100/6061 Al and Al GA 7-230 MMC. Different design points were generated using the design of the experiments. Equivalent stress, deformation and mass were evaluated for each design point. The variable selected for optimization using the Box–Behnken scheme was cross member width. The CAD modelling and FE simulation of the heavy motor vehicle chassis were conducted using ANSYS software. From the optimization conducted on the chassis design, response surface plots of equivalent stress, deformation and mass were generated, which enabled to determine the range of dimensions for which these parameters are maximum or minimum. The sensitivity plots of different variables were generated, which has shown that cross member 2’s width has a maximum effect on equivalent stress and cross member 3’s width has a minimum effect on equivalent stress, whereas for total deformation, cross member 3 shows the maximum sensitivity percentage, which signifies that cross member 3 has the maximum effect on total deformation, and vice versa. The use of the aluminium metal matrix composites P100/6061 Al and Al GA 7-230 MMC aided to reduce the weight of the chassis by 68% and 70%, respectively, without much reduction in the strength of the chassis. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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22 pages, 4977 KiB  
Article
Multi-Indicators Decision for Product Design Solutions: A TOPSIS-MOGA Integrated Model
by Zeyuan Yu, Wu Zhao, Xin Guo, Huicong Hu, Chuan Fu and Ying Liu
Processes 2022, 10(2), 303; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10020303 - 03 Feb 2022
Cited by 6 | Viewed by 1949
Abstract
Design decisions occur in all phases of product design and largely affect the merits of the final solution, which will ultimately determine the success or failure of the product in the market. Product design is a continuous process, and a large number of [...] Read more.
Design decisions occur in all phases of product design and largely affect the merits of the final solution, which will ultimately determine the success or failure of the product in the market. Product design is a continuous process, and a large number of existing studies have proposed decision methods and decision indicators for the characteristics of different stages of design. These methods and indicators can meet the requirements of one of the phases: demand analysis, conceptual design, or detailed design. However, further research can still be conducted on the integration of methods throughout the design phase, using intelligent design methods, and improving the design continuity and efficiency. To address this problem, a TOPSIS-MOGA-based multi-indicators decision model for product design solutions is proposed, including its product design process, decision algorithm, and selection method. First, a TOPSIS-MOGA integrated model for conceptual design and detailed design process is established, the continuity of decision-making methods is achieved by integrating decision indicators. Second, conceptual design solutions are selected through the technique for order of preference by similarity to ideal solution (TOPSIS), based on hesitant fuzzy linguistic term sets and entropy weight method. Finally, detailed design solutions are selected through a multiobjective genetic algorithm (MOGA), based on a polynomial-based response surface model and central combination experimental design method. A case study of the decision-making in the design of high-voltage electric power fittings is presented, the conceptual design phase and the detailed design phase are connected through the indicators, which demonstrates that the proposed approach is helpful in the decision-making of the product design solutions. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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11 pages, 948 KiB  
Article
Reliability Estimation in Multicomponent Stress-Strength Based on Inverse Weibull Distribution
by Ahmed Ibrahim Shawky and Khushnoor Khan
Processes 2022, 10(2), 226; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10020226 - 25 Jan 2022
Cited by 6 | Viewed by 2304
Abstract
The present study focuses on the multi-component stress-strength (MCSS) model based on inverse Weibull distribution (IWD). Both stress and strength are assumed to follow IWD with a common shape parameter. In such a system, reliability is obtained by the maximum likelihood (ML) method. [...] Read more.
The present study focuses on the multi-component stress-strength (MCSS) model based on inverse Weibull distribution (IWD). Both stress and strength are assumed to follow IWD with a common shape parameter. In such a system, reliability is obtained by the maximum likelihood (ML) method. The results are extracted using Monte Carlo simulation for comparing the performance of the reliability component Rs,k using different sample sizes and different combinations of the parameters (s,k). The procedure is further illustrated through a real data set to show how the proposed technique may be employed to study the strength and stress of multicomponent model. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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19 pages, 2561 KiB  
Article
Barriers and Enablers for Continuous Improvement Methodologies within the Irish Pharmaceutical Industry
by Olivia McDermott, Jiju Antony, Michael Sony and Stephen Daly
Processes 2022, 10(1), 73; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10010073 - 30 Dec 2021
Cited by 26 | Viewed by 6372
Abstract
This study aims to investigate the barriers that exist when implementing continuous improvement methodologies, such as Lean Six Sigma (LSS), within the Irish Pharma industry. The main finding of this study is that 45% of participants perceived that a highly regulated environment could [...] Read more.
This study aims to investigate the barriers that exist when implementing continuous improvement methodologies, such as Lean Six Sigma (LSS), within the Irish Pharma industry. The main finding of this study is that 45% of participants perceived that a highly regulated environment could be a barrier to continuous improvement implementation, while 97% of respondents utilised Continuous improvement (CI) methods, such as Lean, Six Sigma, and LSS, within their organisations. While the International Conference of Harmonisation integrates CI into its Pharmaceutical Quality Systems (PQS) regulations, the highest motivation for CI implementation amongst the Irish Pharma industry is to improve Productivity and Quality. The main obstacles highlighted for CI implementation in Pharma attributed to stringent regulatory regimes were fear of extra validation activity, a compliance versus quality culture, and a regulatory culture of being “safe”. Another relevant finding presented in this paper is that participants CI LSS tools are very strongly integrated into the pharma industries corrective and preventative action system, deviations, and internal audit systems. Limitations of the research are that all the data collected in the survey came from professionals working for multinational Pharmaceutical companies based in Ireland. The authors understand that this is the first research focused on the barriers and status of CI initiatives in the pharmaceutical industry. The results of this study represent an important step towards understanding the enablers and obstacles for the use of continuous improvement methodologies in pharmaceutical manufacturing industries on a global scale. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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21 pages, 17807 KiB  
Article
Research on Collaborative Efficiency Evaluation of Complex Supplier Network under the Background of Intelligent Manufacturing
by Minghao Zhang, Li Shi, Xiangzhi Zhuo and Yuan Liu
Processes 2021, 9(12), 2158; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9122158 - 29 Nov 2021
Cited by 3 | Viewed by 1703
Abstract
Supplier network collaborative efficiency evaluation is important content in the transformation and upgrading of intelligent manufacturing enterprises. Aiming at the shortcomings of existing methods, this paper proposes a new method to evaluate the collaborative efficiency of internal members of a complex supplier network [...] Read more.
Supplier network collaborative efficiency evaluation is important content in the transformation and upgrading of intelligent manufacturing enterprises. Aiming at the shortcomings of existing methods, this paper proposes a new method to evaluate the collaborative efficiency of internal members of a complex supplier network based on complex network theory. Based on the analysis of the characteristics of the complex supplier network, from the perspective of the system, the macro supplier network is divided into multiple multi-level supplier micro subsystems with manufacturing enterprises as the core. In order to reasonably quantify the collaboration relationship of members in the subsystem structure model, the collaboration entropy is introduced as a measurement tool, and combined with the hesitation fuzzy scoring function, and the collaborative evaluation model of the complex supplier network is constructed. By quantifying the collaboration relationship among the members in the subsystem and summarizing it step by step and iteratively, the collaborative efficiency evaluation of the complex supplier network from local to overall is realized. Finally, taking a large battery manufacturing enterprise in China as an example, the proposed method is used to calculate the collaboration entropy, collaborative efficiency, and collaboration ratio of members at different supplier network levels. The results verify the effectiveness of the model. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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20 pages, 12318 KiB  
Article
Numerical Modelling and Multi Objective Optimization Analysis of Heavy Vehicle Chassis
by Abhishek Agarwal and Linda Mthembu
Processes 2021, 9(11), 2028; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9112028 - 13 Nov 2021
Cited by 11 | Viewed by 4240
Abstract
The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a [...] Read more.
The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a heavy motor vehicle chassis using numerical and experimental methods. The CAD design and FE analysis is conducted using the ANSYS software. The design of the chassis is then optimized using Taguchi design of Experiments (DOE); the optimization techniques used are the central composite design (CCD) scheme and optimal space filling (OSF) design. Thereafter, sensitivity plots and response surface plots are generated. These plots allow us to determine the critical range of optimized chassis geometry values. The optimization results obtained from the CCD design scheme show that cross member 1 has a higher effect on the equivalent stresses as compared to cross members 2 and 3. The chassis mass reduction obtained from the CCD scheme is approximately 5.3%. The optimization results obtained from the OSF scheme shows that cross member 2 has a higher effect on equivalent stress as compared to cross members 1 and 3. The chassis mass reduction obtained from optimal space filling design scheme is approximately 4.35%. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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19 pages, 11575 KiB  
Review
A Review on Observer Assistance Systems for Harvested and Protected Fish Species
by Taehoon Koh and Yonghoon Kim
Processes 2023, 11(4), 1261; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11041261 - 19 Apr 2023
Viewed by 796
Abstract
Restrictions on competitive fishing activities due to the depletion of living marine resources and the monitoring of fish resources for the purpose of marine ecosystem research are supported by statistics on the protection of fish resources and ecosystem research, which are gathered through [...] Read more.
Restrictions on competitive fishing activities due to the depletion of living marine resources and the monitoring of fish resources for the purpose of marine ecosystem research are supported by statistics on the protection of fish resources and ecosystem research, which are gathered through existing observer monitoring systems. However, in the case of deep-sea fishing vessels and special-purpose fishing vessels, some matters, such as collusive transactions with shipping companies and shipowners and threats toward the observer, are problematic, as observers are always active on board. Therefore, through the present study we would like to discuss the methodology and directions for research on the independent role of the observer and the methods for improving the reliability of data through systems that automate the monitoring of the acquisition of fish resources, which is expected to be a continuing problem. After an analysis of research trends for each issue related to the electronic monitoring system, future research directions are suggested on the basis of the findings, and for the research currently in progress, this paper presents the results from a prediction server and client and an image collector. In order to use these in the field in the future, as the detection method and reliability of the electronic monitoring system that can automate self-learning should be improved, we describe the image transmission technology, the image recognition technology for studying fish, and the methodology for calculating the yield. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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24 pages, 3266 KiB  
Review
Overview of Fire Prevention Technologies by Cause of Fire: Selection of Causes Based on Fire Statistics in the Republic of Korea
by Hoon-Gi Lee, Ui-Nam Son, Seung-Mo Je, Jun-Ho Huh and Jae-Hun Lee
Processes 2023, 11(1), 244; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11010244 - 12 Jan 2023
Cited by 1 | Viewed by 2643
Abstract
Every year, diverse types of safety accidents cause major damage to human life and property. In particular, failure to suppress safety accidents caused by fires during the early stages can lead to large-scale accidents, which in turn can cause more serious damage than [...] Read more.
Every year, diverse types of safety accidents cause major damage to human life and property. In particular, failure to suppress safety accidents caused by fires during the early stages can lead to large-scale accidents, which in turn can cause more serious damage than other types of accident. Therefore, this paper presents an analysis of the prevailing research trends and future directions for research on preventing safety accidents due to fire. Since fire outbreaks can occur in many types of places, the study was conducted by selecting the places and causes involved in frequent fires, using fire data from Korea. As half of these fires were found to occur in buildings, this paper presents an analysis of the causes of building fires, and then focuses on three themes: fire prevention based on fire and gas detection; fire prevention in electrical appliances; and fire prevention for next-generation electricity. In the gas detection of the first theme, the gas referred to does not denote a specific gas, but rather to the gas used in each place. After an analysis of research trends for each issue related to fire prevention, future research directions are suggested on the basis of the findings. It is necessary to evaluate the risk, select a detection system, and improve its reliability in order to thoroughly prevent fires in the future. In addition, an active emergency response system should be developed by operating a fire prevention control system, and safety training should be developed after classifying the targets of the training targets appropriately. Full article
(This article belongs to the Special Issue Big Data in Manufacturing, Biology, Healthcare and Life Sciences)
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