Processes

Research

21 pages, 13098 KiB

Open AccessFeature PaperArticle

Improving the Efficiency of the Bowden Cable Terminal Injection Process for the Automotive Industry

by José L. T. A. Pereira, Raul D. S. G. Campilho, Francisco J. G. Silva, Isidro J. Sánchez-Arce, Chander Prakash and Dharam Buddhi

Processes 2022, 10(10), 1953; https://doi.org/10.3390/pr10101953 - 28 Sep 2022

Cited by 5 | Viewed by 2447

Abstract

Control cables transfer force between two separate locations by a flexible mean, and hence, they are important in the automotive industry and many others; their terminals interact with both moving and moved mechanisms, so they must be strong. Cable terminals are commonly made [...] Read more.

Control cables transfer force between two separate locations by a flexible mean, and hence, they are important in the automotive industry and many others; their terminals interact with both moving and moved mechanisms, so they must be strong. Cable terminals are commonly made of ZAMAK and are created by injection molding. However, such a production method requires leaving extra material to allow the correct molding, also known as sprues, which are removed later in the process. In this case, the sprues were separating from the terminals in an uncontrolled way. In this work, the cause of sprues separating prematurely from the terminals in a production line is addressed. The whole process was analyzed, and each possible solution was evaluated using process improvement techniques and the Finite Element Method, leading to the best solutions. Molds, mold structures, and auxiliary equipment were improved, resulting in a minimally invasive intervention and remaining compatible with other equipment. Cost analyses were done, indicating an investment return in less than a year. The modification led to a reduction of 62.6% in the sprue mass, while porosity was reduced by 10.2% and 55.9%, corresponding to two terminal models. In conclusion, the interventions fulfilled the requirements and improved the operation of the line. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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19 pages, 5248 KiB

Open AccessArticle

Test and Simulation Analysis of Soybean Seed Throwing Process

by Dongxu Yan, Jianqun Yu, Na Zhang, Ye Tian and Lei Wang

Processes 2022, 10(9), 1731; https://doi.org/10.3390/pr10091731 - 1 Sep 2022

Cited by 4 | Viewed by 1785

Abstract

In order to analyze the effect of different factors on the bouncing and rolling distance of soybeans at the time of seed throwing, tests and discrete element method (DEM) are employed to analyze test soil and three representative soybean varieties. The parameters between [...] Read more.

In order to analyze the effect of different factors on the bouncing and rolling distance of soybeans at the time of seed throwing, tests and discrete element method (DEM) are employed to analyze test soil and three representative soybean varieties. The parameters between soybean seed particles and soil particles are calibrated by means of a piling test and simulation. A seed throwing test apparatus is improved to analyze the effects of seed throwing height, soil plane inclination angle and collision orientation on the bouncing and rolling distance of soybean seeds. The effect of relative seed throwing speed on the bouncing and rolling distance of soybean seeds is analyzed using a computer vision seeding test bench. On this basis, the above-mentioned test procedure is simulated and compared with the test results. The results showed that the bouncing distance of the soybean seed particles was not significant. The rolling distance had a certain randomness when the seed throwing height was different. When the inclination of the soil plane became larger, the rolling distance increased. When the sphericity of the soybean seed particles was high, the effect of different collision orientations was not obvious. If the sphericity was low, the rolling distance was the shortest when colliding in the horizontal orientation and the longest when colliding in the vertical orientation. The larger the relative seed throwing speed, the larger the rolling distance of the soybean seed particles. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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19 pages, 2534 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Different Approaches to the Creation of a Mathematical Model of Melt Temperature in an LD Converter

by Marek Laciak, Ján Kačur, Ján Terpák, Milan Durdán and Patrik Flegner

Processes 2022, 10(7), 1378; https://doi.org/10.3390/pr10071378 - 14 Jul 2022

Cited by 3 | Viewed by 1785

Abstract

In the steel production process in the LD converter, it is important to have information about the melt temperature. The temperature and chemical composition of the steel are important parameters in this process in terms of its completion. During the process, continuous measurement [...] Read more.

In the steel production process in the LD converter, it is important to have information about the melt temperature. The temperature and chemical composition of the steel are important parameters in this process in terms of its completion. During the process, continuous measurement of the melt temperature and thus also information about the end of the process are missing. This paper describes three approaches to creating a mathematical model of melt temperature. The first approach is a regression model, which predicts an immeasurable melt temperature based on other directly measured process variables. The second approach to creating a mathematical model is based on the machine learning method. Simple and efficient learning algorithms characterize the machine learning methods. We used support vector regression (SVR) method and the adaptive neuro-fuzzy inference system (ANFIS) to create a mathematical model of the melt temperature. The third approach is the deterministic approach, which is based on the decomposition of the process and its heat balance. The mathematical models that were compiled based on the mentioned approaches were verified and compared to real process data. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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19 pages, 4329 KiB

Open AccessArticle

Using Linkography and Situated FBS Co-Design Model to Explore User Participatory Conceptual Design Process

by Juan Cao, Wu Zhao, Huicong Hu, Yeqi Liu and Xin Guo

Processes 2022, 10(4), 713; https://doi.org/10.3390/pr10040713 - 6 Apr 2022

Cited by 2 | Viewed by 2542

Abstract

To unravel the complex challenges addressed by product innovation, it is oftentimes essential for users to participate in the design process. However, there is a paucity of research in terms of in-depth exploration of the cognitive patterns and dynamic design processes of co-design [...] Read more.

To unravel the complex challenges addressed by product innovation, it is oftentimes essential for users to participate in the design process. However, there is a paucity of research in terms of in-depth exploration of the cognitive patterns and dynamic design processes of co-design with user participation in the existing design cognition research. The current study aimed to investigate the cognition activities involved in the process of co-design between user and designer at both the individual and team levels. The combination method of linkography and the situated function–behavior–structure (FBS) co-design model was carried out to encode and analyze the protocol data. The results showed that, at the individual level, designers and users adopted different design strategies to promote the progress of the design. In addition, the interaction activities among users and designers varied in different co-design processes. However, at the team level, the collaborators showed systematic thinking modes, and each design move was two-way. This cognitive strategy of the innovation team ensured the continuity and effectiveness of the co-design process. Theoretically, these findings will bring new insights for studies on team cognition activities and contribute to building user-centric design theory by uncovering the dynamic design processes of co-design with user participatory. In addition, the study makes a methodological contribution by illustrating how linkography and the situated FBS co-design model can be utilized to analyze the team cognition during co-design activities. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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26 pages, 3897 KiB

Open AccessArticle

Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment

by Nikolay Viktorovich Baranovskiy and Viktoriya Andreevna Kirienko

Processes 2022, 10(3), 483; https://doi.org/10.3390/pr10030483 - 27 Feb 2022

Cited by 5 | Viewed by 2698

Abstract

In order to predict and assess the danger from crown forest fires, it is necessary to study the thermal degradation of different forest fuels in a high-temperature environment. In this paper, the main characteristics of pyrolysis accompanied by moisture evaporation in a foliage [...] Read more.

In order to predict and assess the danger from crown forest fires, it is necessary to study the thermal degradation of different forest fuels in a high-temperature environment. In this paper, the main characteristics of pyrolysis accompanied by moisture evaporation in a foliage sample of angiosperms (birch) were investigated within conditions typical for a crown forest fire. The heat and mass transfer in the forest fuel element is described by the system of non-stationary non-linear heat conduction equations with corresponding initial and boundary conditions. The considered problem is solved within the framework of the three-dimensional statement by the finite difference method. The locally one-dimensional method was used to solve three-dimensional equations for heat conduction. The simple iteration method was applied to solve nonlinear effects caused by the forest fuel pyrolysis and moisture evaporation. The fourth kind of boundary conditions are applicable at the interface between the sub-areas. Software implementation of the mathematical model is performed in the high-level programming language Delphi in the RAD Studio software. The characteristic changes in the sample temperature field and the phase composition under high-temperature exposure from a forest fire are presented. The induction period of the thermal decomposition of dry organic matter in the sample was determined. Recommendations are made about key features of accounting for the pyrolysis and evaporation processes when predicting forest fire danger. The research results can be used in the development and improvement of systems for predicting forest fire danger and environmental consequences of the forest fires. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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16 pages, 6389 KiB

Open AccessArticle

A Study on Welding Deformation in Fiber Laser Welding of 9% Nickel Steel through Finite Element Analysis Part I: Implementation of Welding Heat Source Model

by Changmin Pyo, Jaewoong Kim and Du-Song Kim

Processes 2021, 9(12), 2188; https://doi.org/10.3390/pr9122188 - 4 Dec 2021

Cited by 3 | Viewed by 3110

Abstract

Due to various environmental regulations, the demand for natural gas, i.e., a clean energy, is expected to increase continuously. In terms of efficient storage and transportation of natural gas, liquefied natural gas has an advantageous volume of 1/600 compared to natural gas, but [...] Read more.

Due to various environmental regulations, the demand for natural gas, i.e., a clean energy, is expected to increase continuously. In terms of efficient storage and transportation of natural gas, liquefied natural gas has an advantageous volume of 1/600 compared to natural gas, but the materials that can be used at a cryogenic temperature of −163 °C are limited. A 9% nickel steel is a material recommended by IMO through IGC. It has excellent mechanical properties compared to other cryogenic materials, but its use has been limited due to its disadvantages in arc welding. Therefore, the main topic of this study is the automatic welding of 9% nickel steel using fiber laser and its purpose is to predict the welding deformation during fiber laser welding. First, an investigation was conducted to find the fiber laser welding heat source. A model that can cover all the models in prior studies such as curve, exponential, conical, conical-conical combination, and conical-cylinder combination models was proposed and the heat source model was constructed in a multi-layer format. Heat transfer analysis was performed using the ratio of a heat source radius and heat energy of each layer as a variable and the pass or failure of a heat source was determined by comparing the analysis results to the experimental results. By changing the variables in conjunction with the optimization algorithm, the main parameters of a passed heat source model were verified in a short period of time. In addition, the tendency of parameters according to the welding speed was checked. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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15 pages, 878 KiB

Open AccessFeature PaperArticle

Automatic Tolerance Analysis of Permanent Magnet Machines with Encapsuled FEM Models Using Digital-Twin-Distiller

by Tamás Orosz, Krisztián Gadó, Mihály Katona and Anton Rassõlkin

Processes 2021, 9(11), 2077; https://doi.org/10.3390/pr9112077 - 19 Nov 2021

Cited by 9 | Viewed by 3037

Abstract

Tolerance analysis is crucial in every manufacturing process, such as electrical machine design, because tight tolerances lead to high manufacturing costs. A FEM-based solution of the tolerance analysis of an electrical machine can easily lead to a computationally expensive problem. Many papers have [...] Read more.

Tolerance analysis is crucial in every manufacturing process, such as electrical machine design, because tight tolerances lead to high manufacturing costs. A FEM-based solution of the tolerance analysis of an electrical machine can easily lead to a computationally expensive problem. Many papers have proposed the design of experiments, surrogate-model-based methodologies, to reduce the computational demand of this problem. However, these papers did not focus on the information loss and the limitations of the applied methodologies. Regardless, the absolute value of the calculated tolerance and the numerical error of the applied numerical methods can be in the same order of magnitude. In this paper, the tolerance and the sensitivity of BLDC machines’ cogging torque are analysed using different methodologies. The results show that the manufacturing tolerances can have a significant effect on the calculated parameters, and that the mean value of the calculated cogging torque increases. The design of the experiment-based methodologies significantly reduced the calculation time, and shows that the encapsulated FEM model can be invoked from an external system-level optimization to examine the design from different aspects. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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13 pages, 2819 KiB

Open AccessArticle

Research on Variable-Universe Fuzzy Control Technology of an Electro-Hydraulic Hitch System

by Jikang Xu, Ruichuan Li, Yanchao Li, Yisheng Zhang, Huilai Sun, Xinkai Ding and Yong Ma

Processes 2021, 9(11), 1920; https://doi.org/10.3390/pr9111920 - 27 Oct 2021

Cited by 9 | Viewed by 2130

Abstract

To improve the quality and control accuracy of the farming tractor electro-hydraulic hitch system, a variable-universe fuzzy control algorithm is introduced herein based on force–position mixed adjustment. (1) Background: This research sought to improve the operation quality and control precision of the tractor [...] Read more.

To improve the quality and control accuracy of the farming tractor electro-hydraulic hitch system, a variable-universe fuzzy control algorithm is introduced herein based on force–position mixed adjustment. (1) Background: This research sought to improve the operation quality and control precision of the tractor electro-hydraulic suspension operation system by solving the slow response and low precision problems in the target value control of the system. (2) Methods: According to the characteristics of the operating system, the working principle is discussed. The variable-universe fuzzy controller and the control module were designed based on MC9S12XS128. At the same time, we used Matlab/Simulink to study the step response, and field tests were carried out based on the existing test conditions. (3) Results: In the response stage, the variable-universe fuzzy control only needs 5.85 s, and there is no overshoot problem; in the normal tillage stage, the maximum tillage depth difference is only 1.6 cm, and the traction force is 428 N, which is closer to the expected value. (4) Conclusions: The farming quality and efficiency of the operating system were improved. Additionally, the operating system can also provide technical support for intelligent agricultural machinery and the field management mode in the future. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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40 pages, 28052 KiB

Open AccessArticle

Variable Selection for Fault Detection Based on Causal Discovery Methods: Analysis of an Actual Industrial Case

by Nayher Clavijo, Afrânio Melo, Rafael M. Soares, Luiz Felipe de O. Campos, Tiago Lemos, Maurício M. Câmara, Thiago K. Anzai, Fabio C. Diehl, Pedro H. Thompson and José Carlos Pinto

Processes 2021, 9(3), 544; https://doi.org/10.3390/pr9030544 - 19 Mar 2021

Cited by 7 | Viewed by 3241

Abstract

Variable selection constitutes an essential step to reduce dimensionality and improve performance of fault detection and diagnosis in large scale industrial processes. For this reason, in this paper, variable selection approaches based on causality are proposed and compared, in terms of model adjustment [...] Read more.

Variable selection constitutes an essential step to reduce dimensionality and improve performance of fault detection and diagnosis in large scale industrial processes. For this reason, in this paper, variable selection approaches based on causality are proposed and compared, in terms of model adjustment of available data and fault detection performance, with several other filter-based, wrapper-based, and embedded-based variable selection methods. These approaches are applied in a simulated benchmark case and an actual oil and gas industrial case considering four different learning models. The experimental results show that obtained models presented better performance during the fault detection stage when variable selection procedures based on causality were used for purpose of model building. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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15 pages, 9852 KiB

Open AccessArticle

Selection, Sizing, and Modeling of a Trickle Bed Reactor to Produce 1,2 Propanediol from Biodiesel Glycerol Residue

by Juan B. Restrepo, Johnnys A. Bustillo, Antonio J. Bula and Carlos D. Paternina

Processes 2021, 9(3), 479; https://doi.org/10.3390/pr9030479 - 8 Mar 2021

Cited by 8 | Viewed by 3383

Abstract

Propylene glycol, also known as 1,2 propanediol, is one of the most important chemicals in the industry. It is a water-soluble liquid, considered by the U.S. Food and Drug Administration as safe to manufacture consumer products, including foodstuffs, medicines, and cosmetics. This chemical [...] Read more.

Propylene glycol, also known as 1,2 propanediol, is one of the most important chemicals in the industry. It is a water-soluble liquid, considered by the U.S. Food and Drug Administration as safe to manufacture consumer products, including foodstuffs, medicines, and cosmetics. This chemical has essential properties, such as solvent, moisturizer, or antifreeze, in addition to a low level of toxicity. This paper aims to present the selection, simulation, and dimensioning of a trickle bed reactor at a laboratory scale. The sizing was validated with other authors. Two predictive models have been considered for reactor modeling, intrinsic kinetics and coupled intrinsic kinetics, along with mass transfer equations and the wetting of the catalyst particles. The model was implemented using Aspen Custom Modeler^® (20 Crosby Dr. Bedford, MA 01730, EE. UU.) to study the reactor behavior in terms of conversion. The results show the profiles of different variables throughout the reactor and present higher glycerol conversion when mass transfer is added to the model. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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18 pages, 1580 KiB

Open AccessArticle

Validation of the Molar Flow Rates of Oil and Gas in Three-Phase Separators Using Aspen Hysys

by Adeola Grace Olugbenga, Najah M. Al-Mhanna, Muibat Diekola Yahya, Eyitayo Amos Afolabi and Martins Kolade Ola

Processes 2021, 9(2), 327; https://doi.org/10.3390/pr9020327 - 10 Feb 2021

Cited by 7 | Viewed by 6058

Abstract

A three-phase separator is the first vessel encountered by well fluids. The application of separators has been of great value to the oil and gas industry. In order to generate the gas phase envelope that is applicable to the study of reservoir fluid [...] Read more.

A three-phase separator is the first vessel encountered by well fluids. The application of separators has been of great value to the oil and gas industry. In order to generate the gas phase envelope that is applicable to the study of reservoir fluid and the selection of optimum operating conditions of separators, this research utilizes a specified reservoir fluid stream to simulate a three-phase separator executed in Aspen HYSYS. Subsequently, a comparative study of the effects of specified inlet operating conditions on the output of gas and oil streams was carried out. The results show that changing the inlet pressure of the separator from 1000 to 8000 kPa reduces the gas outlet flow from 1213 to 908.6 kg mol/h, while it increases the liquid flow rate from 374 to 838.0 kg mole/h. By changing the temperature of the separator feed stream from 13 to 83 °C, the gas outlet stream was raised from 707.4 to 1111 kg mol/h, while the liquid flow rate dropped from 1037.0 to 646.1 kg mol/h. It was observed that the concentration of the outlet methane product is not affected by changing the flow rate of the feed stream at a specific pressure and temperature. Therefore, the thermodynamic property method is appropriate to simulate the separation of reservoir fluids which was achieved by selecting the Peng–Robinson (PR) model. The operating conditions of the separator were at 8000 kPa and 43 °C, which lies right on the dew point line. This is comparable to similar work on CHEMCAD which was in turn validated by plant data. Thus, the gas flow rate and the oil flow rate were dependent on pressure and temperature conditions of the plant. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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20 pages, 1892 KiB

Open AccessFeature PaperArticle

Stratification Analysis and Behaviour of a Real Industrial Thermocline Thermal Energy Storage Tank for Cogeneration Purposes

by Francisco J. Fernández, José Díaz, María B. Folgueras and Inés M. Suárez

Processes 2021, 9(1), 120; https://doi.org/10.3390/pr9010120 - 8 Jan 2021

Cited by 3 | Viewed by 2445

Abstract

Thermal energy storage systems help to couple thermal energy generation and process demand in cogeneration facilities. One single deposit with two design temperatures and one main temperature step in sensible thermal energy storage define the thermocline systems. Performance of one high size real [...] Read more.

Thermal energy storage systems help to couple thermal energy generation and process demand in cogeneration facilities. One single deposit with two design temperatures and one main temperature step in sensible thermal energy storage define the thermocline systems. Performance of one high size real thermocline thermal energy storage system is analysed. Starting from temperature and mass flow rate data registered by the plant control system, one advanced thermodynamic analysis is performed. The quality of heat storage is analysed in terms of evaluation of the stratification in the thermocline zone. The temperature data registered at 21 positions is extended by displacement analysis generating detailed profiles. Fraction of recoverable heat, thermocline width, stratification indices based on energy and exergy analysis, and mean temperature gradients in the thermocline region are calculated. These parameters are monitored under real operation conditions of the plant. The calculated parameters are studied to check their distribution and correlation. First and Second Law indices show parallel behaviour and two values are found that delimit situations of high and low values of mean temperature gradients. It was observed that buoyancy generates uniform forced movement with the right water temperature entering the diffusers, but good control strategies are essential to avoid mixing. The system demonstrated great stability in this use. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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21 pages, 4434 KiB

Open AccessArticle

Improving the Energy Efficiency of Industrial Refrigeration Systems by Means of Data-Driven Load Management

by Josep Cirera, Jesus A. Carino, Daniel Zurita and Juan A. Ortega

Processes 2020, 8(9), 1106; https://doi.org/10.3390/pr8091106 - 5 Sep 2020

Cited by 13 | Viewed by 5006

Abstract

A common denominator in the vast majority of processes in the food industry is refrigeration. Such systems guarantee the quality and the requisites of the final product at the expense of high amounts of energy. In this regard, the new Industry 4.0 framework [...] Read more.

A common denominator in the vast majority of processes in the food industry is refrigeration. Such systems guarantee the quality and the requisites of the final product at the expense of high amounts of energy. In this regard, the new Industry 4.0 framework provides the required data to develop new data-based methodologies to reduce such energy expenditure concern. Focusing in this issue, this paper proposes a data-driven methodology which improves the efficiency of the refrigeration systems acting on the load side. The solution approaches the problem with a novel load management methodology that considers the estimation of the individual load consumption and the necessary robustness to be applicable in highly variable industrial environments. Thus, the refrigeration system efficiency can be enhanced while maintaining the product in the desired conditions. The experimental results of the methodology demonstrate the ability to reduce the electrical consumption of the compressors by 17% as well as a 77% reduction in the operation time of two compressors working in parallel, a fact that enlarges the machines life. Furthermore, these promising savings are obtained without compromising the temperature requirements of each load. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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19 pages, 11037 KiB

Open AccessArticle

Prediction of Particle-Collection Efficiency for Vacuum-Blowing Cleaning System Based on Operational Conditions

by Yuan Xi, Yan Dai, Xi–long Zhang and Xing Zhang

Processes 2020, 8(7), 809; https://doi.org/10.3390/pr8070809 - 9 Jul 2020

Cited by 9 | Viewed by 3981

Abstract

The dust-collection system, as the core of a sweeper vehicle, directly inhales dust particles on the pavement. The influence of variable operational conditions on particle-separation performance was investigated using computational fluid dynamics (CFD) Euler–Lagrange multiphase model. The particle-separation performance efficiency and retention time [...] Read more.

The dust-collection system, as the core of a sweeper vehicle, directly inhales dust particles on the pavement. The influence of variable operational conditions on particle-separation performance was investigated using computational fluid dynamics (CFD) Euler–Lagrange multiphase model. The particle-separation performance efficiency and retention time were used to evaluate the dust-collection efficiency. The uniform design (UD) and multiple regression analysis (MRA) methods were employed to predict and optimize the effects of reverse-blowing flow rate, pressure drop, and traveling speed on separation efficiency. The results indicated that the dust-collection performance initially increased and then decreased with increasing reverse-blowing flow rate. As the pressure drop increased, there was an increase in total dust-collection efficiency. However, the efficiency decreased with increasing traveling speed. The regression model showed that the proposed approach was able to predict the particle collection efficiency accurately. In addition, the optimum operational conditions were obtained, namely a reverse-blowing flow rate of 2100 m³/h, a traveling speed of 5 km/h, and a pressure drop of 2400 Pa. The maximum particle-separation efficiency was 99.10%, which showed good agreement with the experimental results. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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20 pages, 4151 KiB

Open AccessArticle

Optimization of Electrolysis Parameters for Green Sanitation Chemicals Production Using Response Surface Methodology

by Nurul Izzah Khalid, Nurul Shaqirah Sulaiman, Norashikin Ab Aziz, Farah Saleena Taip, Shafreeza Sobri and Nor-Khaizura Mahmud Ab Rashid

Processes 2020, 8(7), 792; https://doi.org/10.3390/pr8070792 - 6 Jul 2020

Cited by 17 | Viewed by 4128

Abstract

Electrolyzed water (EW) shows great potential as a green and economical sanitation solution for the food industry. However, only limited studies have investigated the optimum electrolysis parameters and the bactericidal effect of acidic electrolyzed water (AcEW) and alkaline electrolyzed water (AlEW). Here, the [...] Read more.

Electrolyzed water (EW) shows great potential as a green and economical sanitation solution for the food industry. However, only limited studies have investigated the optimum electrolysis parameters and the bactericidal effect of acidic electrolyzed water (AcEW) and alkaline electrolyzed water (AlEW). Here, the Box–Behnken experimental design was used to identify the optimum parameters. The tests were conducted with different types of electrodes, electrical voltages, electrolysis times, and NaCl concentrations. There were no obvious differences observed in the physico-chemical properties of EW when different electrodes were used. However, stainless steel was chosen as it meets most of the selection criteria. The best-optimized conditions for AcEW were at 11.39 V, 0.65 wt.% NaCl, and 7.23 min, while the best-optimized conditions for AlEW were at 10.32 V, 0.6 wt.% NaCl, and 7.49 min. The performance of the optimum EW (AcEW and AlEW) compared with commercial cleaning detergents for the food industry was then evaluated. The bactericidal activity of AcEW and AlEW was examined against Escherichia coli ATCC 10536 at different temperatures (30 °C and 50 °C) for 30 s. The results show that both AcEW and AlEW have the ability to reduce the Escherichia coli to non-detectable levels (less than 2 log CFU/mL). Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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14 pages, 1735 KiB

Open AccessFeature PaperArticle

Application of Combined Developments in Processes and Models to the Determination of Hot Metal Temperature in BOF Steelmaking

by José Díaz and Francisco Javier Fernández

Processes 2020, 8(6), 732; https://doi.org/10.3390/pr8060732 - 24 Jun 2020

Cited by 4 | Viewed by 3631

Abstract

Nowadays, the steel industry is seeking to reduce its carbon footprint without affecting productivity or profitability. This challenge needs to be supported by continuous improvements in equipment, methods, sensors and models. The present work exposes how the combined development of processes and models [...] Read more.

Nowadays, the steel industry is seeking to reduce its carbon footprint without affecting productivity or profitability. This challenge needs to be supported by continuous improvements in equipment, methods, sensors and models. The present work exposes how the combined development of processes and models (CDPM) has been applied to the improvement of hot metal temperature determination. The synergies that arise when both sides of this research are simultaneously approached are evidenced. A workflow that takes into account the CDPM approach is proposed. First, a thermal model of the process is developed, making it possible to identify that hot metal temperature is a key lever for carbon footprint reduction. Then, three main alternatives for hot metal temperature determination are compared: infrared thermometry, time-series forecasting and machine learning prediction. Despite considering only few process variables, machine learning techniques succeed in extracting relevant information from process databases. An accuracy close to infrared thermometry is obtained, with a much higher applicability. This research shows that process-model alternatives are complementary when judiciously nested in the process computer routines. Combining measurement and modelling techniques, 100% applicability is achieved with an error reduction of 7 °C. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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16 pages, 3053 KiB

Open AccessFeature PaperArticle

A Data-Driven-Based Industrial Refrigeration Optimization Method Considering Demand Forecasting

by Josep Cirera, Jesus A. Carino, Daniel Zurita and Juan A. Ortega

Processes 2020, 8(5), 617; https://doi.org/10.3390/pr8050617 - 21 May 2020

Cited by 4 | Viewed by 3758

Abstract

One of the main concerns of industry is energy efficiency, in which the paradigm of Industry 4.0 opens new possibilities by facing optimization approaches using data-driven methodologies. In this regard, increasing the efficiency of industrial refrigeration systems is an important challenge, since this [...] Read more.

One of the main concerns of industry is energy efficiency, in which the paradigm of Industry 4.0 opens new possibilities by facing optimization approaches using data-driven methodologies. In this regard, increasing the efficiency of industrial refrigeration systems is an important challenge, since this type of process consume a huge amount of electricity that can be reduced with an optimal compressor configuration. In this paper, a novel data-driven methodology is presented, which employs self-organizing maps (SOM) and multi-layer perceptron (MLP) to deal with the (PLR) issue of refrigeration systems. The proposed methodology takes into account the variables that influence the system performance to develop a discrete model of the operating conditions. The aforementioned model is used to find the best PLR of the compressors for each operating condition of the system. Furthermore, to overcome the limitations of the historical performance, various scenarios are artificially created to find near-optimal PLR setpoints in each operation condition. Finally, the proposed method employs a forecasting strategy to manage the compressor switching situations. Thus, undesirable starts and stops of the machine are avoided, preserving its remaining useful life and being more efficient. An experimental validation in a real industrial system is performed in order to validate the suitability and the performance of the methodology. The proposed methodology improves refrigeration system efficiency up to 8%, depending on the operating conditions. The results obtained validates the feasibility of applying data-driven techniques for the optimal control of refrigeration system compressors to increase its efficiency. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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15 pages, 4107 KiB

Open AccessArticle

A Novel Process of H₂/CO₂ Membrane Separation of Shifted Syngas Coupled with Gasoil Hydrogenation

by Weirong Huang, Xiaobin Jiang, Gaohong He, Xuehua Ruan, Bo Chen, Aazad Khan Nizamani, Xiangcun Li, Xuemei Wu and Wu Xiao

Processes 2020, 8(5), 590; https://doi.org/10.3390/pr8050590 - 15 May 2020

Cited by 15 | Viewed by 5339

Abstract

A novel process of membrane separation for H₂/CO₂ of shifted syngas coupled with gasoil hydrogenation (NMGH) is proposed. First, a new process, with two-stage CO₂-selective and one-stage H₂-selective membranes, was developed to substitute the conventional PSA [...] Read more.

A novel process of membrane separation for H₂/CO₂ of shifted syngas coupled with gasoil hydrogenation (NMGH) is proposed. First, a new process, with two-stage CO₂-selective and one-stage H₂-selective membranes, was developed to substitute the conventional PSA separation devices to remove CO₂ and purify H₂ in coal gasification refineries to reduce energy consumption and investment costs. Then, the process was coupled with gasoil hydrogenation and the recycled H₂ produced by the hydrogenation reactor could be further purified by the H₂-selective membrane, which increased the H₂ concentration of the hydrogenation reactor inlet by about 11 mol.% compared with the conventional direct recycling process, and the total system pressure was reduced by about 2470 kPa. At the same time, this additional membrane separation and purification prevented the accumulation of CO/CO₂ in the recycled H₂, which ensured the activity of the catalyst in the reactor and the long-term stable operation of the devices. Further, parameters such as compressor power, PI (polyimide)/PEO (polyethylene oxide) membrane area, pressure ratio on both sides of the membrane, and purity of make-up H₂ were optimized by sensitivity analysis. The results showed that, compared with the conventional method, the NMGH process simplified operations, significantly reduced the total investment cost by $17.74 million, and lowered the total annual costs by $1.50 million/year. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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21 pages, 6709 KiB

Open AccessArticle

Improvement of Small Wind Turbine Control in the Transition Region

by Mario L. Ruz, Juan Garrido, Sergio Fragoso and Francisco Vazquez

Processes 2020, 8(2), 244; https://doi.org/10.3390/pr8020244 - 21 Feb 2020

Cited by 7 | Viewed by 2799

Abstract

Wind energy conversion systems are very challenging from the control system viewpoint. The control difficulties are even more challenging when wind turbines are able to operate at variable speed and variable pitch. The contribution of this work is focused on designing a combined [...] Read more.

Wind energy conversion systems are very challenging from the control system viewpoint. The control difficulties are even more challenging when wind turbines are able to operate at variable speed and variable pitch. The contribution of this work is focused on designing a combined controller that significantly alleviates the wind transient loads in the power tracking and power regulation modes as well as in the transition zone. In a previous work, the authors studied the applicability of different multivariable decoupling methodologies. The methodologies were tested in simulation and verified experimentally in a lab-scale wind turbine. It was demonstrated that multivariable control strategies achieve a good closed-loop response within the transition region, where the interaction level is greater. Nevertheless, although such controllers showed an acceptable performance in the power tracking (region II) and power regulation (region IV) zones, appreciable improvement was possible. To this end, the new proposed methodology employs a multivariable gain-scheduling controller with a static decoupling network for the transition region and monovariable controllers for the power tracking and power regulation regions. To make the transition between regions smoother, a gain scheduling block is incorporated into the multivariable controller. The proposed controller is experimentally compared with a standard switched controller in the lab-scale wind turbine. The experiments carried out suggest that the combination of the proposed multivariable strategy for the transition region to mitigate wind transient loads combined with two monovariable controllers, one dedicated to region II and other to region IV, provide better results than traditional switched control strategies. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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20 pages, 4047 KiB

Open AccessFeature PaperArticle

Phenomenological Analysis of Thermo-Mechanical-Chemical Properties of GFRP during Curing by Means of Sensor Supported Process Simulation

by Robert Hein, Robert Prussak and Jochen Schmidt

Processes 2020, 8(2), 192; https://doi.org/10.3390/pr8020192 - 5 Feb 2020

Cited by 2 | Viewed by 2519

Abstract

Inherent process-induced deformations (PID) and residual stresses impede the application of composite parts. PID lead to a geometrical mismatch in assemblies and require subsequent work for tolerance compensation. Unknown residual stresses cause overweighted structures resulting from unnecessary high safety factors. To counteract the [...] Read more.

Inherent process-induced deformations (PID) and residual stresses impede the application of composite parts. PID lead to a geometrical mismatch in assemblies and require subsequent work for tolerance compensation. Unknown residual stresses cause overweighted structures resulting from unnecessary high safety factors. To counteract the deformations, the tool design needs to be modified until the component geometry meets the specifications. This process is mostly carried out empirically and is time and cost intensive. To improve the efficiency of the development process, an in-deep comprehension of the manufacturing processes is mandatory. Therefore, experimental and simulation-based methods are increasingly applied and enhanced. The object of this work is to investigate the development of process-induced strains as well as the material behaviour during the manufacturing for a GFRP plate. The process-induced strains are monitored by optical fiber Bragg grating (FBG) sensors. The change of the material phases is detected by dielectric sensors. Furthermore, a detailed process simulation considering viscoelastic effects and reaction kinetics is performed. Finally, the measurements are correlated with the simulation data to validate the simulation approach. A very good correlation for both the reaction kinetics as well as the process-induced strains is observed. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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19 pages, 4583 KiB

Open AccessArticle

Modeling of Parallel Movement for Deep-Lane Unit Load Autonomous Shuttle and Stacker Crane Warehousing Systems

by Yanyan Wang, Rongjun Man, Xiaofeng Zhao and Hui Liu

Processes 2020, 8(1), 80; https://doi.org/10.3390/pr8010080 - 7 Jan 2020

Cited by 8 | Viewed by 3925

Abstract

The autonomous shuttle and stacker crane (AC/SC) warehousing system, as a new automated deep-lane unit load storage/retrieval system, has been becoming more popular, especially for batch order fulfilment because of its high flexibility, low operational cost and improved storage capacity. This system consists [...] Read more.

The autonomous shuttle and stacker crane (AC/SC) warehousing system, as a new automated deep-lane unit load storage/retrieval system, has been becoming more popular, especially for batch order fulfilment because of its high flexibility, low operational cost and improved storage capacity. This system consists of a shuttle sub-system that controls motion along the x-axis and a stacker crane sub-system that controls motion along the y-axis and z-axis. The combination of shuttles and a stacker crane performs storage and retrieval tasks. Modelling the parallel motion is an important design tool that can be used to calculate the optimal number of shuttles for a given configuration of the warehousing system. In this study, shuttle movements from one lane to another are inserted into the stock-keeping unit (SKU) task queue, and convert such that they are consistent with the retrieval tasks. The tasks are then grouped according to their starting lane, and converted to an assembly-line parallel job problem by analysing the operating mode with the objectives of minimising the total working time of the stacker crane and the wasted shuttle time. A time sequence mathematical model based on the motion of the shuttles and stacker crane is proposed, and an improved Pareto-optimal elitist non-dominated sorting genetic algorithm is used to solve this multi-objective optimization problem. The model is validated via a simulation study, and via a real-world warehousing case study. We go on to describe guidelines for the layout and configuration of AS/SC warehousing systems, including the optimal number of shuttles and number of x-axis storage cells of lanes, which can improve efficiency and minimise both capital investment and operating costs. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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13 pages, 1932 KiB

Open AccessArticle

A Cost Estimation Model for Cloud Services and Applying to PC Laboratory Platforms

by KyungWoon Cho and Hyokyung Bahn

Processes 2020, 8(1), 76; https://doi.org/10.3390/pr8010076 - 7 Jan 2020

Cited by 3 | Viewed by 4625

Abstract

IaaS (Infrastructure as a Service) is a well-known computing service, which provides infrastructures over the cloud without owning real hardware resources. This is attractive as resources can be scaled up and down instantly according to the user’s computing demands. Customers of such services [...] Read more.

IaaS (Infrastructure as a Service) is a well-known computing service, which provides infrastructures over the cloud without owning real hardware resources. This is attractive as resources can be scaled up and down instantly according to the user’s computing demands. Customers of such services would like to adjust the utilization policy promptly by considering the charge of the service, but an instantaneous response is not possible as it takes several hours or even a couple of days for cloud service providers to inform the billing information. In this article, we present an instant cost estimation model for estimating the cost of public cloud resources. Specifically, our model estimates the cost of IaaS by monitoring the usage of resources on behalf of virtual machine instances. As this is performed by generating a user-side metering daemon, it is very precise and thus similar to the resource usage evaluated by the cloud service provider. To validate our model, we run PC laboratory services for 50 students in two classes by making use of a public cloud during a semester. Experimental results show that the accuracy of our model is over 99.3% in comparison with the actual charge of the public cloud. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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15 pages, 1722 KiB

Open AccessArticle

Hybrid Integrations of Value Stream Mapping, Theory of Constraints and Simulation: Application to Wooden Furniture Industry

by Emad Alzubi, Anas M. Atieh, Khaleel Abu Shgair, John Damiani, Sima Sunna and Abdallah Madi

Processes 2019, 7(11), 816; https://doi.org/10.3390/pr7110816 - 5 Nov 2019

Cited by 25 | Viewed by 7859

Abstract

This paper studies manufacturing processes in a wooden furniture manufacturing company. The company suffers from long manufacturing lead times and an unbalanced production line. To identify sources of waste and delay value stream mapping (VSM) and a discrete event simulation model is implemented. [...] Read more.

This paper studies manufacturing processes in a wooden furniture manufacturing company. The company suffers from long manufacturing lead times and an unbalanced production line. To identify sources of waste and delay value stream mapping (VSM) and a discrete event simulation model is implemented. VSM is used to visualize and analyze the major processes of the company and provide quantifiable KPIs; the manufacturing lead-time and then Overall Equipment Effectiveness (OEE) settings. A discrete event simulation model is then built to analyze the company on a wider scale and provide the data required to identify bottlenecks. Building on the data gathered from the production lines and the simulation model, two-bottleneck detection methods are used, the utilization method, and the waiting time method. Then based on the comparison of the two methods a third bottleneck detection is utilized; the scenario-based method, to identify the primary and secondary bottlenecks. After the bottlenecks are identified, changes are then evaluated using the simulation model and radar charts were built based on the improved simulation model, which evaluates the effect of changes in the utilization and OEE results. This work managed to neutralize the effect of one of the main bottlenecks and minimize the effect of the other. The manufacturing utilization was increased by 15.8% for the main bottleneck resources followed by 2.4% for the second one. However, it is hard to convince the traditional administration of this small size manufacturing plant to adopt a completely revolutionizing, costly, and risky (at such level) lean manufacturing approach. This paper studies and provides a much lower in cost and verified scheme of enhancement. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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16 pages, 1316 KiB

Open AccessArticle

Design of S²_N—NEWMA Control Chart for Monitoring Process having Indeterminate Production Data

by Muhammad Aslam, Rashad A. R. Bantan and Nasrullah Khan

Processes 2019, 7(10), 742; https://doi.org/10.3390/pr7100742 - 14 Oct 2019

Cited by 12 | Viewed by 2531

Abstract

The existing charts for monitoring the variance are designed under the assumption that all production data must consist of exact, precise, and determined observations. This paper presents the design of a new neutrosophic exponentially weighted moving average (NEWMA) combining with a neutrosophic logarithmic [...] Read more.

The existing charts for monitoring the variance are designed under the assumption that all production data must consist of exact, precise, and determined observations. This paper presents the design of a new neutrosophic exponentially weighted moving average (NEWMA) combining with a neutrosophic logarithmic transformation chart for monitoring the variance having neutrosophic numbers. The computation of the neutrosophic control chart parameters is done through the neutrosophic Monte Carlo simulation (NMCS). The performance of the proposed chart is discussed with the existing charts. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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23 pages, 1064 KiB

Open AccessArticle

Sustainable Personnel Scheduling Problem Optimization in a Natural Gas Combined-Cycle Power Plant

by Emir Hüseyin Özder, Evrencan Özcan and Tamer Eren

Processes 2019, 7(10), 702; https://doi.org/10.3390/pr7100702 - 5 Oct 2019

Cited by 8 | Viewed by 3938

Abstract

This paper deals with a sustainable personnel scheduling problem of personnel working in a large-scale natural gas combined-cycle power plant in Turkey. The proposed model focuses on employee complaints due to unfair work schedules and the results of balanced assignments based on power [...] Read more.

This paper deals with a sustainable personnel scheduling problem of personnel working in a large-scale natural gas combined-cycle power plant in Turkey. The proposed model focuses on employee complaints due to unfair work schedules and the results of balanced assignments based on power plant interruptions. Eighty personnel work in three shifts at this natural gas combined-cycle power plant. The model is solved with respect to some of the workers’ skills, and there are 20 criteria regarding skills. The analytic network process method is used to get the weights of workers’ skills, which are calculated and included in the model. Goal programming is used in this paper. Our proposed model gives cost minimization and fair work schedules for the power plant. Compared with the literature, the number and set of criteria are unique in terms of personnel competency in the energy sector. Minimizing cost and imbalanced assignments was achieved by the proposed model for the first time without considering the sector. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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20 pages, 3819 KiB

Open AccessArticle

Gain Scheduling of a Robust Setpoint Tracking Disturbance Rejection and Aggressiveness Controller for a Nonlinear Process

by Veeramani Bagyaveereswaran and Pachiyappan Arulmozhivarman

Processes 2019, 7(7), 415; https://doi.org/10.3390/pr7070415 - 2 Jul 2019

Cited by 8 | Viewed by 3960

Abstract

In this paper, a robust setpoint tracking disturbance rejection and aggressiveness (RTD-A) controller is designed and developed to control the liquid level of a conical tank process. Meta-heuristic algorithms like grey wolf optimization and the genetic algorithm are used to tune the parameters [...] Read more.

In this paper, a robust setpoint tracking disturbance rejection and aggressiveness (RTD-A) controller is designed and developed to control the liquid level of a conical tank process. Meta-heuristic algorithms like grey wolf optimization and the genetic algorithm are used to tune the parameters of the RTD-A controller. Its performance is later compared with that of the conventional standard proportional integral derivative controller. The gain scheduled RTD-A controller is designed and implemented on a nonlinear conical tank process. Also, various performances attributes such as the integral square error, integral absolute error, integral time absolute error, rise time, and settling time are calculated for the first-order process and conical tank process. The servo responses with RTD-A are also compared against the responses recorded from the conventional control schemes. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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18 pages, 7480 KiB

Open AccessArticle

Numerical Determination of RVE for Heterogeneous Geomaterials Based on Digital Image Processing Technology

by Lanlan Yang, Weiya Xu, Qingxiang Meng, Wei-Chau Xie, Huanling Wang and Mengcheng Sun

Processes 2019, 7(6), 346; https://doi.org/10.3390/pr7060346 - 6 Jun 2019

Cited by 3 | Viewed by 3907

Abstract

Representative volume element (RVE) is an important parameter in numerical tests of mechanical properties of heterogeneous geomaterials. For this study, a digital image processing (DIP) technology was proposed for estimating the RVE of heterogeneous geomaterials. A color image of soil and rock mixture [...] Read more.

Representative volume element (RVE) is an important parameter in numerical tests of mechanical properties of heterogeneous geomaterials. For this study, a digital image processing (DIP) technology was proposed for estimating the RVE of heterogeneous geomaterials. A color image of soil and rock mixture (SRM) with size of 400 × 400 mm² taken from a large landslide was used to illustrate the determination procedure of the SRM. Six sample sizes ranging from 40 × 40 mm² to 240 × 240 mm² were investigated, and twelve random samples were taken from the binarized image for each sample size. A connected-component labeling algorithm was introduced to identify the microstructure. After establishing the numerical finite difference models of the samples, a set of numerical triaxial tests under different confining pressures were carried out. Results show that the size of SRM sample affects the estimation of the mechanical properties, including compressive strength, cohesion, and internal friction angle. The larger the size of the samples, the less variability of the estimated mechanical properties. The coefficient of variation (CV) was applied to measure the variability of mechanical properties, and the RVE of the SRM was determined easily with a predefined acceptance threshold of the CV. The results show that a DIP-based modeling method is an effective method got the RVE determination of heterogeneous geomaterials. Full article

(This article belongs to the Special Issue Synergies in Combined Development of Processes and Models)

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