Implementation Of Industrial Applications Research Articles

Case Study of KIMM Universal Gripper: Analysis of Commercial Industrial Gripper and Evaluation of the KIMM Universal Gripper in Industry

The need for automation in manufacturing processes has created a demand for flexible production systems that can easily adapt to changing market needs. However, due to limitations in gripper performance, manual labor is still required in many manufacturing processes, especially when handling different objects. This paper proposes a classification of grippers used in the industrial field and analyzes the characteristics of each gripper category. The effectiveness of gripping and handling objects depends on the type of gripper used, making it challenging to find a gripper that can handle a wider range of objects beyond the typical boundaries. To address this issue, we describe two universal grippers developed by KIMM: the Impactive-type universal gripper and the Astrictivetype universal gripper. We also discuss the limitations of each gripper as discovered during their implementation in industrial applications and present research on overcoming these limitations. Additionally, we introduce two types of hybrid universal grippers as possible solutions to cover a broader range of fields. By analyzing these grippers, we provide predictions for the future development of grippers, which align with KIMM's ongoing research and development efforts.

Sensorless fuzzy-sliding mode control of five phases permanent magnet synchronous motor using MRAS: in three different operating modes

This paper presents a comprehensive study on sensorless control techniques for five-phase permanent magnet synchronous motors (5P-PMSMs). To optimize the speed control performance of (5P-PMSM), which has more advantages than its counterpart three-phase PMSM system, we utilized a combination of fuzzy logic and sliding mode control techniques to optimize the proposed sliding mode control. Additionally, the Model Reference Adaptive System (MRAS) is employed to estimate the speed and rotor position of the 5P-PMSM to enhance the robustness and adaptability of the control system. The modelling of the machine, detailed with a robust nonlinear strategy based on the sliding control, is introduced to track the system until the desired sliding surface is achieved first. To guarantee that the tracking errors converge, the sliding mode control has a chatter due to the discontinuous term. To mitigate the drawback, the proposed control is designed by combining SMC with fuzzy logic, enhancing the performance in a steady state. Examining the control performance of the integrated control fuzzy-SMC with MRAS in different operating modes, including three tests in reversal speed operation, open phase fault mode, and the low-speed operating mode under load torque. The main aim is to assess and analyze the robustness and performance of the proposed control strategy. The stability of the overall control system is examined using the Lyapunov theorem and Popov’s theory analysis of MRAS observer stability. The simulation results of the suggested control displayed by MATLAB-Simulink illustrate the effectiveness and adaptability of the sensorless control scheme across different operating conditions, offering promising prospects for practical implementation in industrial applications.

High-Throughput Screening Techniques for the Selection of Thermostable Enzymes.

The acquisition of a thermostable enzyme is an indispensable prerequisite for its successful implementation in industrial applications and the development of novel functionalities. Various protein engineering approaches, including rational design, semirational design, and directed evolution, have been employed to enhance thermostability. However, all of these approaches require sensitive and reliable high-throughput screening (HTS) technologies to efficiently and rapidly identify variants with improved properties. While numerous reviews focus on modification strategies for enhancing enzyme thermostability, there is a dearth of literature reviewing HTS methods specifically aimed at this objective. Herein, we present a comprehensive overview of various HTS methods utilized for modifying enzyme thermostability across different screening platforms. Additionally, we highlight significant recent examples that demonstrate the successful application of these methods. Furthermore, we address the technical challenges associated with HTS technologies used for screening thermostable enzyme variants and discuss valuable perspectives to promote further advancements in this field. This review serves as an authoritative reference source offering theoretical support for selecting appropriate screening strategies tailored to specific enzymes with the aim of improving their thermostability.

Industrial Soldering Process Simulator

Determination of the physico-chemical interactions between liquid and solid substances is a key technological factor in many industrial processes in metallurgy, electronics or the aviation industry, where technological processes are based on soldering/brazing technologies. Understanding of the bonding process, reactions between materials and their dynamics enables to make research on new materials and joining technologies, as well as to optimise and compare the existing ones. The paper focuses on a wetting force measurement method and its practical implementation in industrial applications. Soldering simulation is a process in which simulation tools are used to model and simulate soldering processes. With simulation, different soldering methods and parameters can be tested to identify the best approach and minimize the risk of errors and failures in the real process. Soldering simulation can be used to optimize the soldering process and increase productivity, as well as to train personnel.

Classification of voltage sags causes in industrial power networks using multivariate time‐series

AbstractVoltage sags are the most frequent and impactful disturbances in industrial power grids, leading to high financial losses for industrial clients. The identification of the cause and its relative location is crucial for the contractual relation between the energy provider and the industrial customers. This paper proposes a methodology to identify the origins of voltage sags based on instantaneous symmetrical components and dynamic time warping. Short‐Time Fourier and Fortescue transform are implemented in the pre‐processing step using the voltage and current waveforms. Then, a distance‐based classification strategy to identify the sources of voltage sags is used. It relies on a four‐dimension time‐series signature used as features. Moreover, a confidence index associated with the classification output is provided. The proposal offers an easy implementation in industrial applications with no previous recorded data. It has the benefit of using a reduced‐size reference database entirely composed of synthetic data. The main advantages of the proposed method are its generalization capabilities and the possibility of raising an alert based on the confidence index. The obtained classification accuracy on synthetic data with seven causes is 100%. The method reaches a classification F1‐score higher than 99% with field measurements representing five classes obtained from three different industrial sites.

AVsIs: An Analytical-Solution-Based Solver for Model-Predictive Control With Hexagonal Constraints in Voltage-Source Inverter Applications

The theory of a new analytical-solution-based algorithm for calculating the optimal solution in model-predictive control applications with hexagonal constraints is discussed in this article. Three-phase voltage-source inverters for power electronic and electric motor drive applications are the target of the proposed method. The indirect model-predictive control requires a constrained quadratic programming (QP) solver to calculate the optimal solution. Most of the QP solvers use numerical algorithms, which may result in unbearable computational burdens. However, the optimal constrained solution can be calculated in an analytical way when the control horizon is limited to the first step. A computationally efficient algorithm with a certain maximum number of operations is proposed in this article. A thorough mathematical description of the solver in both the stationary and rotating reference frames is provided. Experimental results on real test rigs featuring either an electric motor or a resistive–inductive load are reported to demonstrate the feasibility of the proposed solver, thus smoothing the way for its implementation in industrial applications. The name of the proposed solver is <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aVsIs</monospace> , which is released under Apache License 2.0 in GitHub, and a free example is available in Code Ocean.

A Method for Measurement of Workpiece form Deviations Based on Machine Vision

Machine vision has been studied for measurements of workpiece form deviations due to its ease of automation. However, the measurement accuracy limits its wide implementation in industrial applications. In this study, a method based on machine vision for measurement of straightness, roundness, and cylindricity of a workpiece is presented. A subsumed line search algorithm and an improved particle swarm optimization algorithm are proposed to evaluate the straightness and roundness deviations of the workpiece. Moreover, an image evaluation method of cylindricity deviation by the least-square fitting of the circle’s center coordinates is investigated. An image acquisition system incorporating image correction and sub-pixel edge positioning technology is developed. The performance of the developed system is evaluated against the measurement results of the standard cylindricity measuring instrument. The differences in the measurement of straightness, roundness, and cylindricity are −4.69 μm, 3.87 μm, and 8.51 μm, respectively. The proposed method would provide a viable industrial solution for the measurement of workpiece form deviations.

Microscopic fringe projection profilometry systems in Scheimpflug condition and performance comparison

The high-frequency fringe images provided by magnifying lenses with low distortion render the microscopic fringe projection profilometry (MFPP) with better measurement accuracy. In order to extend the depth of field limited in the microscopic environment, the Scheimpflug principle is commonly used in both single-camera-based and multi-camera-based MFPP systems by increasing the mutual overlap range of different views in the object space. In this paper, to compare the performance of single-camera-based and dual-camera-based MFPP systems, we set up MFPP systems and performed 3D measurements of plates, standard balls, and some specifically designed samples. By analyzing the various factors affecting measurement accuracy and integrity, we verified and concluded that the dual-camera-based system wins in measurement accuracy while the single-camera-based system has better integrity, which may provide a reference for the system design in the implementation of industrial applications.

Secured cloud SCADA system implementation for industrial applications

The proposed Remote SCADA System (RSS) is a smarter, faster and more reliable way to control high power machines and monitor their sensors, data, and failures. The proposed system focuses mainly on building our own complete SCADA software and not using open-source SCADA software. The proposed RSS can use unlimited number of added Remote Terminal Units (RTU) nodes and each of them can handling unlimited number of input/output and can be used under different operating systems like Windows and Android. Using RSS all machines can be monitored and controlled by a single click from anywhere at any time. By doing this a real-time response from RSS system can be achieved. It’s mainly based on standard communication techniques between remote nodes and single server-side application that talk to each node with its own ID and modify its instant database. So that every time accessing this web application, a real-time access to these nodes data and a virtual control room controls each General Purpose Input/Output (GPIO) in the selected node can be gotten. When a new event is happened in server-side program, it will be broadcasted to all related. On RSS there are two main points to deal with, the request latency and security of the system. This paper studied how the system latency and security are improved to obtain the needed values. The proposed RSS is a very secure program which have 4 security levels; authentication, authorization, RSA and CBC encryption system. Also, the encryption algorithms used in RSS are RSA and CBC block cipher encryption system. It is mixed way to prevent any attacker from breaking the cipher. First of all, RSA generates the public and private keys, and then CBC generates its Initialization vector and a random encryption key. Then a special function sends all of these keys encrypted with a pre-stored token in the data base and node memory which varied from node to another. Finally, node generates its private key from loaded public key. With this combination the speed of symmetric encryption system and the security of asymmetric encryption system can be achieved. On the other hand, the level of security firewalls needed to be Brocken by the attacker to brock the cipher is increased. The proposed system achieved low cost comparing with reported work; it is lower than Arduino + WIFI method by five times and 13 times lower than Raspberry-PI method. The proposed system is applied in educational systems, where it is used for teaching unlimited number of students Online.

Combining optical spectroscopy and machine learning to improve food classification

Near-infrared spectroscopic data, used for non-destructive product identification, are traditionally processed using multivariate data analysis techniques. However, these methods often cover only a limited product variability. We target the development of a novel machine learning based algorithm enabling the identification of foreign objects, in combination with food safety and quality evaluation in a product stream, by combining the information from ultraviolet, visible, near-infrared reflection spectroscopy and fluorescence spectroscopy. Therefore, we implemented a novel classification scheme using a cascade of individual classifiers combining both types of spectral data. In addition, to ease implementation in industrial applications and reduce processing time, we applied a feature selection search, limiting the considered illumination and detection wavelengths to 8. As an illustration of our novel classification algorithm, we present the processing of walnuts in this paper. The optimal cascade consists of a first classifier based on reflection measurements using Extreme Learning Machine and a second classifier based on fluorescence measurements using Support Vector Machines. A false negative rate of the good nuts of 5.54% was found, while the maximal false positive rate equals 8.34%, for shriveled walnuts. All other sample defects, including both foreign objects and molds, show a correct classification rate exceeding 98%. Consequently, this excellent performance indicates the strength of machine learning processing for multipurpose food processing applications.

Scalable synthesis of KNaTiO3-based high-temperature CO2 capture material from high titanium slag: CO2 uptake, kinetics, regenerability and mechanism study

KNaTiO3 is a novel type of solid CO2 sorbents with strong sorption capacity and excellent regenerability at high temperatures. However, the expensive titanium precursor hampers its implementation for industrial applications. Herein, advanced KNaTiO3 based CO2 sorbents were first fabricated directly from high titanate slag (HTS). Elemental mapping analysis reveals high dispersion of KNaTiO3 and the crystal structure of KNaTiO3 in KNaTiO3-HTS-3 almost unchanged even after 15 cycles. The carbonation conversion of KNaTiO3-HTS-3 preserved a highly commendable value even after 100 sorption/desorption cycles, outperforming pure KNaTiO3. In addition, this sorbent exhibited faster sorption rate at 700 °C. Dynamic simulation demonstrated that the sorption constants k1 and k2 are higher and the activation energy is lower than those of conventional high-temperature sorbents. The CO2 sorption capacity of KNaTiO3-HTS-3 only met a slight decrease from 15.7 to 14.6 wt% with the decreasing CO2 concentration from 100 to 10 vol%. Compared with traditional high temperature CO2 sorbents, KNaTiO3-HTS-3 shows a slower breakthrough time. The reaction mechanism process for the promising sorbent is proposed. The HTS-derived KNaTiO3-based high-temperature CO2 sorbent has outstanding CO2 uptake, excellent regenerability, fast reaction kinetics as well as low cost, offering bright prospects in practical applications.

Optimization of TiO2/ZSM-5 photocatalysts: Energy band engineering by solid state diffusion method with calcination

In this work, based on a type of energy band engineering strategy as calcination, TiO2/ZSM-5 hybrids for photodegradation of methyl orange (MO) in water under UV light have been developed via a facile solid state diffusion method. Effects of varied calcination temperatures on TiO2/ZSM-5 hybrids have been systematically characterized including XRD, FT-IR, SEM, TEM, EDX mapping, BET, PL, EIS, UV–vis DRS, active species trapping experiments and Mott-Schottky curves. It was found that the calcination temperature influenced photocatalytic activity, typically on physicochemical properties of materials and adjustment for the energy gap and band position of TiO2. The XRD analysis revealed that hybridization of ZSM-5 kept the crystal phase of TiO2 as anatase unchanged with the high-rising calcined temperature. The optimum sample calcined at 450 °C named as Z-T (450) presented nearly 99% degradation rate for MO, owing to optimal uniform distribution, highest specific surface area and best charge separation/transfer efficiency. The FT-IR comparison result that the functional groups and peak strength of the used catalyst were alike as before, showed the stability of photocatalyst. Adoption of calcination strategy does provide not only a clean, low-cost and highly efficient path to approach the complete degradation of azo dyes, but also a chance for photocatalytic technology to fulfill the implementation in industrial applications.

Transition Metal Carbides (TMCs) Catalysts for Gas Phase CO2 Upgrading Reactions: A Comprehensive Overview

Increasing demand for CO2 utilization reactions and the stable character of CO2 have motivated interest in developing highly active, selective and stable catalysts. Precious metal catalysts have been studied extensively due to their high activities, but their implementation for industrial applications is hindered due to their elevated cost. Among the materials which have comparatively low prices, transition metal carbides (TMCs) are deemed to display catalytic properties similar to Pt-group metals (Ru, Rh, Pd, Ir, Pt) in several reactions such as hydrogenation and dehydrogenation processes. In addition, they are excellent substrates to disperse metallic particles. Hence, the unique properties of TMCs make them ideal substitutes for precious metals resulting in promising catalysts for CO2 utilization reactions. This work aims to provide a comprehensive overview of recent advances on TMCs catalysts towards gas phase CO2 utilization processes, such as CO2 methanation, reverse water gas shift (rWGS) and dry reforming of methane (DRM). We have carefully analyzed synthesis procedures, performances and limitations of different TMCs catalysts. Insights on material characteristics such as crystal structure and surface chemistry and their connection with the catalytic activity are also critically reviewed.

Parameters Affecting the Improvement of Properties and Stabilities of Immobilized α-amylase on Chitosan-metal Oxide Composites

Chitosan-metal oxide composites, chitosan- Fe3O4 (CSM) and chitosan-ZnO (CSZ) were synthesized and intended as suitable supports for immobilization of starch hydrolyzing enzyme, α-amylase. Here α-amylase was chosen as the enzyme to immobilize on these supports due to its wide implementation in industrial applications. The immobilized enzyme, CSZE showed better immobilization yield of 76%, whereas CSME provides high speed and easy separation from the reaction system due to its magnetic property. The quality of the immobilized α-amylases was demonstrated and assessed based on its activity and stability. The immobilized enzymes with higher Ed values provide them more stability towards denaturation compared to free enzyme. At 50℃ the thermodynamic parameters such as ∆Ho, ∆Go and ∆So for thermal deactivation of free enzyme were evaluated as 104.29, 12.83 and -0.28 KJ mol-1 respectively and are found to be higher in case of both immobilized enzymes. The Km values for CSME and CSZE are 0.65 and 0.5mg/mL respectively, which are higher than that of free enzyme (0.45mg/mL). The Vmax of free enzyme is decreased from 34.48μmol mg-1 min-1 to 16.39(CSME) and 23.81 (CSZE) μmol mg-1 min-1 as a result of immobilization. The immobilized enzymes have exhibited better storage stability over 6 months and retained more than 50% of their initial activities after 10 cycles of reuses.

Linking Microbial Community Structure and Function During the Acidified Anaerobic Digestion of Grass.

Harvesting valuable bioproducts from various renewable feedstocks is necessary for the critical development of a sustainable bioeconomy. Anaerobic digestion is a well-established technology for the conversion of wastewater and solid feedstocks to energy with the additional potential for production of process intermediates of high market values (e.g., carboxylates). In recent years, first-generation biofuels typically derived from food crops have been widely utilized as a renewable source of energy. The environmental and socioeconomic limitations of such strategy, however, have led to the development of second-generation biofuels utilizing, amongst other feedstocks, lignocellulosic biomass. In this context, the anaerobic digestion of perennial grass holds great promise for the conversion of sustainable renewable feedstock to energy and other process intermediates. The advancement of this technology however, and its implementation for industrial applications, relies on a greater understanding of the microbiome underpinning the process. To this end, microbial communities recovered from replicated anaerobic bioreactors digesting grass were analyzed. The bioreactors leachates were not buffered and acidic pH (between 5.5 and 6.3) prevailed at the time of sampling as a result of microbial activities. Community composition and transcriptionally active taxa were examined using 16S rRNA sequencing and microbial functions were investigated using metaproteomics. Bioreactor fraction, i.e., grass or leachate, was found to be the main discriminator of community analysis across the three molecular level of investigation (DNA, RNA, and proteins). Six taxa, namely Bacteroidia, Betaproteobacteria, Clostridia, Gammaproteobacteria, Methanomicrobia, and Negativicutes accounted for the large majority of the three datasets. The initial stages of grass hydrolysis were carried out by Bacteroidia, Gammaproteobacteria, and Negativicutes in the grass biofilms, in addition to Clostridia in the bioreactor leachates. Numerous glycolytic enzymes and carbohydrate transporters were detected throughout the bioreactors in addition to proteins involved in butanol and lactate production. Finally, evidence of the prevalence of stressful conditions within the bioreactors and particularly impacting Clostridia was observed in the metaproteomes. Taken together, this study highlights the functional importance of Clostridia during the anaerobic digestion of grass and thus research avenues allowing members of this taxon to thrive should be explored.

Continuous ohmic heating system for the pasteurization of fermented red pepper paste

Abstract Ohmic heating (OH) is a processing in which heat is generated inside foods by the passage of electric current. This study aimed to determine the optimal conditions for pasteurizing the Gochujang Korean-style fermented food containing hot pepper paste using a continuous OH system. The effective conditions for OH involved three pairs of electrodes connected diagonally and excitation over the voltage range of 50–100 V. The selected conditions provided heating above 100 °C without scale buildup. A microbial inactivation with a 2 log reduction was achieved by the OH, with the processing time being shorter than for conventional heating (CH). OH was available for 57 cycles during 1 cycle of CH, and it could process 104.4 kilotonnes of product. The consistency index related to thickening properties was markedly higher for OH than for CH. This study has confirmed that continuous OH is suitable for the heat-based sterilization of highly viscous foods. Industrial relevance Ohmic heating (OH) is a food processing technique in which heat is generated inside food products by the passage of alternating electric current. This study aimed to determine the optimal conditions for pasteurizing the Gochujang Korean-style fermented food containing hot pepper paste using a self-designed continuous OH system. The effective conditions for OH involved three pairs of electrodes connected diagonally and excitation over the voltage range of 50–100 V. The selected conditions provided heating above 100 °C without scale buildup. The rapid and uniform OH produced a microbial inactivation effect of a 2 log reduction despite the shorter processing time than for batch-type conventional heating (CH). OH was available for 57 cycles during 1 cycle of CH, and it could process 104.4 kilotonnes of food products. And the continuous OH is suitable for the heat-based sterilization of highly viscous foods and could result in better energy efficiency and be suitable for implementation in industrial applications.

De facto methodologies toward the synthesis and scale-up production of UiO-66-type metal-organic frameworks and membrane materials.

Metal-organic frameworks (MOFs) are architected via coordination bonds between inorganic metal nodes and organic ligands. They have become emerging advanced porous materials and gained ever-increasing attention in the past decade. In particular, overwhelming studies have been devoted to those hydrostable MOFs which are suggested to be highly promising for industrial applications. UiO-66 is such a unique MOF because of its superior thermal/chemical stability and structural tunability. However, its repeatable, green, and scale-up synthesis remains a challenge for its commercialization and implementation in industrial applications. This perspective mainly summarises the recent development in the synthesis of UiO-66-type MOFs and their related composites. From a scale-up viewpoint, we also present some important advances in the batch and continuous reactor synthesis toward their massive production (226 references).

Adaptive Algorithm for the Quality Control of Braided Sleeving

We describe the development and application of a robot vision based adaptive algorithm for the quality control of the braided sleeving of high pressure hydraulic pipes. With our approach, we can successfully overcome the limitations, such as low reliability and repeatability of braided quality, which result from the visual observation of the braided pipe surface. The braids to be analyzed come in different dimensions, colors, and braiding densities with different types of errors to be detected, as presented in this paper. Therefore, our machine vision system, consisting of a mathematical algorithm for the automatic adaptation to different types of braids and dimensions of pipes, enables the accurate quality control of braided pipe sleevings and offers the potential to be used in the production of braiding lines of pipes. The principles of the measuring method and the required equipment are given in the paper, also containing the mathematical adaptive algorithm formulation. The paper describes the experiments conducted to verify the accuracy of the algorithm. The developed machine vision adaptive control system was successfully tested and is ready for the implementation in industrial applications, thus eliminating human subjectivity.

Formal Specification and Design Techniques for Wireless Sensor and Actuator Networks

A current trend in the development and implementation of industrial applications is to use wireless networks to communicate the system nodes, mainly to increase application flexibility, reliability and portability, as well as to reduce the implementation cost. However, the nondeterministic and concurrent behavior of distributed systems makes their analysis and design complex, often resulting in less than satisfactory performance in simulation and test bed scenarios, which is caused by using imprecise models to analyze, validate and design these systems. Moreover, there are some simulation platforms that do not support these models. This paper presents a design and validation method for Wireless Sensor and Actuator Networks (WSAN) which is supported on a minimal set of wireless components represented in Colored Petri Nets (CPN). In summary, the model presented allows users to verify the design properties and structural behavior of the system.

On Line Visual-Grasping System Based on a Gripper with Two Flexible Fingers

AbstractIn this work we propose a novel gripper with two flexible fingers combined with a visual object recognition system for its implementation in industrial applications, such as manufacturing, assembly and manipulation, among others. This original system increases the manipulability and flexibility of the robots manipulators and improves the safety of the operations carried out with it. This combined system also makes the manipulation of very fragile or deformable objects possible as result of the flexible characteristic of the gripper fingers. The system is mounted at the end effector of a 6 DOF robot manipulator for object recognition and manipulation tasks. The object recognition software is developed and the force control law for the gripper is designed. Experiments are included to demonstrate the good performance of the system proposed.