Machine Control Research Articles

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

ANÁLISE DE PROTÓTIPO VOLTADO A EFICIÊNCIA ENERGÉTICA APLICADA A TORRE DE RESFRIAMENTO INDUSTRIAL

Introduction: The integration of an energy control system into an industrial cooling tower, by combining this technological advance that current technology provides us, guaranteeing maximum efficiency and environmental protection. Objective: To analyze a prototype focused on energy efficiency applied to industrial cooling towers, with Arduino controlling an automation system aimed at this. Methodology: This study is a qualitative research with a case study type involving the development of a prototype of an energy control system applied to an industrial cooling tower and supporting literature with databases from engineering journals. Results: The results indicate that the system is viable for any industrial use, thus ensuring greater control and efficiency to the industry, being able to adapt to any environment and also adding to it any type of electrical machines for control. Conclusion: integration can contribute significantly to the development of innovative solutions in the field of automation and safety, ensuring greater control and efficiency in the supervision of industrial environments.

Informatization model of Guqin based on grasshopper and CNC machining

ABSTRACT The integration of Computer-Aided Design (CAD) and Computer Numerical Control (CNC) machining has brought modern manufacturing techniques into the craft of Guqin crafting, introducing the concept of Industrialized Standardized Guqin Crafting (ISGC). This study proposes the concept of Guqin Information Modeling (GIM), on the basis of which, the parametric modeling method of Guqin is proposed to realize the parameter control of the key position of Guqin; combined with the CNC machining technology, it verifies the production of Guqin of different materials and shapes, summarizes the method of selecting the tools for CNC machining of Guqin and the machining parameters of each process, and puts forward the Industrialized Standard of Guqin Carving (ISGC). The proposal of GIM and ISGC provides information technology support for the research of the sound quality of Guqin and the protection of Guqin.

Design and building CNC engraving router machine using Arduino Uno with GRBL control system

Computer Numerical Control Machines are one of the advances in automatically operated machining technology that can meet the need for complex and high-precision products. CNC machine parts generally have a mechanical and electrical system, also called a machine controller, that uses a Human Machine Interface at a high price. One of the software used to control the CNC machine is Arduino Uno, a PC-based GRBL System with a low price and the same function. This software is not far from the advantages of the HMI panel. Operating the machine with this software is also not that difficult. In this research, we intend to make a CNC machine using the Arduino Uno control system and software with a PC-based GRBL System, making it easier for operators to operate it. The results of the research that has been carried out show that the CNC has a size of 800x600x50mm with a system that is operated well and precisely

STEP-NC compliant 3-axis CNC machine controller based on Field-Programmable Gate Arrays

ABSTRACT Manufacturing processes have gone through several transformations in history. Previously, G&M codes served as a common programming language for CNC machines. Codes of CNC machines contain the information related to the tools and trajectories. G&M codes are machine-specific and vendors must customize them for the tools installed on a particular machine. STEP-NC, described by ISO-14649, provides an alternative to G&M codes aiming at generic interoperability of CNC machine codes. STEP-NC includes information on both the trajectories and the tool’s specifications making it generic and machine-independent. STEP-NC is an emerging area and a gateway to intelligent machining targeting ‘design anywhere and develop anywhere’. Therefore, several researchers have developed software-based decoders and interpreters. They are difficult to implement on a serial pipelined processor limiting their use for real-time applications. This paper presents a Field Programmable Gate Array (FPGA)-based STEP-NC controller implemented and validated on a SPARTAN-3E kit. To the best of the author’s knowledge, this is the first FPGA-based implementation of STEP-NC. The main contribution of this work is a generic state-machine representation of the STEP-NC entities suitable for implementation on different FPGA platforms. The developed decoder was successfully tested and evaluated on a three-axis CNC machine for an example given in ISO-14649-11 for compliance.

A review of finite control set model predictive control for linear machines

AbstractLinear machines (LMs) have become excellent candidates for linear motion applications due to their abilities of generating thrust without any transmissions, and have been widely adopted in transportation, industries etc. Among the numerous control methods of LM drive systems, finite control set model predictive control (FCS‐MPC) method has been given special attention due to its clear concept, fast response performance, and ability to handle constrained multivariate non‐linear control problems. It is widely used to improve the performance and efficiency of overall LM drive systems. Firstly, based on the three elements of FCS‐MPC, the advantages and shortcomings of the FCS‐MPC method in applications are fully investigated. The research status in FCS‐MPC has been summarised, such as multistep MPC, parameters robustness improvement, fast optimisation, and multi‐vector MPC. Then, the key issues in FCS‐MPC such as delay compensation, parameters design, and stability analysis are discussed, and their typical research methods and current research status are explained. Finally, the future development trends of FCS‐MPC in LM drive systems are discussed.

Trainer Kit Module for DC Motor Speed Control Using Voice Commands Based on Arduino

Based on the results of observations made by researchers through direct observation of lecturers in the field of electricity, Electrical Engineering Education Study Program, it was found that there is a need for additional trainers as learning media in the electrical machine control course. This study aims to find out how to design a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. We also learned the results of testing the design of a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. The research method researchers use is the Research and Development (R&D) method, which aims to develop new products or innovations that benefit. Based on the results of expert validation, it can be concluded that the Arduino Microcontroller-Based Trainer Kit Practical Module obtained a high percentage of media experts at 96%, material experts at 95.5%, and language experts at 80%. These results indicate that this module gets the "Very Eligible" category to be applied to the Electrical Machine Control course.

Study on the analytical verification method of geometric error models

Abstract Geometric error compensation is a widely used and effective approach for enhancing the accuracy of Coordinate Measuring Machines (CMMs) and Computer Numerical Control (CNC) machines. The research in this field primarily focuses on the challenging task of developing geometric error modelling techniques. Currently, there are several well-established methods for modelling geometric errors. However, there is scarce availability of methods that can validate the established geometric error models. Therefore, this article proposes an analytical validation method for geometric error models based on the error transformation equation. The principle of the method is elaborately explained, and its correctness is verified through specific model verification example. The method proposed in this article enables rapid and accurate model correction and iteration, effectively reducing the economic and time costs of model validation in the current geometric error compensation process. Therefore, the method provides guidance for standardising the modelling process and could be widely applied to various structural forms of measurement and machining systems.

On the Lanczos Method for Computing Some Matrix Functions

The study of matrix functions is highly significant and has important applications in control theory, quantum mechanics, signal processing, and machine learning. Previous work has mainly focused on how to use the Krylov-type method to efficiently calculate matrix functions f(A)β and βTf(A)β when A is symmetric. In this paper, we mainly illustrate the convergence using the polynomial approximation theory for the case where A is symmetric positive definite. Numerical results illustrate the effectiveness of our theoretical results.

Fault diagnosis of computer numerical control machine tools table feed system based on digital twin and machine learning

Fault diagnosis of computer numerical control machine tools table feed system based on digital twin and machine learning

Control and monitor bottle filling, capping and labelling machine using a programmable logic controller and human machine interface

Bottle filling, closing, and labellingmachine control and monitoring tool using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). This tool is designed to optimize the production process in the bottled beverage industry,with dimensions of 200 cm × 70 cm × 100 cm. The conveyor transports bottles through the filling, capping, and labeling units. In each unit, sensors are installed to detect the presence of bottles. Bottle liquid volume is determined through time settings inputted through the HMI,and the filling is performed by a water pump. After filling, bottles are capped and tightened mechanically using an air impact system. Labeling is handled by two DC motors which unroll the label and rotate the bottle, ensuringthe label adheres evenlyto all sides of the bottle. The number of bottles produced is calculated using a capacitive proximity sensor and displayed on the HMI. Testing results show that the system effectivelycontrols and monitors the bottle filling, capping, and labeling process viaPLC and HMI. Based on the test results on the bottle filling unit, the system can fill water into the bottle with a maximum percentage error of 0.5% on a 1000 ml volume bottle. In the capping unit, the success rate achieved is 70%, while the success rate in the bottle labeling unit is 80%.

RANCANG BANGUN MESIN PEMURNIAN VIRGIN COCONUT OIL (VCO) DENGAN METODE SENTRIFUGAL BERBASIS INTERNET OF THGINGS (IoT)

Virgin Coconut Oil (VCO) is a virgin coconut oil produced from the extraction process of fresh coconut meat without the use of chemicals or high temperatures. VCO has high economic value with various health benefits. The process of making VCO involves a centrifugal machine to separate the oil from coconut milk. However, the control of the VCO Purification machine still relies on manual intervention by the operator, which can lead to human error and affect production efficiency. In order to improve efficiency and reduce the risk of human error, Internet of Things (IoT) and Mobile Application technologies can be applied in the control of VCO Purification machines. The programming language used is PHP because it can be accessed on various platforms, especially Mobile. The sensor used is an IR (Infrared) speed sensor for measuring rotational speed. The Mobile Application can be a convenient interface for operators to control and record the operation history of the VCO purification machine. This research has succeeded in developing an IoT and Mobile Application-based control system that is effective in controlling VCO purification machines, increasing production efficiency, and reducing the risk of human error.

Toward a digital twin of a robot workcell: standards and methods

Digital twins are poised to improve the engineering, operation, and management of manufacturing facilities. However, implementing digital twins has been a challenge primarily due to a lack of resources and the absence of standardized digital twin frameworks and methods. This paper describes creating a digital twin of a robot workcell using available standards, tools, and methods. The workcell comprises collaborative robot arms, a computer numeric control (CNC) machine tool, and a coordinate measuring machine (CMM). The ISO 23247 standard provides a guideline for building the digital twin. Data are collected from physical devices and the MTConnect standard provides a format for communicating the data between the physical equipment and their digital counterparts. The machine components in the workcell are represented as models in the virtual world. This research shows that the above standards and methods support building a digital twin of a robot workcell. The data collected and communicated can be used to improve workcell functions such as quality management and predictive maintenance.

Evaluation of the accuracy of digital impressions with different scanning strategies: An in vitro study

ObjectivesTo evaluate the effects of three different scanning strategies on the trueness and precision of optical impressions obtained with four intraoral scanners (IOSs). MethodsThe reference maxillary dental arch model was fabricated using Telio CAD, and the reference digital reference cast was obtained using a computer numerical control machine and an optical scanner (E4, 3Shape, Copenhagen, Denmark). Test scans were performed with four different IOSs (TRIOS3, MEDIT i700, CS 3600, and iTero Element 5D) by an experienced operator and three different scanning strategies (S1: manufacturer-recommended, S2: optimal per previous literature, and S3: experimental). The scan duration was recorded for each scan. All scans were converted to standard tessellation language format and imported into Geomagic Control X. The accuracy was measured by absolute deviation/distance between aligned surfaces. Data of trueness and precision of each IOS and scan duration were statistically compared using analysis of variance for repeated measures and Bonferroni post-hoc test (p < .05). ResultsNo significant differences in trueness were found among strategies (S1: 9.98 µm, S2: 11.93 µm, S3: 8.84 µm; p = .388) in Trios 3 and iTero Element 5D (S1: 12.24 µm, S2: 11.53 µm, S3: 10.71 µm; p = p = .279). Scanning strategy S3 with MEDIT i700 achieved greater trueness (7.33 µm) than S2 (16.33 µm, p < .05), while no significant difference was noted between S1 (10.44 µm) and S3 (p = .291). S3 showed the highest trueness (16.28 µm) compared to S2 (24.05 µm) and S1 (24.78 µm, p < .001) for CS 3600, with no difference between S1 and S2 (p = .457). Trios 3 had higher precision with S2 (22.46 µm) than S3 (31.69 µm, p < .05), and no significant differences between S1 (25.67 µm) and S2/S3 (p > .05). MEDIT i700 with S3 (29.52 µm) was more precise than both S1 (39.52 µm) and S2 (46.24 µm) (p < .001) with no difference between the last two (p = .302). S2 yielded the highest precision (44.93 µm) compared to S3 (61.81 µm) and S1 (76.53 µm) (p < .001) for CS 3600, with S3 more precise than S1 (p < .001). Similarly, iTero Element 5D showed S2 as the most precise (30.19 µm) compared to S3 (42.80 µm) and S1 (44.45 µm) (p < .05), with no difference between S1 and S3 (p = .472).Scan durations were shorter for S3 and S1 compared to S2 in Trios 3 (p < .001), and S3 was faster than S1 and S2 for MEDIT i700 (p < .001). CS 3600 scans with S1 were quicker than S2 and S3 (p < .001). For iTero Element 5D, no significant differences were found between S1 and S3 (p = .511), but S2 was slower than both (p < .001). ConclusionsScanning strategies significantly affect the accuracy and scan duration of optical impressions. Specifically, S3 provided the best trueness with both the MEDIT i700 and the CS 3600 while the S2 strategy demonstrated the highest precision for most scanners. Overall, the S1 and S3 strategies resulted faster than S2 among the devices evaluated. Clinical SignificanceThe results suggest that the experimental scan strategy may optimize the use of intraoral scanners in clinical practice, potentially leading to more accurate and time-efficient dental impressions.

Hyper CLS-Data-Based Robotic Interface and Its Application to Intelligent Peg-in-Hole Task Robot Incorporating a CNN Model for Defect Detection

Various types of numerical control (NC) machine tools can be standardly operated and controlled based on NC data that can be easily generated using widespread CAD/CAM systems. On the other hand, the operation environments of industrial robots still depend on conventional teaching and playback systems provided by the makers, so it seems that they have not been standardized and unified like NC machine tools yet. Additionally, robotic functional extensions, e.g., the easy implementation of a machine learning model, such as a convolutional neural network (CNN), a visual feedback controller, cooperative control for multiple robots, and so on, has not been sufficiently realized yet. In this paper, a hyper cutter location source (HCLS)-data-based robotic interface is proposed to cope with the issues. Due to the HCLS-data-based robot interface, the robotic control sequence can be visually and unifiedly described as NC codes. In addition, a VGG19-based CNN model for defect detection, whose classification accuracy is over 99% and average time for forward calculation is 70 ms, can be systematically incorporated into a robotic control application that handles multiple robots. The effectiveness and validity of the proposed system are demonstrated through a cooperative pick and place task using three small-sized industrial robot MG400s and a peg-in-hole task while checking undesirable defects in workpieces with a CNN model without using any programmable logic controller (PLC). The specifications of the PC used for the experiments are CPU: Intel(R) Core(TM) i9-10850K CPU 3.60 GHz, GPU: NVIDIA GeForce RTX 3090, Main memory: 64 GB.

Structural integrity assessment of pipe elbows: Burst test and finite element analysis

In this study, the failure pressures of pipe elbows were compared with those predicted using Level 3 numerical assessment method (Finite Element Method). Four 90-degree pipes elbows representing a pristine pipe, a pipe with a single corrosion defect, a pipe with longitudinally aligned interacting defects, and a pipe with a circumferentially aligned interacting defects, were subjected to internal pressure based on the ASME B31.3–2012 Burst Test standard until failure. The Sch-80 pipes were made of ASTM A234 WPB steel with a wall thickness and bending radius of 12.7 mm and 305 mm respectively. The corrosion defects were simulated on the exterior surface of the pipe elbows using computer numerical control (CNC) machine to generate a machined version of the corrosion defect. The results revealed that corrosion defects significantly reduce the burst pressure of pipe elbows, with longitudinally aligned interacting defects causing the largest reduction of 20.9 % compared to pristine pipe. The comparison between the Level 3 numerical assessment method and burst test showed close agreement with a maximum difference of 4.79 %, confirming the accuracy and reliability of the numerical method.

Robust Control of Electrical Machines in Renewable Energy Systems: Challenges and Solutions

The increasing global demand for energy driven by population growth necessitates a shift towards renewable energy sources to address sustainability and environmental concerns. Renewable energy sources and how they function in tandem with electrical equipment to generate power are covered extensively in this study. Renewable sources like solar-thermal, hydro, wind, wave, tidal, geothermal, and biomass-thermal utilize electric machines to convert various forms of stored energy into electricity. The paper classifies these machines based on their design and application in renewable systems, highlighting the most common types, including DC, induction, and synchronous machines. It also evaluates their performance according to efficiency, power density, and cost-effectiveness. A primary focus is on the challenges associated with controlling electrical machines in renewable energy systems, including issues related to intermittency, grid integration, nonlinear dynamics, fault tolerance, harmonics, efficiency optimization, thermal management, scalability, real-time control, and cost constraints. The paper concludes by discussing the need for advanced control strategies and solutions to address these challenges, aiming to enhance a reliability, efficiency, and performance of renewable energy systems.

A Novel Predictive Modeling for Student Attrition Utilizing Machine Learning and Sustainable Big Data Analytics

Student attrition poses significant societal and economic challenges, leading to unemployment, lower earnings, and other adverse outcomes for individuals and communities. To address this, predictive systems leveraging machine learning and big data aim to identify at-risk students early and intervene effectively. This study leverages big data and machine learning to identify key parameters influencing student dropout, develop a predictive model, and enable real-time monitoring and timely interventions by educational authorities. Two preliminary trials refined machine learning models, established evaluation standards, and optimized hyperparameters. These trials facilitated the systematic exploration of model performance and data quality assessment. Achieving close to 100% accuracy in dropout prediction, the study identifies academic performance as the primary influencer, with early-year subjects like Mechanics and Materials, Design of Machine Elements, and Instrumentation and Control having a significant impact. The longitudinal effect of these subjects on attrition underscores the importance of early intervention. Proposed solutions include early engagement and support or restructuring courses to better accommodate novice learners, aiming to reduce attrition rates.

Comparative study of the two DTC (6S - 12S) approaches applied to PMSM equipped with an IP regulator

Direct torque control was introduced in 1980 for induction machine for torque and flux control and developed for MSAP in 1990. DTC is gaining popularity due to its simple control structure and easy implementation. The principle of direct torque control (DTC) of the asynchronous machine was introduced in 1985 by I. Takahashi as an alternative to flux-directed vector control (FOC). It is thanks to its simple control structure that it gains popularity and its easy implementation that it has opened a new horizon in the field of variable speed control of electric drives. Indeed, direct torque control (DTC) has benefited in recent years from significant methodological advances in operation and technological development following the introduction of power electronics and digital electronics and the implementation of possible and very usable control algorithms. In conjunction with these technological advances, the scientific community has developed several control approaches to control the operation of electrical machines. In this context, this article presents a comparative study of the different direct torque control (DTC) strategies and structures of the permanent magnet synchronous machine (MSAP). We propose the algorithm of this control making it possible to provide solutions to the ripples of the torque and the stator flux in order to reduce them by adopting a method of compensating the effects of progression by passing from the six sector DTC (DTC – 6S: classic and modified) then develop the twelve-sector DTC (DTC-12S) whose purpose is to minimize ripples and control the switching frequency of the inverter. The simulation graphs presented will clearly show the difference between the different controls techniques cited.

A Method for Generating Toolpaths in the Manufacturing of Orthosis Molds with a Five-Axis Computer Numerical Control Machine

This paper proposes a new algorithm for the automatic generation of toolpaths for machining complex geometric positions, such as molds used in orthosis production. The production of individualized orthoses often requires the use of multi-axis machining systems, such as five-axis machines or industrial robots. Typically, complex and expensive CAD/CAM systems are used to generate toolpaths for these machines, requiring the definition of a machining strategy for each surface. While this approach can achieve a reliable and high-quality machining process, it is very time-consuming and makes it challenging to meet the criteria for rapid production of orthopedic aids. Given that their production is a custom-made process using individual shapes as inputs, the toolpath generation process becomes even more demanding. To address these challenges, this paper proposes an algorithm suitable for the automatic generation of toolpaths for such complex positions. The proposed algorithm has been tested and has proven to be robust and applicable.