Speed Settings Research Articles

Wheelchair control system for the disabled based on EMOTIV sensor gyroscope

In this study, a wheelchair control system (WCS) was designed and constructed that utilizes an EMOTIV gyroscope sensor for comfortable wheelchair movement. The proposed WCS involves an electroencephalograph (EEG), DC motors, an electronic wheelchair, a microcontroller, and a laptop. The control system algorithm is bulit in Arduino microcontroller using C++ language. The WCS comprises 15 states and is dependent on head motions. There are 12 motor speed settings and eight wheel rotary radius cases. The WCS was tested by 10 women and men aged between 20 and 70 years. The system was implemented and tested in both indoor and outdoor environments to represent smooth and rough surfaces. It was also evaluated at various directions and speeds as well as at rotational radii (interior and exterior areas), and it prevented collisions with barriers using an ultrasonic sensor and reduced the wheelchair movement response time. The control system algorithm achieves an average response time of approximately 1–2 s to move the wheelchair in the specified direction. The performance metrics were also investigated and included sensitivity, specificity, and accuracy with encouraging results: The average WCS accuracy is 99.16%, sensitivity is 99.2%, and specificity is 99.15%. The overall performance is approximately 98%. The accuracy and response times of this WCS outperforms previous research findings.

Emphasizing speed or accuracy in an eye-tracking version of the Trail-Making-Test: Towards experimental diagnostics for decomposing executive functions.

The Trail-Making-Test (TMT) is one of the most widely used neuropsychological tests for assessing executive functions, the brain functions underlying cognitively controlled thought and action. Obtaining a number of test scores at once, the TMT allows to characterize an assortment of executive functions efficiently. Critically, however, as most test scores are derived from test completion times, the scores only provide a summary measure of various cognitive control processes. To address this problem, we extended the TMT in two ways. First, using a computerized eye-tracking version of the TMT, we added specific eye movement measures that deliver a richer set of data with a higher degree of cognitive process specificity. Second, we included an experimental manipulation of a fundamental executive function, namely participants’ ability to emphasize speed or accuracy in task performance. Our study of healthy participants showed that eye movement measures differed between TMT conditions that are usually compared to assess the cognitive control process of alternating between task sets for action control. This demonstrates that eye movement measures are indeed sensitive to executive functions implicated in the TMT. Crucially, comparing performance under cognitive control sets of speed vs. accuracy emphasis revealed which test scores primarily varied due to this manipulation (e.g., trial duration, number of fixations), and which were still more sensitive to other differences between individuals (e.g., fixation duration, saccade amplitude). This provided an experimental construct validation of the test scores by distinguishing scores primarily reflecting the executive function of emphasizing speed vs. accuracy and those independent from it. In sum, both the inclusion of eye movement measures and of the experimental manipulation of executive functions in the TMT enabled a more specific interpretation of the TMT in terms of cognitive functions and mechanisms, which offers more precise diagnoses in clinical applications and basic research.

Controllable tensile performance of additively manufactured Al–Fe alloy

Achieving both high strength and ductility is challenging in additive manufacturing of Al alloys using the laser powder bed fusion (L-PBF) process by altering the laser conditions to control the microstructural characteristics. The current work focuses on the influence of varying laser energy density (ED), which is adjusted by different sets of laser power (P) and scan speed (v), on the microstructure-tensile property relationships of the L-PBF-fabricated Al–2.5%Fe alloy under varying laser conditions (P = 204–230 W, v = 450–600 mm/s) with a fixed powder layer thickness (t = 30 μm) and hatch distance (h = 30 μm). With increasing ED (= P/v·t·h), a slight increase in the average size of the columnar α-Al grains was found in the experimental samples concurrently with a higher fraction of <001>-oriented grains. Nanosized particles of the Al6Fe phase with an increased tendency to interconnect were observed in the matrix inside the melt pool, and the θ phase formed within the submicron-sized cellular structure along the melt pool boundaries (MPBs). A low tensile ductility, induced by the local microstructural inhomogeneities across MPBs, was found in all specimens tensile-deformed along the building direction, which was characterized by a preference fracture along the MPBs. At higher applied ED, the tensile ductility of the experimental Al–2.5Fe alloy was significantly improved with only a slight decrease in tensile strength. The difference in concentration of Fe across the MPBs in the matrix was also moderately diminished, which is consistent with the reduced local difference in microhardness across the MPBs under higher ED conditions. Therefore, the present results demonstrate that local microstructural inhomogeneities across MPBs can be controlled by the laser conditions, thereby producing both high strength and good ductility in the L-PBF processed Al–Fe alloys.

PENGARUH KECEPATAN INJEKSI, TEKANAN INJEKSI DAN POSISI MOLD PADA PRODUKSI KURSI SANTAI BERBAHAN DASAR POLYPROPYLENE (PP)

Injection molding is making products made from plastic materials through melted plastic and then injected into a mold or mold. The plastic lounge chair is made of polypropylene (PP) by injection molding. In the injection molding process, there are parameters of injection speed, pressure, and molding position. This study aims to determine the effect of injection speed, pressure, and mold position. Injection speed, injection pressure, and improper mold position can produce a lounge chair with short-shot defects. Short-shot defects cannot be repaired but must be recycled by chopping them up to be reused as additional material for producing plastic products; this will increase operational costs. Efforts to reduce short shots can be done by changing the speed parameter settings, injection pressure, and mold position. Plastic lounge chairs, according to standards, were obtained by inverted mold position and injection speed settings in zones 1, 2, 3, 4, and 5 of 70, 60, 50, 45, and 30 in mm/s units. The injection pressures are 95, 85, 75, 65, and 55 bar.

Effect of Welding Parameters on Mechanical Properties and Microstructure of Friction Stir Welded AA7075-T651 Aluminum Alloy Butt Joints.

The aim of this study was to examine the mechanical properties of 5-mm-thick AA7075-T651 alloy using three different welding velocities, 50, 75 and 100 mm/min, and four various sets of tool rotation speeds: 400, 600, 800 and 1000 rpm. All obtained joints were defect-free. In all cases, the values of UTS exceeded 400 MPa, corresponding to 68.5% minimum joint efficiency. The highest value of 447.7 MPa (76.7% joint efficiency) was reported for the joint produced via 400 rpm tool rotation speed and 100 mm/min welding velocity. The SZ microstructure of the strongest joint was characterized by a 5.2 ± 1.7 μm grain size and microhardness of approximately 145 HV0.1. The TMAZ/HAZ interface was identified as the low-hardness zone (105–115 HV0.1, depending on parameters), where the failure of the tensile samples takes place. The fracture mechanism is dominated by a transgranular ductile rupture with microvoid coalescence.

Workload management and server speed setting for cost‐performance ratio optimization

AbstractThe cost‐performance tradeoff is a fundamental issue in a data center for cloud computing, which is closely related to two key metrics that both cloud consumers and service providers care the most, that is, quality of service and cost of service. While there are different definitions of quality of service, the average response time is a common choice of performance metric. While there are various considerations in cost of service, the average power consumption is a common choice of cost metric. Hence, the cost‐performance tradeoff becomes the power‐performance tradeoff. In this article, we deal with the power‐performance tradeoff at the data center level. We study cost‐performance ratio optimization by using the techniques of workload management and server speed setting. In particular, we make the following tangible contributions. We solve three optimization problems, that is, (1) the workload management problem—to find a workload distribution, such that the cost‐performance ratio is minimized; (2) the server speed setting problem—to find a server speed setting, such that the cost‐performance ratio is minimized; (3) the workload management and server speed setting problem—to find a workload distribution and a server speed setting, such that the cost‐performance ratio is minimized. All the three optimization problems are analytically defined as multivariable optimization problems based on M/M/m queueing systems for multiple heterogeneous multiserver systems, together with two power consumption models, that is, the idle‐speed model and the constant‐speed model. Our approach makes it possible to quantitatively evaluate and optimize the cost‐performance ratio of a data center within a rigorously developed framework. Each multivariable optimization problem is transformed to a nonlinear system of equations. Due to the sophistication of these equations, they are solved algorithmically by a numerical procedure. Furthermore, we provide approximate, accurate, and analytical solutions to the first two problems. Performance data are demonstrated for each problem, and the accuracy of our approximate solutions are also discussed. To the best of the author's knowledge, this is the first paper which analytically and algorithmically minimizes the cost‐performance ratio of a data center with multiple heterogeneous multiserver systems using the techniques of workload management and server speed setting.

Development, validation and application of an energy model for energy efficient operation of parallel pump systems

Parallel pumps are commonly applied in chilled water and hot water systems to handle broad water flow variation. The application of variable frequency drives leaves the sequencing control of parallel pumps a tricky problem, especially if the pumps have various sizes or/and experience various speeds. The objective of this paper is to develop and validate an energy model to optimize the operation of parallel pump systems. First a comprehensive energy model is developed based on the affinity and Kirchhoff Laws. The pump installed head is applied to eliminate the impact of the pump fittings and the drive efficiency is considered to obtain the true electrical power. Then, the energy model is constructed and validated for a parallel pump system, which has three 284 L/s pumps with one as a backup pump and each powered by a 150 kW motor. Finally, the validated model is applied to identify the energy efficient operation. The results reveal that one-pump operation outperforms two-pump operation at lower flow range with the switchover flowrate decreasing from 300 L/s to 240 L/s as the controlled pump installed head varies from a constant setpoint to a reset variable setpoint. Moreover, faulty various speed settings result in the electrical power waste of 20 kW for the lower-speed pump.

Optimization of a gas network fuel consumption with genetic algorithm

In this paper genetic algorithm (GA) was used for the optimization of two natural gas network, the study focuses on fuel consumption minimization of the second gas network. Studies using GA to simultaneously optimize a gas network and a compressor station based on the constraint of the gas network and compressor station are limited. The relationship between several compressor speed and the total fuel consumption and the relationship between the sum of pressure drop in compressor station loops and compressor inlet flow are assessed for optimization. For this purpose, the optimization of two networks was presented and the results were compared with result from analytical methods. The first network problem was to determine the flow rates and node pressures under a given load, which serves as a guide in using GA. Comparison with result from analytical solution showed good agreement of predicted values. The second network consisted of two compressor stations, each containing six compressors with the objective to optimize the fuel consumption of the system. The simulation was divided into two main simulations, the first simulation was the flow optimization, which results in the optimum flow, based on the fitness function, which is the summation of pressure loss for each compressor station. In the second simulation which was the speed optimization, the optimum set of compressor speed was obtained which depends on the fitness function, which is the minimum fuel consumption, the flow obtained from the flow optimization served as input and remained constant. All speeds were simulated together. The predicted results were compared with literature and showed GA can be used for compressor station fuel optimization but still requires improvement. Based on the outcomes, data on natural gas network operations should be accessible to encourage studies on fuel consumption and CO2 emissions minimization.

Acceleration of imaging in atomic force microscopy working in sub-resonance tapping mode.

Sub-resonance tapping (SRT) mode of atomic force microscopy (AFM) enables researchers to image surfaces with well-controlled load forces and to collect maps of multiple physical properties of samples. The major bottleneck of this mode is a relatively low scan speed compared to other scanning modes. This paper presents a novel control algorithm that substantially improves the scanning speed over the standard SRT. We propose naming the new modality Trajectory Tracking SRT (TT-SRT). In contrast with the standard SRT control, TT-SRT uses the feedback within every single touch of the sample by the AFM probe. To demonstrate the advantage of TT-SRT, we conduct scans on a variety of samples with differing topologies, roughnesses, and mechanical properties. Each sample region is scanned with both standard SRT and TT-SRT at the same set of speeds. The control gains are tuned before each scan for maximum performance in each mode. Performance is evaluated by selecting a given level of image quality and finding the maximum speed that can be achieved by each algorithm. We find that with increased demand for data quality, the utility of TT-SRT becomes more apparent; for example, the speed of TT-SRT can be ten times faster or more than standard SRT for a reasonable expectation of data quality.

KMOEA: A Knowledge-Based Multiobjective Algorithm for Distributed Hybrid Flow Shop in a Prefabricated System

In this article, a distributed hybrid flow shop scheduling problem with variable speed constraints is considered. To solve it, a knowledge-based adaptive reference points multiobjective algorithm (KMOEA) is developed. In the proposed algorithm, each solution is represented with a 3-D vector, where the factory assignment, machine assignment, operation scheduling, and speed setting are encoded. Then, four problem-specific lemmas are proposed, which are used as the knowledge to guide the main components of the algorithm, including the initialization, global, and local search procedures. Next, an efficient initialization approach is presented, which is embedded with several problem-related initialization rules. Furthermore, a novel Pareto-based crossover heuristic is designed to learn from more promising solutions. To enhance the local search abilities, a speed adjustment local search method is investigated. Finally, a set of instances generated based on the realistic prefabricated production system is tested to verify the efficiency and effectiveness of the proposed algorithm.

Hemolytic Footprint of Rotodynamic Blood Pumps.

In preclinical examinations, rotodynamic blood pumps (RBPs) are predominantly evaluated at design-point conditions. In clinical practice, however, they run at diversified modes of operation. This study aimed at extending current preclinical evaluation of hemolytic profiles in RBPs toward broader, clinically relevant ranges of operation. Two implantable RBPs - the HeartMate 3 (HM3) and the HeartWare Ventricular Assist Device (HVAD) - were analyzed at three pump speeds (HM3: 4300, 5600, 7000 rpm; HVAD: 1800, 2760, 3600 rpm) with three flow rates (1-9L/min) per speed setting. Hemolysis measurements were performed in heparinized bovine blood. The delta free hemoglobin (dfHb) and the normalized index of hemolysis (NIH) served as hemolytic measures. Statistical analysis was performed by multiple comparison of the 9 operating conditions. Moreover, computational fluid dynamics (CFD) was applied to provide mechanistic insights into the interrelation between hydraulics and hemolysis by correlating numerically computed hydraulic losses with in-vitro hemolytic measures. In both devices, dfHb increased toward increasing speeds, particularly during low but also during high flow condition. By contrast, in both RBPs magnitudes of NIH were significantly elevated during low flow operation compared to high flow conditions (p<0.0036). Maps of hemolytic metrics revealed morphologically similar trends to in-silico hydraulic losses (r>0.793). While off-design operation is associated with increased hemolytic profiles, the setting of different operating conditions render a preclinical prediction of clinical impact with current hemolysis metrics difficult. The identified increase in hemolytic measures during episodes of off-design operation is highlighting the need to consider worst-case operation during preclinical examinations.

Special physical training of skaters in the preparatory period at the stage of specialized basic training

In the process of long-term training, the stage of specialized basic training coincides with the pre-adolescent period of development of skaters, which requires increased attention of coaches, psychologists and doctors. Purpose: to determine the features of physical training of skaters in the preparatory period. Research methods: methods of theoretical level of research were used: analysis, comparison, induction, deduction, systematization and generalization of scientific and methodical literature, legal documents and information resources of the Internet on the problem of physical training of skaters in the preparatory period. Results: special physical training of skaters in the preparatory period has a narrower focus and is based on the biomechanical structure of the elements of figure skating. It is aimed at the development of physical abilities due to the specifics of figure skating as a sport, as well as the peculiarities of competitive activities in it. Most of the training activities of skaters are working on jumping elements. To master multi-turn jumps it is necessary to develop a sufficient level of speed and strength abilities (set of high speeds during the run-up period) and strength abilities (push-ups, keeping the body in a group in flight, landing). Today, the ability to keep the group is one of the most important conditions for the jump in three and four turns. Conclusions: in the available scientific and methodological literature there are contradictory data characterizing the features of special physical training of skaters in the preparatory period. The issue of optimizing physical training in figure skating at the stage of specialized basic training in the preparatory period, taking into account the age, physical and functional characteristics of athletes, by redistributing the means of general and special training, as well as regulating the intensity of physical activity, taking into account functional status which requires further study.

Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method.

Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination (R2 > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest R2 value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift.

An Image Classification Algorithm Based on Hybrid Quantum Classical Convolutional Neural Network

Quantum machine learning is emerging as a strategy to solve real-world problems. As a quantum computing model, parameterized quantum circuits provide an approach for constructing quantum machine learning algorithms, which may either realize computational acceleration or achieve better algorithm performance than classical algorithms. Based on the parameterized quantum circuit, we propose a hybrid quantum-classical convolutional neural network (HQCCNN) model for image classification that comprises both quantum and classical components. The quantum convolutional layer is designed using a parameterized quantum circuit. It is used to perform linear unitary transformation on the quantum state to extract hidden information. In addition, the quantum pooling unit is used to perform pooling operations. After the evolution of the quantum system, we measure the quantum state and input the measurement results into a classical fully connected layer for further processing. We demonstrate its potential by applying HQCCNN to the MNIST dataset. Compared to a convolutional neural network in a similar architecture, the results reveal that HQCCNN has a faster training speed and higher testing set accuracy than a convolutional neural network.

A decision model on human-robot collaborative routing for automatic logistics

This paper studies an integrated human-robot routing problem arising in collaborative order picking systems. Travelling routes of pickers and robots interact with each other and simultaneously determine the start time of tasks. A mixed-integer programming model is proposed which aims to minimize the total task completion time by optimizing both pickers’ and robots’ routes. Moreover, a variable neighborhood search and dynamic programming -based heuristic algorithm is developed for solving the problem in large-scale environments. Numerical experiments are conducted to prove the necessity of the proposed model and also validate the efficiency of the proposed heuristic algorithm. The results indicate the methodology can yield solutions with smaller optimality gap within a reasonable period of time, in comparison with an intuitive but common decision rule. A sensitivity analysis is also conducted to derive a number of managerial implications regarding the configuration of pickers and robots and robots’ speed setting.

Profit Maximization in a Federated Cloud by Optimal Workload Management and Server Speed Setting

In an environment with multiple heterogeneous multiservers across multiple clouds and data centers, optimal workload management and server speed setting makes strong impact on the aggregated performance, cost, and profit of a cloud service provider. Such a situation provides us a more challenging opportunity to address and discuss profit maximization of a service provider in a wider scale and to generate more significant influence. In this paper, we investigate profit maximization by optimal workload management and server speed setting for multiple heterogeneous multiservers in a federated cloud or a geo-distributed data center. The heterogeneous multiservers have different sizes, speeds, power consumption models, workload, performance, costs, and profit. To conduct rigorous study, each multiserver system is modeled by an M/M/m queueing system, such that the profit of a multiserver system can be characterized analytically. We address two problems, i.e., workload management without server speed setting and workload management with server speed setting. Both problems are formulated as multi-variable optimization problems. We develop numerical algorithms to solve these problems. We also provide numerical data for the purpose of illustration. To the best of the author's knowledge, this is the first paper which analytically discusses profit maximization for multiple heterogeneous multiservers in a federated cloud or a geo-distributed data center using queueing systems.

Temporary materials used in prosthodontics: The effect of composition, fabrication mode, and aging on mechanical properties

PurposeTo evaluate the effect of composition, fabrication mode, and thermal cycling on the mechanical properties of different polymeric systems used for temporary dental prostheses. Materials and methodsStandard bar-shaped specimens (25 × 2 × 2 mm) were fabricated of six polymeric systems of varying compositions and fabrication modes (n = 10/group): conventional PMMA (Alike, GC) – group CGC; conventional PMMA (Dêncor, Clássico) – group CD; bis-acryl (Tempsmart, GC) – group BGC; bis-acryl (Yprov, Yller) – group BY; milled PMMA (TelioCAD, Ivoclar) - group MI; 3D printed bis-acryl – (Cosmos Temp, Yller) group PY. Half of the specimens were subjected to 5000 thermal cycles (5 °C to 55 °C). Three-point bending tests were performed using a universal testing machine with a crosshead speed set to 0.5 mm/min. Flexural strength and elastic modulus were calculated from the collected data. FTIR spectra were recorded pre and post curing and after thermal cycling to evaluate material composition and degree of conversion. Energy-dispersive spectroscopy (EDS) and scanning electron microscope (SEM) were utilized to examine the composition and micromorphology of the systems, respectively. Data were analyzed using two-analysis of variance and Tukey tests (α = 0.05). ResultsFTIR spectra indicated that BGC, BY and PY groups corresponded to urethane dimethacrylate systems (bis-acryl), while CGC, CD, and MI groups corresponded to monomethacrylate systems, polymethyl methacrylate (PMMA). Bis-acryl BGC system yeilded the highest flexural strength (80 MPa), followed by the milled PMMA MI system (71 MPa), both statistically significant different relative to other groups. Bis-acryl BY exhibited the lowest flexural strength (27 MPa). Thermocycling significantly increased the flexural strength of all polymeric systems (∼10–15 MPa), except for the 3D-printed PY group. Bis-acryl BGC (1.89 GPa) and conventional PMMA CGC (1.66 GPa) groups exhibited the highest elastic modulus, followed by milled PMMA MI group (1.51 GPa) and conventional PMMA CD (1.45 GPa) systems, with significant difference detected between BGC group and MI and CD groups. The 3D printed PY (0.78 GPa) and bis-acryl BY (0.47 GPa) systems presented the lowest elastic modulus. Thermocycling did not have a significant influence on the elastic modulus. FTIR spectra indicate water sorption and release of unreacted monomers as well as increased degree of conversion (∼5–12%) after thermal cycling. ConclusionComposition and fabrication mode and thermal cycling significantly affected the mechanical properties of polymeric systems used for temporary dental prostheses.

Interaction of printing speed and temperature settings on the build plate adhesion of 3D-printed polylactide acid parts

ABSTRACT Fused filament fabrication, also called material extrusion, is a widespread used 3D-printing process which allows to manufacture parts with a high freedom of design at low costs. A common issue is the deformation of parts during the printing process caused by thermal stress and an insufficient adhesion. Despite the widespread usage of material extrusion only few publications dealing with this topic and it is yet nearly unknown, which process parameters have an influence onto the part adhesion nor how they interact among each other. This publication investigates how the adhesion between part and build surface is affected by the most important process parameters. The influence of the first layer’s height, printing speed, nozzle temperature, and build surface temperature was determined for three different build surface materials. Furthermore, the interactions of these parameters among each other were investigated. It was found that the first layer’s height has a strong influence onto the adhesion, which can be increased up to 0.56 MPa. Also, a strong dependence of printing speed, build surface temperature and nozzle temperature among each other was found.

Pengaturan Kecepatan Motor Induksi 3 Fasa Dengan Metode V/F Konstan Dan Kontrol PID-CHR

Its sturdy construction and simple maintenance make the induction motor the main driving machine in the industry. Induction motor speed setting is one of the operating conditions that are often used so that an inverter 3 phase is needed as an induction motor speed regulator. Inverter 3 phase is a device used to make AC voltage 3 phase from dc voltage supply source. Inverter 3 phase used type Current Source Inverter that uses the Sinusoidal Pulse Width Modulation (SPWM) method with constant voltage / frequency control (v / f constant). In optimizing the motor response, it is used to control feedback with a low error rate, pid-CHR control is applied which can cover a wider range of operating conditions and is easily adjustable.

SISTEM MONITORING SPEED SETTING PADA ROLLER MIXER BERBASIS MIKROKONTROLER ARDUINO UNO

Roller mixer is a laboratory tool that serves to mix blood samples and reagents. In this case, the substances that are mixed are blood and anti-clotting agents (coagulants). In the process of mixing the blood, the timer and the rotational value of the motor are set by the selector switch. The design of the speed setting of the roller mixer tool is made so that the user can control and monitor how much the value of the motor speed used is displayed on the 16x2 LCD display. This research will be conducted at the Electronics Laboratory of Sari Mutiara University, Helvetia District, Medan City. This type of research method is experimental research, namely conducting direct experiments. The components in monitoring this tool are microcontroller, display, timer setting, speed setting and roller. After carrying out the research process on the design of this tool, the measurement results obtained from the Infrared Sensor are displayed on the LCD, with a minimum speed measurement of 36, Medium 38 and a maximum of 44 rpm. With a comparison from a thacometer with an average value of Minimum 44 Medium 54 and maximum 56.