Test plants or laboratory prototypes are essential for developing training activities in engineering. In the field of automation and control, simulators or high-fidelity equipment models commonly used in industrial processes are necessary. These tools allow engineering trainees to gain experience working with devices similar to those they will encounter in their professional contexts. This paper presents the design and simulation of a fly-cutting plant for academic use. A 3D model was developed in SketchUp, incorporating features typical of industrial plants. The system’s simulation was carried out in MATLAB R2023b using mathematical modeling. The primary contribution of this work is the design of a low-cost, compact industrial prototype that includes a conveyor belt and a continuous cutting mechanism, enabling the understanding and operation of large-scale industrial processes. Performance tests were conducted using MATLAB, Simulink, and Code Composer Studio. Subsequently, operational and cutting tests were performed using classical control techniques. Additionally, the design features of the fly-cutting plant, which can be easily implemented for process control training activities, are detailed. In engineering, teaching processes are in constant evolution, raising new challenges that must be satisfied to provide high-quality education according to the particular context in which it is being applied. With the development of new technologies, educational environments have undergone a significant transformation in the digital era. This evolution can be traced back to the Gutenberg printing press, which emerged in 1450 as a revolutionary tool for the dissemination of knowledge on a mass scale [ 1]. In the context of academia, the advent of the digital era is largely associated with the rise of information and communications technology (ICT). Initially, ICT enabled the development of innovative tools to enhance the accessibility and advancement of educational materials. Moreover, the emergence of web-based platforms paved the way for the advancement of educational technologies and interaction tools. These developments promoted collaborative learning, multiple intelligences, and the integration of mobile devices, ultimately improving engineering trainees’ comprehension and knowledge retention [ 1, 2, 3]. Another significant aspect of contemporary higher education is the implementation of learning management systems (LMSs) in virtual and distance learning environments. These systems leverage information and communications technology (ICT) tools to personalize learning processes, thus improving student motivation [ 4]. Additionally, the popularization of artificial intelligence (AI) has marked a significant evolution in the field of learning management systems (LMSs), particularly in higher education institutions. AI not only enhances the capabilities of existing digital tools but also introduces innovative features such as adaptive learning systems, research support tools, and autonomous or assisted teaching mechanisms. These advancements personalize the learning journey and align it with the individual needs of each learner [ 5]. The training processes for engineers in automation and control should focus not only on the handling of technological tools, time management, and collaborative work, but also on fostering consistent engagement with the challenges faced by society and industry. Therefore, it is crucial to define the value of academic work in automation and control processes, helping students to develop fundamental skills, including those related to analog circuits, digital electronics, dynamic systems analysis, introductory control, and other activities that require precision and robustness [ 6]. To enhance the rigor of academic work, it is vital to strengthen core engineering domains while establishing laboratories equipped with test plants that replicate authentic industrial processes. This will facilitate the integration of diverse scenarios beyond the academic domain. In recent years, test plants have gained significant interest due to two primary factors: First, the critical importance of automation and process control in the corporate landscape, coupled with the need for academic institutions to keep pace with these advancements [ 7]. Second, the high cost of laboratory equipment from companies such as Festo or Mitsubishi. As a result, many academic institutions have designed cost-effective, modular, and scalable test prototypes aimed at enhancing engineering education while also conducting research that has led to process improvements in industry. For example, in [ 8], applications for robotic manipulation and digital control were developed within an educational framework. Regarding fly-cutting plants and their role across different industrial sectors, numerous applications have been implemented using a wide range of system configurations or architectures. Table 1 provides a comparative analysis of existing fly-cutting designs used in both academic and industrial environments. The papers featured in this collection highlight a variety of insights related to plants and on-the-fly shearing systems, incorporating both theoretical and practical perspectives. For example, studies such as [ 11, 15, 20] explored academic subjects such as optimizing dynamic scenarios, analyzing transmission system performance, and creating electronic designs for cutting mechanisms. These studies achieved significant theoretical progress in dynamics and control. In contrast, research works including [ 14, 16] focused on specific advancements in cutting plants, with the aim of enhancing system precision and stability through advanced controllers such as SIEMENS PLC and PID algorithms. Additionally, novel strategies for generalized control were introduced to cut costs and boost integration. The research in [ 9, 10, 18] explored the usage of technologies such as FPGA and DTC to increase the efficiency of speed, position, and torque control, consequently minimizing waste and optimizing energy use. Finally, studies such as [ 12, 13, 17, 19] combined technological elements with material analysis to prolong the useful life of the components, implement vacuum sealing in MEMSs, and refine blade performance in industrial setups. These investigations contributed to both applied research and the development of practical solutions in industrial settings. Furthermore, other studies on flying shear plants, such as [ 21], introduced a three-dimensional model of a flying shear, focusing on structural and dynamic analysis of the shear process using MATLAB/SimMechanics and Solidworks/COSMOS motion. The results offer valuable theoretical insights into designing electronic control systems and optimizing parameters for similar flying shears. In [ 22], the mechanism for a sheet shearing plant was designed with an analytical focus on the losses generated in transformer cores due to irregular shearing. These works represent some of the advancements in the modeling of shear systems conducted at universities and research institutes, most of which remain at the simulation level. Another area of focus in prototype development at the academic level has been the integration of hardware development, where devices are manipulated or controlled through remote applications in addition to the use of simulations. In [ 23], a remote laboratory was developed for two test plants (an industrial robot and a mobile robot) using Java Servlet environments. In [ 24], a study was conducted on the implementation of a real-time control system for a 20 KVA power converter using the Texas Instruments LAUNCH-XL F28379D board. This research highlights the importance of employing dedicated hardware in control systems. Additional studies stress the value of using laboratory plants that replicate authentic industrial processes in an academic context. In [ 25], the authors emphasized the evolution of pedagogical methodologies and developed a state-space control system in a float-shield laboratory plant to replicate real-world environments in the classroom. As evidenced in the literature reviewed, research on flying shear prototypes has primarily focused on simulations of estimated mathematical models. The methodology employed in this study makes a significant contribution by designing and simulating a fly-cutting plant that considers real-world behavior. This ensures the replicability of our work and the full implementability of the presented prototype in academic settings. Another notable contribution of this research is its integration of concepts from control theory, mechanical engineering, and physical principles. This interdisciplinary approach provides a detailed understanding of the operation of the proposed fly-cutting plant and facilitates research across new areas. Additionally, this study contributes to the field of electronic engineering by bridging the industrial sector in the pursuit of efficient solutions to enhance processes through new technologies, such as augmented reality laboratories and 3D printing. These technologies enable the testing of designed prototypes prior to their final implementation. This research presents the design and simulation of a fly-cutting plant for implementing real-time control strategies in academic environments. The plant was designed using a three-dimensional modeling approach, enabling the creation of a digital prototype that could be subsequently implemented. The operational efficacy of the fly-cutting plant was validated through real-time simulations, with the plant represented in mathematical terms. This study makes additional contributions to the automation and control field within the Electronic Engineering Program at Universidad del Quindío, including the following: The design of a laboratory plant to emulate the continuous cutting process of moving parts, a procedure frequently performed in various industrial sectors. The definition of requirements and mechanisms is necessary to implement a fly-cutting plant on a laboratory scale. The development of applications using specialized tools for the design and simulation of real-time control systems, oriented toward the modeling and control of industrial processes at the laboratory scale. This contrasts to previous work, such as [ 26], which focused on robot manipulation. The design of a laboratory plant to emulate the continuous cutting process of moving parts, a procedure frequently performed in various industrial sectors. The definition of requirements and mechanisms is necessary to implement a fly-cutting plant on a laboratory scale. The development of applications using specialized tools for the design and simulation of real-time control systems, oriented toward the modeling and control of industrial processes at the laboratory scale. This contrasts to previous work, such as [ 26], which focused on robot manipulation. This paper is structured into distinct sections. First, the methodology, including the materials and methods used for the design and simulation of the fly-cutting plant, is outlined. Next, the results obtained and their analysis in relation to the implemented control strategy are presented. Finally, a comprehensive summary of the main conclusions derived from this research is provided. Fly-cutting plants or machines (also known as flying shears) are mechanical systems equipped with a cutting blade and a conveyor belt to transport the material to be processed. These devices operate either in mechanical synchronism between the cutting blade and the moving material or by matching their speeds with the assistance of additional electronic devices. Various manufacturers, such as RISHBIN, produce different types of fly-cutting machines. RISHBIN’s catalog includes metal plate cutting machines classified by cutting type: rotary, crank–rotary lever, eccentric crank, and pendulum plants [ 27]. An illustrative example is provided in [ 28], where a crank-type cutting machine is analyzed for kinematics, profile error, acceleration, and velocities across different cutting phases. Schneider Electric offers an alternative classification system for RISHBIN flying shears, dividing shear systems into T1, T2, and T3 types [ 29]. Figure 1 illustrates the T1 fly-shearing plant, which features a cutting system where the saw’s base supports the material and synchronizes its speed with the material while performing the cut. MATLAB (Matrix Laboratory) is a numerical computational tool that integrates capabilities for calculation, visualization, and programming within an interactive environment. It allows users to express problem solutions in a format similar to mathematical notation, with arrays serving as the fundamental data structure since they do not require explicit dimensioning. All data are represented with double precision, enabling more accurate calculations and easier interaction [ 30]. MATLAB provides a variety of toolboxes that offer specialized functions for diverse fields of knowledge. The Control Toolbox includes the PIDTuner application, which facilitates the automated adjustment of gains in designed controllers. The design process is graphical, enabling the evaluation of controller performance and robustness through associated graphical analyses. A key feature of PIDTuner is its ability to support controller design in both the time and frequency domains. Figure 2 illustrates the user interface of the MATLAB PIDTuner application [ 31]. SketchUp is a versatile 3D modeling tool that supports the creation of three-dimensional designs, models, and extended reality experiences. Available on multiple platforms, including desktop, web, and mobile, it is an excellent choice for professionals across various disciplines, particularly in engineering. One of its most notable features is the integration of artificial intelligence (AI) functionalities, which optimize and accelerate workflows, streamlining the design process. Figure 3 illustrates the graphical user interface of SketchUp’s desktop version. The structure of the designed fly-cutting plant is illustrated in Figure 4. The block diagram consists of two principal systems: The first is the mechanical system, which includes a conveyor belt and a cutting mechanism with three-dimensional movement along the X-, Y-, and Z-axes. The second is the electronic system, comprising a control board with peripherals and other control elements, a power circuit housing the main card for motor operation, and a switching circuit that allows the system to operate with internal devices or an external control device. The plant features a conveyor belt and a cutting mechanism that moves along the X-, Y-, and Z-axes. Each component was analyzed individually to meet the specified requirements. The following key elements were identified: Cutting system: This must be capable of creating markings or patterns on the conveyor belt. Conveyor belt: The system must be modular to facilitate easy relocation and stable to prevent vibrations from causing irregularities during the cutting process. Dimensions: The plant requires a fixed base on the floor with rollers positioned at a height of approximately 80 cm, corresponding to the hand height of an average operator. Ease of transport: As a structure designed for academic environments, it must be easy to move between spaces. Belt traction: The traction system comprises two rollers to ensure proper alignment and prevent the belt from deviating. One roller must be mechanically connected to a motor, controlled by electronic circuits. Location of the cutting system and circuit boards: The belt structure must include designated spaces to house the circuit boards and protect the electronic components. Tape material: The upper part of the tape must be smooth and allow for the erasure of the marks made with the cutting system. Cutting system: This must be capable of creating markings or patterns on the conveyor belt. Conveyor belt: The system must be modular to facilitate easy relocation and stable to prevent vibrations from causing irregularities during the cutting process. Dimensions: The plant requires a fixed base on the floor with rollers positioned at a height of approximately 80 cm, corresponding to the hand height of an average operator. Ease of transport: As a structure designed for academic environments, it must be easy to move between spaces. Belt traction: The traction system comprises two rollers to ensure proper alignment and prevent the belt from deviating. One roller must be mechanically connected to a motor, controlled by electronic circuits. Location of the cutting system and circuit boards: The belt structure must include designated spaces to house the circuit boards and protect the electronic components. Tape material: The upper part of the tape must be smooth and allow for the erasure of the marks made with the cutting system. The conveyor belt structure was designed using a SketchUp 3D model and will be constructed with 4 × 2 cm rectangular iron tubes of 0.8 mm gauge. One of the upper horizontal profiles, which supports the rollers, was designed to be fastened with bolts, allowing it to be disassembled if the conveyor belt or any component requires replacement. Figure 5 illustrates the designed structure of the conveyor belt. The rollers are essential for ensuring the proper rotation of the conveyor belt and were designed using SketchUp 3D Pro 2023 software to facilitate subsequent belt calibration and alignment. An 8 mm shaft-bearing system was used at one end of the belt to align the roller, which is driven by the motor through pulleys. This roller is a fixed drum roller that rotates in conjunction with the smooth shaft, enabling movement through the bearings. Figure 6 illustrates a representation of the fixed drum roller. The opposite end of the belt features a freely rotating drum roller, supported by bearings that enable axial movement. The 8 mm threaded shaft allows clamping at both ends after the conveyor belt is calibrated and aligned. Belt alignment is achieved using a pair of grooves in each profile where the roller fits, clamping nuts for necessary adjustments, and tensioners to pull the shaft outward. Figure 7 illustrates a representation of the idler pulley. The design and operation of the fly-cutting plant were validated by assessing its ability to execute a precise cutting path, characterized by uniformity and the absence of zigzagging patterns. To achieve this, it is crucial that the components are arranged correctly and that the motors or actuators operate with precision. Accordingly, a cutting system was designed consisting of a three-dimensional plane defined by the X, Y, and Z coordinates. The X- and Y-axes are driven by two motors, while an actuator or servo controls the movement along the Z-axis, executing the cutting path. Figure 8 provides an illustration of the cutting system. To develop the system depicted in Figure 8, it is essential to consider kinematic aspects within both the system and the designated conveyor belt area, as increasing the total area requires a proportional extension of the X- and Y-axes. This led to setting the conveyor belt’s operational area at 80% of its total capacity as the upper limit, ensuring scalability for the cutting system and its potential application in other areas requiring Cartesian movement, such as CNC machines or modular laser cutting systems. The linear motion of the cutting system is achieved using V-SLOT extruded aluminum profiles and high-precision bearings, commonly employed in the manufacturing of 3D printers, CNC machines, Cartesian robots, and similar devices. Finally, the Z-axis is actuated by a servomechanism adapted from those used in drawing machines, incorporating linear bearings and a base for fixing the cutting point. The design of the cutting system, created using SketchUp 3D modeling software, is illustrated in Figure 9. To develop the experimental framework, modifications were made to various operational parameters of the fly-cutting plant. The operational tests were conducted in the controlled environment of the Universidad del Quindío control laboratory, a humidity-free enclosure with an average temperature of 25 °C. Regarding the mechanical and operational configuration of the fly-cutting plant, the working area of 3000 cm² was reduced to 2200 cm² to avoid the need for a significant extension of the X- and Y-axis rails. The dimensions of the metal profiles and the configuration of various components provided a working area equivalent to 80% of the conveyor belt’s total area. For the operational tests of the conveyor belt motors and the cutting system, eight characterizations and input/output data collections were performed to gather consistent information about the behavior of these mechanisms and their respective technical specifications. The motion systems were tested at their maximum allowable input. Finally, the sensors and encoders used to measure motor speed, and the location of the cutting system were characterized based on the information provided by the manufacturers in the corresponding data sheets. The mechanical system of the proposed fly-cutting plant features finite movement along the axes, limited by the dimensions of the conveyor belt. Therefore, it is crucial to determine the operating limits of each component within the mechanical transmission system to validate them through experimental testing. The belt drive consists of the rollers shown in Figure 6 and Figure 7, along with a pulley system that connects one of the rollers to the motor driving the belt. Figure 10 illustrates the mechanical system used to move the conveyor belt. Theoretically, the maximum angular speed achievable by the output of the conveyor belt’s motor gearbox is 100 rpm, which is also the maximum speed of pulley P1. To determine the tangential speed of the rollers, we use the radius values of the pulleys and rollers shown in Table 2 and apply the equations of uniform circular motion. The following relations are used: w_1 = 100 rpm (1) Converting to radians per second, the angular speed of the pulley P1 is as follows: w_1 = 10.47 rad/s (2) The angular velocity is transmitted to pulley P2 linearly; therefore, the tangential speed v_1 at pulley P1 is equal to the tangential speed v_2 at pulley P2. vt_1 = vt_2 (3) We know vt = 2π * r/T (4) then vt = w * r (5) Rewriting Equation (3), we have w_1 * r_1 = w_2 * r_2 (6) Using Equation (6), we can know the angular speed at the pulley P2: w_2 = (w_1 * r_1)/r_2 = (10.47 * 0.7)/1.3 = 5.64 rad/s (7) As the pulley P2 is attached to the roller axis R1, both rotate at the same angular speed. w_2 = w_roll1 = 5.64 rad/s (8) Since both rollers have the same radius, their speeds are identical. Based on the angular speed of roller R1, the tangential speeds of both rollers, R1 and R2, can be determined, corresponding to the speed of the conveyor belt. Vt_roll1 = w_roll1 * r = 5.64 * 2.165 = 12.21 cm/s (9) After performing a theoretical analysis to determine the relationship between speeds in the mechanical system of the conveyor belt, experimental tests were conducted to validate the results. As shown in Figure 11, when maximum tension is applied to the motor, it achieves a speed of 93.39 rpm, corresponding to a linear speed of 11.40 cm/s on the conveyor belt. Similarly to the conveyor belt motor, a theoretical analysis was conducted for the X-axis motion of the cutting system. To prevent damage or movement beyond the conveyor belt’s length, limits were established at each end of the cutting system, as shown in Figure 9. After these adjustments, the cutting system’s movement along the X-axis was determined to be 62 cm. This is illustrated in Figure 12. The movement of the cutting system along the X-axis must match the speed of the conveyor belt. To achieve this, the pulley attached to the motor must have the same characteristics as the fixed pulley of the drive roller ( Figure 6). Another important aspect of the X-axis movement is the inclusion of a gearbox similar to that of the conveyor belt motor. This configuration allows for a theoretical maximum speed of 100 rpm. Therefore, the tangential speed of the X-axis for the cutting system can be expressed as follows: w_x = 100 rpm = 10.47 rad/s (10) Vt_x = 10.47 × 1.3 = 13.61 cm/s (11) Based on the tangential speed of the X-axis motor, as previously established in Equation (11), the X-axis cutting system can traverse the entire workpiece length in approximately 4.55 s, representing the maximum allowable time for the system to complete a single cutting operation. Figure 13 illustrates the operational characteristics of the motor used in the X-axis cutting system. The maximum speed attained was 88.20 rpm, equivalent to a tangential speed of 12.0 cm/s. In comparison, the time required to travel the distance between the two endpoints was determined to be 4.71 s. This value was calculated by subtracting the number of start and end samples from the predefined sample time of 0.1 s used for simulation purposes. For the angular velocity of the Y-axis cutting system, a maximum speed of 214 rpm was achieved using a square wave of 714 Hz. This result was obtained through experimentation with varying signal frequencies controlling the Y-axis motor driver. The displacement along the Y-axis of the cutting system is defined as 30.5 cm, corresponding to the width of the conveyor belt, and is ensured by two sensors that mark the beginning and end of the movement. The maximum frequency enabling this displacement was 500 Hz, with a duty cycle of 71%, a peak voltage of 4.78 V, and a root-mean-square (RMS) voltage of 3.89 V. For the Z-axis movement, a PWM signal with a frequency of 50 Hz was generated. The signal’s high-level duration was adjusted to vary the angle of rotation. Figure 14 illustrates the configurations used for the simulations and motor response tests on the Y- and Z-axes of the cutting system. The data illustrated in Figure 14b indicate that an angular displacement of 0° relative to the Z-axis servo motor positions the cutting blade on the workpiece. Additionally, it can be observed that an angular displacement of 50° is sufficient to return the blade to its initial position. The power circuits illustrated in Figure 15 were designed to facilitate easy connections to the two L298N drivers, which propel the geared motors controlling the conveyor belt and the X-axis of the cutting system. Additionally, a DRV8825 driver was incorporated to regulate the Y-axis stepper motor within the cutting system. Connection pins were added to enable direct linkage with a development PCB, as well as specific pins for the switching circuit. The power circuit design includes terminal blocks, Molex, USB, and RJ-45 connectors for interconnecting with other components of the cutting plant, such as the power supply, sensors, actuators, control circuits, and programming interfaces. The electronic circuits were designed with scalability in mind, allowing for rapid and intuitive connections between devices necessary for integration during implementation. The design of the electronic circuits highlights three primary groups: Mechanical System: Includes sensors (e.g., limit switches, encoders), DC motors, stepper motors, and servos. Power Board: Contains drivers and signal conditioning for managing sensors, actuators, and embedded control systems. Control Board: Facilitates user interaction with the fly-cutting plant, enabling different modes of operation, such as internal and external modes. Mechanical System: Includes sensors (e.g., limit switches, encoders), DC motors, stepper motors, and servos. Power Board: Contains drivers and signal conditioning for managing sensors, actuators, and embedded control systems. Control Board: Facilitates user interaction with the fly-cutting plant, enabling different modes of operation, such as internal and external modes. The circuit illustrated in Figure 15 (lower section) features a DIP switch that defines the motor’s operational steps. Capacitor C2 and resistor R21 collectively form an RC circuit, also known as a high-pass filter. This configuration allows the passage of frequencies exceeding the cutoff frequency, mitigating potential interference from lower frequencies. Optocoupler isolation can be employed for data transmission and reception between the control and power PCBs. However, due to the switching delays of the PC817 optocouplers, which range from 4 µs to 5 µs, a high-speed electronic circuit was designed using 6N137 optocouplers. These optocouplers, with a propagation delay of 48 ns to 50 ns, support transfer rates of up to 115,200 baud. The designed circuit is shown in Figure 16. The designed power circuit also incorporates the following features: The option to use either an internal or external power supply. A latching circuit that keeps the start LED illuminated. This is initiated upon pressing the start button and deactivated upon pressing the stop button. The ability to select either digital pins or the Enhanced Quadrature Encoder (EQEP) module, commonly integrated into embedded systems, for the encoder readout pins. Finally, Figure 17 shows the 3D design of the power circuit. The option to use either an internal or external power supply. A latching circuit that keeps the start LED illuminated. This is initiated upon pressing the start button and deactivated upon pressing the stop button. The ability to select either digital pins or the Enhanced Quadrature Encoder (EQEP) module, commonly integrated into embedded systems, for the encoder readout pins. Finally, Figure 17 shows the 3D design of the power circuit. To perform signal switching and enable control from the processing device, it is necessary to consider whether the signal is read or written, as this determines the use of multiplexers or demultiplexers. The latter are constructed with analog switches. The 74HC157 integrated circuit is used for multiplexing signals, while the 74HC4066 integrated circuit is employed for demultiplexing. The electronic configuration for multiplexing and demultiplexing signals is illustrated in Figure 18. A similar methodology is applied to all input and output signals used for commutation, including pulse-width modulation (PWM), gearmotors, steering, stepper motor control, servo duty cycle, encoder read pulses, and general-purpose input and output signals. Once the input and output signals for the commutation circuit are defined, its three-dimensional model is generated, as shown in Figure 19. The primary function of the control circuit is to serve as a conduit between the user interface and the power circuit. To achieve this, the circuit was equipped with three RJ-45 connectors to facilitate signal transmission for sensor and actuator management, serial communication, general-purpose ports, and other applications. An Arduino Nano was integrated into the design to enable information visualization and the transmission of corresponding values to the power circuits. The control circuit was configured to include a buzzer, jumpers for configuring pull-up or pull-down resistors, general-purpose ports, I2C communication pins for the LCD, and a power supply for additional connections. The design of the control circuit is illustrated in Figure 20. The integration of the designed plant’s functionalities, including mechanical elements and electrical circuits, requires implementing a programming strategy for each module and card. Additionally, it is essential for all of these components to collectively establish communication with the plant. A variety of software tools can be used to program such systems, and the choice depends on the programmer’s preferences and experience. In this case, several alternatives were considered, including Energia Nu designed in Austin, Texas, USA in 2012 by Robert Wessels as a Wiring/Arduino-based environment for Texas Instruments microcontrollers, Arduino that was developed in Ivrea, Italy in 2005 by a group of students and professors at the Interaction Design Institute Ivrea, and Code Composer Studio (CCS) developed in Dallas, Texas, USA in 1997 by Texas Instruments (TI). Energia is an open-source integrated development environment (IDE) based on the Wiring and Arduino framework. It enables the development of applications using high-level programming, as described in [ 33]. Another explored option was CCS, an IDE featuring a C/C++ compiler, source code editor, debugger, and other tools for managing workspaces efficiently, making it a viable choice for developing various applications. For this research, CCS was selected as the most suitable tool. If the designed plant is implemented in the future, CCS will allow the programmer to create microcontroller-based embedded systems for real-time applications, such as those used in Texas Instruments systems based on C2000 microcontrollers [ 34, 35]. Figure 21 shows the CSS workspace in its desktop version. A review of the CCS editor’s work environment shows that its programming structure is comparable to that of other development environments. Programming can be developed in the C language, as the default compiler used in CCS is ANSI C89. Since the objective of the designed plant was to integrate all constructed modules and devices, the programming was consolidated into a global project, resulting in the generation of numerous native files. These files contain the essential functions required for managing the sensors and actuators of the cutting plant, particularly for real-time control of the components. The files used for simulation development are presented in Appendix A. Figure 22 illustrates the defined programming structure for the proposed fly-cutting plant. Conversely, designing the controller for the fly-cutting plant requires an understanding of the plant’s behavior and dynamics. Given the experimental nature of the design, factors such as friction, uncertainty, and various dynamic components were integrated into the identification process rather than being considered separately. The resulting model for the proposed system is as follows: G(s) = 8368.1/(0.182 s + 1) (12) The plant model was paired with MATLAB’s PIDTuner to adjust the PID controller settings. The tuning process indicated that derivative action was unnecessary for the intended system, which is typical for this type of configuration. A key feature of the designed controller is its 0% overshoot and short settling time, both crucial for efficiently completing the trimming process. The parameters of the tuned controller are shown in Figure 23. The implemented control loop is shown in Figure 24. Since the PI controller is implemented on a microcontroller, the continuous model must be discretized. This requires determining a sampling time, which depends on the processing capacity of the digital device and the analysis of the open-loop and closed-loop poles. The following provides a brief overview of the method used to compute these poles and determine the plant’s sampling time: s(0.182s + 1) = 0,         s_1 = 0,    s_2 = −5.4945 (13) The feedback system is described by (8.6524 × 10 −5 s + 5.3054 × 10 −4)8368.1 + 0.182s 2 + s = 0 (14) The highest frequency of the plant, denoted as ω_(max), is determined by the pole with the greatest magnitude, which is 5.4945 in this case. Based on this value, the maximum sampling time can be calculated. f_m ≥ (10ω_max)/2π,       Tm ≤ 2π/(10ω_max) (16) For the task of reading the encoders and implementing the control strategy, a sampling time of T_m = 0.1 s was selected. This sampling interval was then used to determine the discrete-time PI controller constants. Various controller tuning methods can be applied in this scenario, such as the Ziegler–Nichols approaches [ 34, 35, 36]. In this study, the Ziegler–Nichols rules, as outlined in Table 3, were adopted due to their compatibility with the sampling time T_m. Using the PID controller equation from Figure 25 and the Ziegler–Nichols rules from Table 3, the resulting implemented PI equation is Gc(s) = u(s)/e(s) = k_p + k_i/s + k_d s (17) Gc(z) = k_p + (k_i Tm)/(1 − z^(−1)) + (k_d (1 − z^(−1)))/Tm,   with Tm = 0.1 s (18) Gc(z) = P(z) + I(z) + D(z) (19) with p(z) = P(z)e(z) = k_pe(z) (20) Finally, the PID controller expressed in difference equations is p[k] = k_p e[k] (23) Using Equations (23)–(25), we implemented the closed-loop control as shown in Figure 25. The fly-cutting plant was subsequently subjected to simulation and operational tests following the modeling and simulation of all circuits. The system responses are presented over a period of six seconds, during which the conveyor belt remains inactive, representing a duty cycle of 0%, and the cutting system is in its initial position. At 6.8 s, a duty cycle of 50% is applied to the conveyor belt, and 1.8 s elapses for the belt speed to stabilize at approximately 6330 rpm. At this point, a set point for the conveyor belt movement is established, causing the geared motor to transition from a resting state (red signal). Between 8 and 9.7 s, the cutting trace is generated as both speeds equalize. At 9.8 s, a downward peak is observed in the red signal, accompanied by an increase in revolutions to approximately 8344. This is attributed to a directional change, during which the X-axis geared motor pauses momentarily before returning to its initial position at maximum speed. The X-axis geared motor, now at its initial position, ceases movement after 11.9 s, reverses direction, and generates another peak in revolutions. This prevents the motor’s inertia from causing additional movement or contact with the left stop. Following the application of the brake to the X-axis motor, the system responds after 12.1 s, synchronizing the X-axis speed with the belt to produce a second stroke. The operation summary is shown in Figure 26. From the operation of the cutting plant in a dynamic state, it was determined that the system exhibited a response time of 3.28 milliseconds following the application of the signal. Regarding the displacement of pieces from one end to the other, the system showed an error of 4.83%. This discrepancy arose because the theoretical time for this displacement was 4.55 s, while the system required 4.77 s to complete the task. Additionally, certain displacement and cutting system parameters had to be recalculated due to differences between the theoretical maximum speed of the X-axis motor (100 rpm) and the actual achieved speed (88.2 rpm), resulting in an error of 11.8%. Due to these discrepancies in the response times of specific cutting plant elements, a compensation factor was incorporated into the controller to ensure precision and uniformity in the cuts. Without this compensation factor, the cuts exhibited a deviation of approximately 35°. This research represents a significant advancement in the development of industrial plant prototypes within an academic framework, providing an invaluable resource for engineers training in control and automation. The primary methodological innovation lies in the design and simulation of a cost-effective, small-scale cutting plant that replicates continuous cutting processes found in industry. This approach enables students to understand and manage extensive processes within a laboratory environment, offering practical experience comparable to industrial settings without the high costs associated with commercial equipment. From an engineering perspective, this study integrates key concepts from control theory, mechanical engineering, and physical principles to construct a prototype that facilitates education and hands-on experimentation with real-time control systems. The validation of the design through MATLAB simulations, along with the use of tools such as Code Composer Studio for developing real-time controllers, underscores the plant’s effectiveness as both an educational and research model, adaptable to various contexts. Furthermore, this research is pivotal in bridging the gap between theoretical knowledge and practical application in engineering education. The developed prototype allows students to engage with authentic industrial processes, enriching their understanding of complex system dynamics and fostering the development of innovative and efficient industrial solutions using emerging technologies like 3D printing and augmented reality. These attributes make this prototype a valuable asset in training future engineers, equipping them to meet the challenges of industrial automation and control. Conceptualization, D.F.R.-J. and C.A.T.V.; methodology, D.F.R.-J. and C.A.T.V.; software, D.F.R.-J. and C.A.T.V.; validation, D.F.R.-J. and C.A.T.V.; formal analysis, D.F.R.-J. and C.A.T.V.; investigation, D.F.R.-J. and C.A.T.V.; resources, D.F.R.-J. and C.A.T.V.; data curation, D.F.R.-J. and C.A.T.V.; writing—original draft preparation, D.F.R.-J. and C.A.T.V.; writing—review and editing, D.F.R.-J. and C.A.T.V.; visualization, D.F.R.-J. and C.A.T.V.; supervision D.F.R.-J. and C.A.T.V.; project administration, D.F.R.-J. and C.A.T.V.; funding acquisition, D.F.R.-J. and C.A.T.V. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Data is contained within the article. The authors declare no conflicts of interest. The files required to perform the simulations can be downloaded from https://drive.google.com/file/d/1WNoosUDp7Nm2SyEC7THFFODBir-vfcfP/view?usp=drive_link (accessed on 8 December 2024). Source: The authors. Source: The authors. Source: The authors. Adapted from [34,36]. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. Abstract Test plants or laboratory prototypes are essential for developing training activities in engineering. In the field of automation and control, simulators or high-fidelity equipment models commonly used in industrial processes are necessary. These tools allow engineering trainees to gain experience working with devices similar to those they will encounter in their professional contexts. This paper presents the design and simulation of a fly-cutting plant for academic use. A 3D model was developed in SketchUp, incorporating features typical of industrial plants. The system’s simulation was carried out in MATLAB R2023b using mathematical modeling. The primary contribution of this work is the design of a low-cost, compact industrial prototype that includes a conveyor belt and a continuous cutting mechanism, enabling the understanding and operation of large-scale industrial processes. Performance tests were conducted using MATLAB, Simulink, and Code Composer Studio. Subsequently, operational and cutting tests were performed using classical control techniques. Additionally, the design features of the fly-cutting plant, which can be easily implemented for process control training activities, are detailed. Keywords: three-dimensional (3D) modeling; academic environments; digital control; flying shear; industrial prototype; real-time control; fly-cutting plant