Oluwaseun Kayode Ajayi

A desirable property in metal applications for medical, aerospace, and automobile applications is low weight, impact strength, wear resistance, and high strength. Titanium (Ti) and aluminum (Al) are lightweight, only titanium possesses some of these properties. However, to achieve improved properties, Ti-Al binary alloys are used as base metals, but with synthetic and natural reinforcements. In this study, zirconium oxide (ZrO2) and rice husk ash (RHA) in different proportions were combined with aluminum alloy (Al6061), proportions of titanium and aluminum powder to form novel metal matrix composites. Four sets of samples of varying weight fractions of Ti, Al, with each having six (6) samples with varying fractions of RHA and ZrO2, making a total of twenty-four (24) samples, were fabricated through the stir casting process. Tensile tests were carried out on each sample to determine its mechanical properties. The weight fraction by per cent of Al6061 was 85% for all the samples. From the tensile test, Ti increases the strength of the sample more than Al powder. For both tensile and ductile properties, RHA has a better impact on the modulus of elasticity than increased ZrO2 _reaching as high as 152 MPa. However, it can be proven that Ti powder, Al powder, RHA, and ZrO2 all improved the mechanical properties of Al6061.

In real-world applications, time delays and uncertain nonlinearities are inevitable and impose significant challenges in modern control systems. The uncertainties commonly include nonlinear backlash-like hysteresis, external disturbances, parameter perturbation (internal disturbance), measurement noise (white noise), and varying time-delay components. Recently, time-delay estimation (TDE) techniques have gained widespread traction for compensating for nonlinearities in various time-delay control systems. This study evaluates the performance of weighted TDE-based proportional-integral-derivative (PID) control on a complex, high-order system comprising a third-order system with a repeated pole structure. The concerned system can be regarded as analogous to a conveyor belt or a real-world thermal system. Experimental analyses are conducted to validate the effectiveness of integrating the TDE mechanism and the PID controller, with their respective weighting coefficients, during controller operation for a high-order time-delay nonlinear system under the effects of hysteresis, white noise, system parameter perturbation, external output disturbance, and varying time-delay scenarios. The simulation results, compared with the traditional PID controller, demonstrate that the proposed weighted TDE-PID control method outperforms in terms of improved transient performance characteristics, resilience, and robustness, with negligible steady-state errors. Moreover, stability and sensitivity analyses for the selection of the weighted coefficients are performed for the weighted TDE-PID-controlled high-order time-delay system, thereby further substantiating the validity of the proposed weighted control law. Hence, the results corroborate the applicability of this improved TDE-PID control method for high-order time-delay nonlinear processes encountered in realistic industrial settings.

Traditional subtractive technology is rapidly losing significance with the advent of digital manufacturing technologies, which offer affordable machining with high accuracy and repeatability. Computer numeric controlled (CNC) machining has been around for a while; however, it has been costly to own one. Since the concept of CNC machining is now broadly understood and open-source software is available for control, designers can make use of available local materials to develop cheaper CNC machines. Hence, this presents the evaluation of the design and development of a one-square-meter CNC milling machine. The control was implemented on Arduino Uno, while open-source Universal G-code Sender (UGS) and G-code reference block library (GRBL) were used for the G-code generation and machine control, respectively. The built CNC was calibrated and tested on wood and plastic materials, and the resulting products were acceptable in accuracy up to ±0.02 mm in the first trial, but attained perfect accuracy by the third trial. Multiple tests repeatedly showed that accuracy was maintained. Since the machine is reconfigurable, future work entails automation and incorporating laser cutting capabilities into the machine.

SS 316L, a low-carbon 316 Stainless Steel, has been used to manufacture swivel mechanisms for paraplegic patients, but its weight is relatively high compared to a few materials in its range of properties. Aluminum alloy 6061 and Titanium alloy (Ti6Al4V) offer lightweight and incredible strength-to-weight ratio, hence their use for medical, aerospace, and automotive applications. This study, therefore, seeks a replacement for SS 316L. A 3D model of a swivel mechanism was developed to compare the performance of the swivel mechanism made with SS 316L, AA 6061, and Ti6Al4V. The kinematic analysis of the mechanism based on a range of weights: 1kN, 1.1 kN, 1.2 kN, 1.3 kN, 1.4 kN, and 1.5 kN was carried out to generate the inputs for the simulation. The 3D model was made with SolidWorks, and the results of the kinematic analysis were used to define the simulation parameters for the mechanism. Two scenarios generated depicted the full collapse of the mechanism and the full extension. The results showed that AA 6061 and Ti6Al4V outperformed SS 316L with higher yield strength and factor of safety. Therefore, swivel plates made with AA 6061 and Ti6Al4V have higher yield strength than those made with SS 316L, adding to the advantage that they have a higher strength-to-weight ratio. From this analysis and known knowledge of the cost of these materials, the optimal replacement considering cost with yield strength is AA 6061. However, Ti6Al4V is a better alternative for the strength-to-weight ratio for SS 316L.

Additive Manufacturing (AM) plays a vital role in rapid prototyping. Polylactic acid (PLA), a biomass thermoplastic monomer made from corn starch is the most used filament material in AM. Due to the strength requirement of haptic device prototypes, there is a need to carefully explore all parameters that could enhance the performance of printed parts. This study considered three printing parameters: printing speed, infill density, and layer thickness on three levels each. A tensile test according to ASTM D638 was performed on each. Statistical analysis was done to investigate the influence of each of the parameters on maximum tensile stress, load at maximum tensile stress, and Modulus respectively for each sample. Subsequently, a regression analysis was performed. The sample with an Infill density of 15%, printing speed of 70mm/s, and 0.1mm layer thickness exhibited the highest tensile strength. However, it was discovered further that the infill density has the highest influence on the mechanical properties of the 3D printed PLA material in tensile testing. The chart of the mechanical properties and the parameter configurations were also presented to assist in selecting printing parameters for desired mechanical properties.

This work demonstrates the fruit sorting improvement system architecture using the Faster-RCNN algorithm to identify fruits of varying size, colour selection, and segregation. The requirement is for a fruit sorting mechanism with accurate and precise detection with accurate placement capabilities. For this purpose, a 5 DOF robotic arm was built in the laboratory. For the control, an algorithm was developed using Denavit-Hartenberg (D-H) kinematic analysis model. The Image processing was implemented in OpenCV by adopting the Faster-RCNN image processing using NumPy and panda packages. Color clustering was employed to improve fruit detection, and segmentation techniques were used to focus more on the fruit image. The algorithm used was based on baseline architecture within relevant architecture, and with the results that are derived, it shows a great improvement from typical fruit detection systems using non-deep learning techniques, especially for position identification and the edge-to-edge estimation of the fruits. However, it was discovered that the time to detection was the same for all colours and weights, while the sorting duration varies with weight.

The conventional method of mechanism control which requires physical contact is being replaced with remote control, especially with the advent of the Internet of things (IoT). Facial recognition is used to identify and authenticate faces from images or videos. It has many applications, including granting or restricting access to a facility, or secured areas, or preventing unauthorized users, including selective access. The accuracy of such a recognition and control system is very important and depends on how the system was modeled and adopted. In this study, facial images and gesture images were collated and modeled in a python neural network, then optimized using TensorFlow. The algorithm was compiled unto a raspberry pi for testing on a developed automatic gate. An effective method of achieving accuracy using the epoch is presented in this work. Five (0, 5, 10, 15, 20) batch number and epoch respectively were modeled to achieve accuracy for the system. The model was trained with five gestures; fist, palm, thumb up, thumb, and last finger. The gesture recognition accuracy achieved through the epoch was maximum at 99.97 when both batch number and epoch were set to 20. However, when no epoch was set, the accuracy was below 10.2, whereas there was no accuracy below 98% when the epoch was introduced. This depicts the importance of epoch in achieving accuracy in image recognition. It was also discovered that the higher the epoch and the batch number the greater the accuracy, but the processing would require a very high processing unit.

Occupant safety is one of the critical performance criteria established in the aerospace industry. Several composite materials have been developed but the energy absorption properties are not yet satisfactory. This study investigates the energy absorption characteristics of aluminum tubes reinforced with coir-fiber/epoxy system at varying proportions (10-90%) according to the specifications of hybrid tube thickness compositions (10T, 15T, 20T) towards evolving a criterion for optimal performance. Finite element analysis was conducted in ABAQUS to determine the load–displacement response and the crashworthiness properties of the tubes while a representative volume element (RVE) model was formulated to obtain the elastic properties of the reinforcement phase. The results indicated that the incidence of high peak forces P_max is related to tube thickness variations where the 20T tubes were found to give the best performance, while the 15T tubes showed a superior performance under progressive crushing and presented the best responses for specific energy absorption (SEA). A multi-objective optimization plan was implemented and through the Pareto fronts, tube configurations (C20T60F), (C15T70F) and (C20T40F) were found to be most consistent with the design criteria. Results from experimental validation were found to be in close agreement with numerical predictions and satisfied the overall objective of achieving a good balance in lightweight design for crashworthiness applications.