A training model of an automated storage and retrieval system (AS/RS) with customized warehouse management system (WMS)

AS/RS is a key industrial automation system that has drastically reduced the workforce needed to run a warehouse. Via a computer-controlled system, many intensive labour jobs are taken over by the system, including tediously moving and sorting heavy load from the minute of receving until shipping to customers, intensive paperwork to record goods receiving and order receipts. Somehow, in real business, the system is always complex in the perspective of engineering considerations, depending on the nature of the business, tending to upgrading and modification from time to time. It is desirable that the engineering training curve would provide an engineer perspective in industry design concepts and contemporary teclmologies to the students, not in the operator prospective. This project is intended to develop a training model of AS/RS for the engineering students. The learning curves are provided through three levels in the system integration. The device level illustrates basic input and output devices that are carefully choosen. The controller level processes all input information from the input devices and host computer. The supervisory level implements graphic user interface for system monitoring and control for the operator. The training model also emphasizes in three design concepts, flexibility, expand ability and modularity. Flexibility will allow a broad spectrum of application environments and extend application life. Expandability will allow application in areas not yet defined. Modularity will enhance modification and maintenance

A mechatronic system for achieving optimum alignment of lower limb prosthesis

Misalignment in the lower limb prosthesis can cause great discomfort in the stumpsocket interface and disturbance to gait function. In the long run, it could deteriorate the musculoskeletal system. In practice, the assessment still depends heavily on the verbal feedback of an amputee and experiences of a prosthetist. Moreover it is inconsistent amongst the prosthetists. Prosthetic alignment involves the adjustment of the prosthetic components relative to the gait quality. Some methods were proposed, including symmetry index, variation in a step-to-step transition, stability within the zone of integrated balance, matching roll-over shape (ROS) to an ideal ROS and etc. It is not clear if the optimum alignment could be achieved. These methods exhibit a few limitations, i.e. limited use of gait variables in a single comparison and non-uniform results when different gait variables are applied. There is a need to provide an objective assessment method that processes high dimensional gait variables and presents them in a simple form. In addition, it could be impractical and expensive clinically to spend excessive time on a patient. An ambulatory gait measurement system could achieve this objective to a certain extent. This research investigates a potential engineering solution that is able to provide an assistive and objective assessment of the lower limb prosthetic alignment that provides optimal gait quality. The effort includes a development of a low-cost ambulatory gait measurement system which could be reliably used during indoor and outdoor trials. Human walking trials using the designed ambulatory system are designed and performed to justify the proposed solution. A novel gait analysis method using Principle Component Analysis and Self-Organizing Feature Map is proposed to process high dimensional gait data into a simple plot and a decision guide. The proposed methodology could help to collect sufficient gait data during indoor and outdoor gaits and could provide an objective gait assessment during the application of lower limb prosthetic alignments

Development of a twin-head infusion pump for micromixing

Mixing is a crucial process in most of the industrial technology such as the operation of chemicals and fermentation reactors, combustion engines, polymer blends, and pharmaceutical formulations [1]. For handling a smaller volume of liquid, micromixing is a suitable method that can be applied. Micromixing (micromixer) is one of the microfluidic functions for mixing and blending liquids as precursors for biological process such as cell activation, enzyme reaction, and drug delivery system [2, 3]. There are several advantages of applying microfluidic device (micromixer) in the chemical technological processes such as processing accuracy, efficiency, minimum usage of reagents and ease of disposing of devices and fluids [3]. Basically, micromixers are categorised into passive and active micromixers. Passive micromixer consists of no moving parts and free from additional friction. It does not use external forces, fully dependent on molecular diffusion and chaotic advection for mixing process [4]. In contrast to active micromixers, external forces are applicable to active micromixers by implementing moving elements either within the microchannels, a time-variant, or a pressure field [5]. To create the pressure field differences for moving the liquid within the micromixer, an infusion pump is usually applied

Oncoming Vehicle Detection with Variable-Focus Liquid Lens

Computer vision plays an important role in autonomous vehicle, robotics and manufacturing fields. Depth perception in computer vision requires stereo vision, or fuse together a single camera with other depth sensors such as radar and Lidar. Depth from focus using adjustable lens has not been applied in autonomous vehicle. The goal of this paper is to investigate the application of depth from focus for oncoming vehicle detection. Liquid lens is used to adjust optical power while acquiring images with the camera. The distance of the oncoming vehicle can be estimated by measuring the oncoming vehicle’s sharpness in the images with known lens settings. The results show the system detecting oncoming vehicle at ±2 meter and ±4 meter using depth from focus technique. Estimation of oncoming vehicles above 4 meter can be done by analysing the relative size of the vehicle detected

Neuro Model for Passive Suspension of a Light Car

The system model is neccessery to be determined in control systems engineering which is generally represented in mathematical form. The mathematical model can be utilized for analysing the system's characteristics or designing the controller parameters of the system. Here, a neuro model for passive suspension system of a light car is proposed. The candidate structure of the neuro model is contructed from non-linear system of passive suspension of a quarter car mathematical model. Weights estimation of neuro model is conducted by applying iterative weighted least square algorithm. Actual input output data of a test car for training process are acquired by driving the test vehicle on an artificial surface of road. An artificial surface of road is a kind of real road surface imitation. Experimental findings show that the proposed model is able to imitate sucessfully the dynamic properties of the passive suspension system of the light  car. The model response shows similar trend and has smallest error

Vision Based Human Decoy System for Spot Cooling

This project aims to reduce the energy consumption of air conditioner usage while maintaining occupant comfort. Cooling down the unoccupied space can be considered as waste of energy. Therefore, a human decoy system is proposed to track any human in the detection area. Image contains depth data in each pixel which can be used to detect the presence of target subject as well as their position. The acquired position data is processed by using MATLAB and subsequently is transmitted to Arduino Mega using serial communication to control stepper motors. The experimental results show that the air conditioner airflow is successfully can be directed to the target human subject with average response of 0.860 seconds per movement within detection area

Removal of nutrients and heavy metals from domestic and industry using botryococcus sp.

Microphytes or microalgae are the most basic food source of many types of organisms on earth and blooms during the presence of dissolved inorganic phosphorus. Wastewater is a body of water that is dangerous to organic life forms when consumed or used. It contains many pollutants that can cause health problems and also affect the ecosystem of an environment. This study aims to improve the water quality of wastewaters using phycoremediation process. The objectives of this study are to determine the growth of Botryococcus sp. in different types of wastewater in terms of resistance and survival of Botryococcus sp. in phycoremediation performance, to measure the environmental factor effecting the growth of Botryococcus sp. of phycoremediation process, to optimize the physiochemical and heavy metal removal in different types of wastewaters and to evaluate the effectiveness of Botryococcus sp. to remove the pollutants in wastewaters. Phycoremediation or bioremediation process is using macroalgae or microalgae for removing pollutants, nutrients, xenobiotics and heavy metals from wastewater. This research was done by collecting microalgae sample, isolating and culturing the required Botryococcus sp. Growth optimization and followed by phycoremediation process is done to remove unwanted elements from wastewaters. The optimum growth rate of algae is achieved when salinity is at 0M, temperature at 330C, photoperiod at 12:12 and light intensity of 18000 Lux. Result shows that the highest nitrate removal percentage occurs in semiconductor (100%), followed by palm oil mill effluent (97.29%), textile wastewater (98.04%) and domestic wastewater (85.43%). Total Phosphorus removal indicates the highest percentage for domestic wastewater (100%), palm oil effluent (99.2%), textile wastewater (98.44%) and semiconductor (50.39%). From this research, it is found that the best overall removal of physiochemical and heavy metal content occurs in palm oil mill effluent followed by domestic wastewater, semiconductor wastewater and textile wastewater

Development of a Malaysian Sign Language interpreter using image recognition for the community to understand the deaf

In Malaysia, Person with Disabilities (PWD) with hearing problems or commonly known as the deaf, struggle to have a conversation with the communities who do not know or how to do sign language efficiently. The consequence is hearing PWD received unequal treatment in jobs and learning opportunities. This project aims to develop a Malaysian Sign Language interpreter to convert hand signs to texts, in order to facilitate the conversation between hearing PWD and the communities. The system would implement a camera and vision system to capture images of hand signs. Four hand signs have been selected. Stacks of these images were processed digitally using deep learning method, and eventually the trained network could recognize the hand signs successfully. This feasible study suggests that the proposed setup could be further implemented to train more hand signs and enrich the hand signs-to-text vocabulary

Development of a Wireless and Ambulatory Posture Monitoring System

The wireless and ambulatory posture monitoring system monitors the movement and posture change of the human body with respect to the g-line. It is crucial to monitor the posture health of the ophthalmologist who spends a prolonged period on the static sitting posture while operating on the slit lamp which leads to any painful experience. The motivation of the proposed system is to improve the ergonomics of the ophthalmologist on their working environment and reduce any occupational potential hazard which may prompt Work-Related Musculoskeletal Disorders (WMSDs). The proposed system also induced a wireless system by using XBee wireless units to reduce the use of the wire that may tangle on the study subject which causes any uncomfortable experience to the study subject during the human trial. Inertial Measurement Unit (IMU) sensor which consists of an Accelerometer, a Gyroscope and a Magnetometer is used to measure the angle of deviation of the body segment with respect to the g-line. The data is tabulated and presented into the graphical method to identify and extract the properties of the graph on each different static sitting posture which later are used for posture recognition

In Vitro Growth of Human Keratinocytes and Oral Cancer Cells into Microtissues: An Aerosol-Based Microencapsulation Technique

Cells encapsulation is a micro-technology widely applied in cell and tissue research, tissue transplantation, and regenerative medicine. In this paper, we proposed a growth of microtissue model for the human keratinocytes (HaCaT) cell line and an oral squamous cell carcinoma (OSCC) cell line (ORL-48) based on a simple aerosol microencapsulation technique. At an extrusion rate of 20 �L/min and air flow rate of 0.3 L/min programmed in the aerosol system, HaCaT and ORL-48 cells in alginate microcapsules were encapsulated in microcapsules with a diameter ranging from 200 to 300 �m. Both cell lines were successfully grown into microtissues in the microcapsules of alginate within 16 days of culture. The microtissues were characterized by using a live/dead cell viability assay, field emission-scanning electron microscopy (FE-SEM), fluorescence staining, and cell re-plating experiments. The microtissues of both cell types were viable after being extracted from the alginate membrane using alginate lyase. However, the microtissues of HaCaT and ORL-48 demonstrated differences in both nucleus size and morphology. The microtissues with re-associated cells in spheroids are potentially useful as a cell model for pharmacological studies