Variability reduction in stencil printing of solder paste for surface mount technology

Competition in stencil printing to produce excellence in the finished product is intense. Faults in the printing process are a major source of board failure. Studies have shown that over 63% of defects identified after reDow originated from the solder paste printing ( A. Lotfi ,1998 ) . However. understanding these failures are a challenging problem as the printing process has a large number of non linearly dependent variables such as factors relating to paste (formulation. viscosity), the environment (temperature, humidity) and machine parameter (alignment, pressure and speed of squeegee, blade hardness etc). The process engineer is challenged to widen the process window so that future modifications to the process, such as the addition of a new component, can be achieved with little. if any, change in materials or process parameters. This thesis reports the effect of temperature and humidity variation from the manufacturing environment on the solder paste consistency and optimization of the essential parameters of squeegee pressure, squeegee speed. separation speed and print gap. The outcome of variation in temperature and humidity to the solder paste viscosity were analyzed and tests were done to determine the characteristic of the solder paste. The tests results indicate that the temperature and humidity has an impact on the solder paste printability. thus some attempts must be taken to control these variables. For parameter optimization. the analysis was carried out using statistical optimization. The main aim was to combine these parameters with three main pitch categories to produce the acceptable print formation. The results showed that. the ideal print result requires optimum statistical combinations of four parameters essentially related to a particular pitch. It is also shown that there is a diversity and contrasts of the combination of the parameters for each category of pitch. Detailed explanations as to the phenomenon are outlined in the thesis

3-D kinematic comparison of treadmill and overground running.

Studies investigating the mechanics of human movement are often conducted using the treadmill. The treadmill is an attractive device for the analysis of human locomotion. Studies comparing overground and treadmill running have analyzed discrete variables, however differences in excursion from footstrike to peak angle and range of motion during stance have yet to be examined. This study aimed to examine the 3-D kinematics of the lower extremities during overground and treadmill locomotion to determine the extent to which the two modalities differ. Twelve participants ran at 4.0m/s in both treadmill and overground conditions. 3-D angular kinematic parameters during the stance phase were collected using an eight camera motion analysis system. Hip, knee and ankle joint kinematics were quantified in the sagittal, coronal and transverse planes, then compared using paired t-tests. Of the parameters analyzed hip flexion at footstrike 12° hip range of motion 17°, peak hip flexion 12.7°, hip transverse plane range of motion 8° peak knee flexion 5° and peak ankle excursion range 6.6°, coronal plane ankle angle at toe-off 6.5° and peak ankle eversion 6.3° were found to be significantly different. These results lead to the conclusion that the mechanics of treadmill locomotion cannot be generalized to overground

Push recovery with stepping strategy based on time-projection control

In this paper, we present a simple control framework for on-line push recovery with dynamic stepping properties. Due to relatively heavy legs in our robot, we need to take swing dynamics into account and thus use a linear model called 3LP which is composed of three pendulums to simulate swing and torso dynamics. Based on 3LP equations, we formulate discrete LQR controllers and use a particular time-projection method to adjust the next footstep location on-line during the motion continuously. This adjustment, which is found based on both pelvis and swing foot tracking errors, naturally takes the swing dynamics into account. Suggested adjustments are added to the Cartesian 3LP gaits and converted to joint-space trajectories through inverse kinematics. Fixed and adaptive foot lift strategies also ensure enough ground clearance in perturbed walking conditions. The proposed structure is robust, yet uses very simple state estimation and basic position tracking. We rely on the physical series elastic actuators to absorb impacts while introducing simple laws to compensate their tracking bias. Extensive experiments demonstrate the functionality of different control blocks and prove the effectiveness of time-projection in extreme push recovery scenarios. We also show self-produced and emergent walking gaits when the robot is subject to continuous dragging forces. These gaits feature dynamic walking robustness due to relatively soft springs in the ankles and avoiding any Zero Moment Point (ZMP) control in our proposed architecture.Comment: 20 pages journal pape

Estimation of ground reaction forces and moments during gait using only inertial motion capture

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory

Sensor-Based Adaptive Control and Optimization of Lower-Limb Prosthesis.

Recent developments in prosthetics have enabled the development of powered prosthetic ankles (PPA). The advent of such technologies drastically improved impaired gait by increasing balance and reducing metabolic energy consumption by providing net positive power. However, control challenges limit performance and feasibility of today’s devices. With addition of sensors and motors, PPA systems should continuously make control decisions and adapt the system by manipulating control parameters of the prostheses. There are multiple challenges in optimization and control of PPAs. A prominent challenge is the objective setup of the system and calibration parameters to fit each subject. Another is whether it is possible to detect changes in intention and terrain before prosthetic use and how the system should react and adapt to it. In the first part of this study, a model for energy expenditure was proposed using electromyogram (EMG) signals from the residual lower-limbs PPA users. The proposed model was optimized to minimize energy expenditure. Optimization was performed using a modified Nelder-Mead approach with a Latin Hypercube sampling. Results of the proposed method were compared to expert values and it was shown to be a feasible alternative for tuning in a shorter time. In the second part of the study, the control challenges regarding lack of adaptivity for PPAs was investigated. The current PPA system used is enhanced with impedance-controlled parameters that allow the system to provide different assistance. However, current systems are set to a fixed value and fail to acknowledge various terrain and intentions throughout the day. In this study, a pseudo-real-time adaptive control system was proposed to predict the changes in the gait and provide a smoother gait. The proposed control system used physiological, kinetic, and kinematic data and fused them to predict the change. The prediction was done using machine learning-based methods. Results of the study showed an accuracy of up to 89.7 percent for prediction of change for four different cases

Production of biodiesel from palm oil

The present researches study the alternative fuel to replace the diesel fuel and how to produce the alternative fuel. Diesel fuel which is made from fossil fuel due the anaerobic decomposition through million years cause many harmful effect to the environment and human health such as the greenhouse effect, air pollution, acidification and more. The aim of the study is to produce the biodiesel from vegetable oil which is palm oil. It starts with mixing the 50 ml of ethanol and 0.5 g of sodium hydroxide as catalyst. The dissolved catalyst then will be poured into the heated 250 ml of palm oil and be stirred for 30 minutes. After the content is mixed the transesterification method is carried out. The content then transferred to separating funnel for separating process. At the end, two layers which the bottom layer will be by- product and the upper layer will be biodiesel. The biodiesel will enter purification method which rinse it with hot distilled water and ready to be test which are the density, kinematic viscosity and heating value of the biodiesel. By using biodiesel as an alternative fuel, the environment and human health will be secure more and it may attract people to more concern about the benefits of the biodiesel

Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System

This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications

An adaptive hybrid control architecture for an active transfemoral prosthesis

The daily usage of a prosthesis for people with an amputation consists of phases of intermittentand continuous walking patterns. Based on this observation, this paper introduces a novel hybrid architectureto control a transfemoral prosthesis, where separate algorithms are used depending on these two differenttypes of movement. For intermittent walking, an interpolation-based algorithm generates control signals forthe ankle and knee joints, whereas, for continuous walking, the control signals are generated utilizing anadaptive frequency oscillator. A switching strategy that allows for smooth transitioning from one controllerto another is also presented in the design of the architecture. The individual algorithms for the generation ofthe joints angles’ references, along with the switching strategy were experimentally validated on a pilottest with a healthy subject wearing an able-bodied adapter and a designed transfemoral prosthesis. Theresults demonstrate the capability of the individual algorithms to generate the required control signals whileundergoing smooth transitions when required. Through the use of a combination of interpolation and adaptivefrequency oscillator-based methods, the controller also demonstrates its response adaptation capability tovarious walking speeds

An adaptive hybrid control architecture for an active transfemoral prosthesis

The daily usage of a prosthesis for people with an amputation consists of phases of intermittent and continuous walking patterns. Based on this observation, this paper introduces a novel hybrid architecture to control a transfemoral prosthesis, where separate algorithms are used depending on these two different types of movement. For intermittent walking, an interpolation-based algorithm generates control signals for the ankle and knee joints, whereas, for continuous walking, the control signals are generated utilizing an adaptive frequency oscillator. A switching strategy that allows for smooth transitioning from one controller to another is also presented in the design of the architecture. The individual algorithms for the generation of the joints angles’ references, along with the switching strategy were experimentally validated on a pilot test with a healthy subject wearing an able-bodied adapter and a designed transfemoral prosthesis. The results demonstrate the capability of the individual algorithms to generate the required control signals while undergoing smooth transitions when required. Through the use of a combination of interpolation and adaptive frequency oscillator-based methods, the controller also demonstrates its response adaptation capability to various walking speeds