Applied Mechanics and Materials Vol. 471

Abstract: Ergonomically designed workstation is vital towards improving health and safety of operators. This study was carried out at the assembly department to assess female operators effectiveness at standing workstations during assembling different components and parts for making electronic product in a manufacturing factory. Long working hours with static standing postures can lead to musculoskeletal disorders. The study main objectives are to assess, identify risks and body parts complaints with respect to standing workstation. The methodology use in this study includes anthropometric data measurements of female operators, standing risk assessment and body parts symptoms survey. One hundred female operators working at standing workstations took part in the study. This study revealed three major types of musculoskeletal disorders (MSDs) observed in this factory, they are pain at the shoulder region, pain at the leg region and pain at the upper back region. Based on the findings from this study, the authors have proposed a standing workstation designs that overcome the MSDs.

Abstract: Fatigue can be defined as a feeling of drowsiness or sleepiness, tiredness, boredom, or an inability to focus and a mental sluggishness. The aim of the present study is to discover the general perceptions on fatigue risk factor of teenage motorcycle riders in an urban city in Klang Valley, Malaysia. Respondents provided feedback through questionnaires that were developed based on the Motorcycling Fatigue Model and other practices in existing empirical studies. In addition, the questionnaire highlights 18 statements that cover two main components, namely, vehicle or environment factors and rider factors. All the 60 respondents in this study habitually ride various types of motorcycles as their main transportation from and to their homes and offices. Findings indicate that poor road design is the primary contributor to fatigue, whereas driving early in the morning was the least contributor. Although the sample is quite small, the results of this study coincide with those of previous literature.

Abstract: In this study, displacement and strain energy mode shapes obtained from the structure, are processed using continuous spatial wavelet transforms for damage identification. A cantilever and simply supported beam are analysed in ANSYS to obtain mode shapes by performing modal analysis both for damaged and undamaged conditions. Different wavelets are processed to choose the best mother wavelet for detecting crack, a representation of damage. The dimensions of crack like depth are varied from 0.5 mm. Spatial distribution of wavelet coefficients obtained is used for identifying the damage. The quantification of the damage is done by using Lipchitz constant. It is observed that by using strain energy mode shapes the percentage of damage (crack) identification level can be improved than by using displacement mode shapes. The minimum damage level that the strain mode shape can identify is approximately 3% of the element thickness, whereas with displacement mode shapes, it is about 7% of the element thickness. Different types of crack configurations like single surface crack, double surface cracks and internal cracks are simulated and studied using both the modal methods. It is observed that the strain energy mode method could identify internal cracks also.

Abstract: Various condition monitoring techniques were applied during a laboratory engine test in order to understand the wear processes occurring and to determine a suitable method which could be applicable to the detection and diagnosis of abnormal engine condition in practice. The goal of the research presented in this study is to monitor the internal combustion engine block. The proposed engine block approach is based on measuring and monitoring the engine operation in variable speed and torque using Piezoelectric Sensor. However, it normally requires analyzing the obtained signal for providing valuable information. This research involves two main procedures including data collecting as well as data analyzing. Data collecting is processes of sensor attach, run the engine and record the data while data analyzing is translating the data using data acquisition and filtering by fast furrier transform and analyzing by I-kaz and MZN methods.

Abstract: This paper presents the convenient wavelet family for the fatigue strain signal analysis based on the wavelet coefficients. This study involves the Morlet and Daubechies wavelet coefficients using both the Continuous and Discrete Wavelet Transforms, respectively. The signals were collected from a front lower suspension arm of a passenger car by placing strain gauges at the highest stress locations. The car was driven over public road surfaces, i. e. pavé, highway and UKM roads. In conclusion, the Daubechies wavelet was the convenient wavelet family for the analysis. It was because the wavelet gave the higher wavelet coefficient values indicating that the resemblance between the wavelet and the signals was stronger, closer and more similar.

Abstract: Cutting force is an important signal in machining process and has been widely used for tool condition monitoring. Monitoring the condition of the cutting tool in the machining process is very important to maintain the machined surface quality and consequently reduce inspection costs and increase productivity. This paper utilizes I-kaz-based analysis of cutting force signal to monitor the status of tool wear. The cutting force signals are measured by two channels of strain gauge that were mounted on the surface of tool holder. Experiments were carried out by turning hardened carbon steel and cutting force signals were analyzed using I-kaz^TM technique by integrating two component of signals (I-kaz 2D, Z₂), I-kaz of cutting force (Z of F_y), and I-kaz of feed force (Z of F_x). The results show that I-kaz of feed force can be effectively used to monitor tool wear progression during turning operation.

Abstract: The Hearing Impaired People (HIP) cannot distinguish the sound from a moving vehicle approaching from their behind. Since, it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in outdoor. If HIPs can successfully get sound information through some machine interface, dangerous situation will be avoided. Generally the profoundly deaf people do not use any hearing aid which does not provide any benefit. This paper presents, simple statistical features are used to classify the vehicle type and its distance based on sound signature recorded from the moving vehicles. An experimental protocol is designed to record the vehicle sound under different environment conditions and also at different speed of vehicles. Basic statistical features such as the standard deviation, Skewness, Kurtosis and frame energy have been used to extract the features. Probabilistic neural network (PNN) models are developed to classify the vehicle type and its distance. The effectiveness of the network is validated through stimulation.

Abstract: This paper presents durability analysis using a new statistical-based method, called the Fatigue Integrated Kurtosis-based Algorithm for Z-notch filter (Fatigue I-kaz) technique. This method provides a three dimensional graphical representation of the data distribution of the signal at three different frequency range in order to measure the degree of data scattering. For validation, three road surfaces were used for data collection purposes. An experiment has been performed on the motorcycle frame. In this study, the strain signals were collected based on three different road surfaces. The strain gauges were fixed on the motorcycle frame to measure the variable strain amplitude loadings imposed. The strain signals were then analysed using Fatigue I-kaz coefficient. Residential road surfaces give a higher Fatigue I-kaz coefficient, _f than campus and off road surfaces which is 0.0120 which is 0.0079 and 0.0067

Abstract: The main subject of this study was to establish a meaningful significance of the acoustic emission technology to be incorporated in the pedicle screw fixation procedure. Its purpose was to find a replacement technique using the acoustic emission technology instead of keep using the conventional way which only depends on the surgeons expertise. The experiment of pedicle screw fixation method work was carried out on a goats vertebrae as a lab scale material instead of the human cervical vertebrae. While the experimental work was done, the acoustic emission signatures were then acquired using the Physical Acoustics acoustic emission data acquisition system. Once completed, the acoustic emission signatures were then analysed using Matlab software together with the AEWin software package. From the results obtained, the numbers of data counts are generally bigger for the pedicle screw fixation procedure at early stage of bone penetration compared to the latter. It is significant to the different structure of bones as hard bone technically takes more time to be penetrated compared to the soft ones. This technique undoubtedly has high potential to be studied further so that it can be commercialized into the medical field.

Abstract: The performance of a fuel injector greatly influences the performance of a vehicle engine. An effective monitoring system is capable of detecting damage, instability, and even the life of fuel injector. In this study, a test rig on fuel injector using piezoelectric film sensor has been developed. Three parameters, namely, pulse width at 5, 10, and 15 ms; frequency at 17, 20, and 25 Hz; and pressure at 10, 50, and 70 bar were used for observation. These parameters were set at different combinations to obtain the different injection patterns of the fuel injector. Statistical methods were used to analyze the data, with the aid of the Matlab software. The injection pattern was described using a new I-kaz (Ƶ) statistical parameter, which is intended to provide a simple explanation of the corresponding correlations between the coefficient of I-kaz and the statistical parameters, such as root mean square, Skewness, and Kurtosis, to obtain effective information on the operation state of the fuel injector. The results showed that higher pulse width results in a higher I-kaz coefficient, which also increases with an increase in frequency and varies with pressure; however, the pattern depends on the pulse width. The I-kaz scatter graph against skewness showed a clear pattern among the statistical parameters. The corresponding correlation was useful for monitoring the fuel injector and can be used as a reference for future studies.