Effect of postural angle on back muscle activities in aging female workers performing computer tasks.

[Purpose] This study investigated the effects of postural angle on back muscle activity during a computer task in aging women. [Subjects] Seventeen women ≥50 years old participated. [Methods] The participants were instructed to perform computer-related tasks for 20 minutes on a workstation that simulated typical office working conditions. Back posture was measured from the measured trunk and pelvic angles. Electromyography activities were recorded simultaneously from the cervical erector spinae, longissimus, and multifidus muscles. [Results] The lowest mean percentages of maximum voluntary contraction for the cervical erector spinae and longissimus muscles were obtained when the upper trunk and pelvic angles were between 0° to -5° from the sagittal plane. The back muscle activities increased as the upper trunk and pelvic angles exceeded 0°. Statistical analysis showed significant correlations between upper trunk angle and cervical erector spinae and longissimus muscle activities. Similarly, pelvic angle was significantly correlated with cervical erector spinae and multifidus muscle activities. [Conclusion] A neutral back posture minimizes muscle activities in aging women performing computer tasks.

Muscle activity, time to fatigue, and maximum task duration at different levels of production standard time.

[Purpose] This study investigated the variations in muscle fatigue, time to fatigue, and maximum task duration at different levels of production standard time. [Methods] Twenty subjects performed repetitive tasks at three different levels of production standard time corresponding to "normal", "hard" and "very hard". Surface electromyography was used to measure the muscle activity. [Results] The results showed that muscle activity was significantly affected by the production standard time level. Muscle activity increased twice in percentage as the production standard time shifted from hard to very hard (6.9% vs. 12.9%). The muscle activity increased over time, indicating muscle fatigue. The muscle fatigue rate increased for the harder production standard time (Hard: 0.105; Very hard: 0.115), which indicated the associated higher risk of work-related musculoskeletal disorders. Muscle fatigue was also found to occur earlier for hard and very hard production standard times. [Conclusion] It is recommended that the maximum task duration should not exceed 5.6, 2.9, and 2.2 hours for normal, hard, and very hard production standard times, respectively, in order to maintain work performance and minimize the risk of work-related musculoskeletal disorders.

The effects of energy expenditure rate on work productivity performance at different levels of production standard time.

[Purpose] The purpose of this study was to investigate the effects of energy expenditure rate on work productivity performance at different levels of production standard time. [Subjects and Methods] Twenty industrial workers performed repetitive tasks at three different levels of production standard time, normal, hard, and very hard. Work productivity and energy expenditure rate were recorded during the experimental tasks. [Results] The work productivity target was not attainable for the hard and very hard production standard times. This was attributed to the energy expenditure rate, which increased as the level of production standard time became harder. The percentage change in energy expenditure rate for the very hard level (32.5%) relative to the normal level was twice that of the hard level (15.5%), indicating a higher risk of work-related musculoskeletal disorders for the harder production standard time. The energy expenditure rate for the very hard production standard time (1.36 kcal/min) was found to exceed the maximum energy expenditure rate recommended for light repetitive tasks involving both arms (1.2 kcal/min). [Conclusion] The present study shows that working with an energy expenditure rate that is either equal to or above the maximum energy expenditure rate of the tasks results in decreased work productivity performance due to the onset of physical fatigue and a higher risks of work-related musculoskeletal disorders.

Fuzzy mixed assembly line sequencing and scheduling optimization model using multiobjective dynamic fuzzy GA.

A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.

The relation between upper limb muscle and brain activity in two precision levels of repetitive light tasks.

A study was conducted to investigate the effects of repetitive light tasks of low and high precision on upper limb muscles and brain activities. Surface electromyography (EMG) and electroencephalography (EEG) were used to measure the muscle and brain activity of 10 subjects. The results show that the root-mean-square (RMS) and mean power frquency (MPF) of the muscle activity and the mean power of the EEG alpha bands were higher on the high-precision task than on the low-precision one. There was also a high and significant correlation between upper limb muscle and brain activity during the tasks. The longer the time and the more precise the task, the more the subjects become fatigued both physically and mentally. Thus, these results could be potentially useful in managing fatigue, especially fatique related to muscle and mental workload.

The effect of job and environmental factors on job satisfaction in automotive industries.

A methodology was developed for diagnosing industrial work, which includes questionnaire, observation, measurements, data collection and statistical analysis. A survey was conducted to investigate the relationship between job satisfaction and factors that affect work design in 2 automotives manufacturing companies in Malaysia. A basic work design model was proposed. The aim of this model was to determine the factors that influence employees' perception towards their work. A set of multiple-choice questionnaires was developed and data was collected by interviewing employees at a production plant. The survey focused on job and environmental factors. The results supported the proposed model and showed that job and environmental factors were significantly related to job satisfaction. They highlighted the significant influence of age, work experience and marital status on job satisfaction. Further, environmental factors, especially the surroundings, context dependence and the building's function, also had a significant impact on job satisfaction.

Development of statistical models for predicting muscle and mental activities during repetitive precision tasks.

This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students' and workers' data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.

An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness.

The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts' uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

Virtual reality based support system for layout planning and programming of an industrial robotic work cell.

Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.

The effect of job organizational factors on job satisfaction in two automotive industries in Malaysia.

A methodology is developed in diagnosing the effect of job organizational factors on job satisfaction in two automotive industries in Malaysia. One hundred and seventy male subjects of age 18-40 years with the mean age of 26.8 and standard deviation (SD) of 5.3 years and the mean work experience of 6.5 years and SD of 4.9 years took part in the study. Five job organizational factors were tested in the study including job rotation, work method, training, problem solving and goal setting. A job organization questionnaire was designed and was based on respondents' perception in relation to job satisfaction. The results showed that job organization factors were significantly related to job satisfaction. Job rotation, work method, training and goal setting showed strong correlation with job satisfaction while problem solving had intermediate correlation in the first automotive industry. On the other hand, most job organization factors showed intermediate correlation with job satisfaction in the second automotive industry except the training factor which had low correlation with job satisfaction. These results highlight that job rotation, work methods, problem solving and goal setting are outstanding factors in the study of job satisfaction for automotive industries.