The classical psychophysical approach to setting limits in manual lifting tasks is discussed in view of experimental procedures used, non-linearity of human perception of load heaviness, and the related experimental outcomes. The results of two studies investigating the human assessment of load acceptability and safety are presented. The first study compares the classical concept of the maximum acceptable weight of lift (MAWL) to the alternative concept of the maximum safe weight of lift (MSWL). The second study utilizes the linguistic magnitude estimation (LME) method to mathematically model human assessment of four categories of lifted loads, including the concepts of acceptable, safe, not-too-heavy, and too-heavy loads for continuous lifting. It is shown that the concepts of the lifted load acceptability and safety are non-linear, and can be modelled with great accuracy using the third degree polynomials. This study also introduces and investigates the concept of the load indifference in assessment of load heaviness, and shows that lack of a cognitive benchmark introduces inconsistency in subjects' perception of load acceptability and safety compared to the concept of too-heavy load for continuous lifting. It is concluded that a new research approach to manual lifting tasks based on cognitive engineering is needed to improve the quality of research methodologies currently utilized in this field. This unexplored area of research should lead to greater understanding of human capacities and limitations in manual lifting tasks in the context of cultural and linguistic anthropology.

This study examined the roles of the coping strategies used by individuals to cope with job stress. The coping strategy was formed throughout the cognitive appraisal of the stressful events. It was found that direct action coping strategy shows negative relations with job stressors, whereas there are positive relations between stressors and other coping strategies. This implies that direct action coping strategy is used to alleviate the job stress by affirmatively changing the deleterious effects of job stressors in the work environment, while other coping strategies led to the positive impact on job stress or negative impact on job performance. To secure the usability and applicability of the model in practice, more considerations in the future should be made on the mediating variables such as personality type and social support, which are possible variables impacting the selection of coping strategy.

The main objective of this study was to develop a hybrid neuro-fuzzy system for estimating the magnitude of EMG responses of 10 trunk muscles based on two lifting task variables (trunk velocity and trunk moment) as model inputs. The input and output variables were represented using the fuzzy membership functions. The initial fuzzy rules were generated by the neural network using true EMG data. Two different laboratory-derived EMG data sets were used for model development and validation, respectively. The mean absolute error (MAE) between the actual and model-estimated normalized EMG values was calculated. Across all muscles, the average value of MAE was 8.43% (SD=2.87%) of the normalized EMG data. The larger absolute errors occurred in the left side of the trunk, which exhibited higher levels of muscular activity. Overall, the developed model was capable of estimating the normalized EMG values with average value of the mean absolute differences of 6.4%. It was hypothesized that model performance could be improved by increasing the number of inputs, including additional task variables as well as the subjects' characteristics.

Manufacturing of electronic circuits for microwave communication boards often requires tuning of different circuit characteristics by manual adjustment of several trimmer components, including the trimmer's resistance and capacitance. This manual tuning process was automated by applying the artificial neural network modeling approach. In the considered tuning process, which required manual adjustment of a set of trimmers, multiple specification criteria had to be satisfied by several trimmer rotations. The tuning process was described in terms of three independent steps: the circuit output measurement, trimmer selection, and trimmer rotation. The trimmer selection was performed by a semi-supervised neural network, which learned the patterns of circuit characteristics and the deviations between the ideal and practical outputs. Another network was developed for determination of trimmer rotation rate. The results, based on computer simulation of the tuning process, showed that the developed system improved performance of the tuning process, allowing for automation of the microwave circuit board tuning task in a real manufacturing environment.

Many companies have endeavored to build a quality cost management system in order to be more productive business organization. This study shows the detail procedures of constructing a quality cost management system which is believed to be appropriate for their business system. That is, the method to calculate the quality cost and the linking logic between the quality improvement and its financial impact are explained based on a particular industry case. In this sense, the changes of business performance measures such as market share, customer satisfaction, etc. were analyzed in the longitudinal perspective for the consecutive 4 years (2003~2006). As the quantitative results of this study, the improvement activities based on the quality cost management system resulted in the 32% reduction of quality cost and the 121% increase of business profit, compared 2005 with 2006. In the qualitative perspective, the successive practice of quality cost reduction and the job information sharing in business unit were obtained by providing the best practices and bench-marking cases. Finally, the customer satisfaction has increased so that the customer-friendly management system has been accomplished. With these efforts, the 3.4% increase of the market share and the 3% increase of the customer satisfaction were obtained in 2005. As the future study, the current study can be extended to the concept of COPQ (cost of poor quality) which focuses on the hidden quality cost of the whole business activities. Such extension of analysis will help us understand the wider role of a quality cost management system in the business.