**1. Introduction**

170 Fuzzy Inference System – Theory and Applications

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Present industrial environment is quite different than past. Globalization and market driven forces has made the working environment quite competitive. It is quite obvious that these factors when combined with environmental factors, lead to poor operators/workers performance. Therefore, ergonomists has new challenges in terms of predicting workers efficiency as well as workers health protection and well being.

High noise level exposure leads to psychological as well physiological problems. It results in deteriorated cognitive task efficiency, although the exact nature of work performance is still unknown. To predict cognitive task efficiency deterioration, neuro-fuzzy tools were used. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems. Among them, adaptive neuro-fuzzy inference system provides a systematic and directed approach for model building and gives the best possible design parameters in minimum possible time.

Input variables were noise level, cognitive task type, and age of workers. Out-put variable was predicted in terms of reduction in cognitive task efficiency. The cause-effect relationships of these parameters are complex, uncertain, and non-linear in nature therefore, it is quite difficult to properly examine it by conventional methods. Hence, an attempt is made in present study to develop a neuro-fuzzy model to predict the effects of noise pollution on human work efficiency as a function of noise level, cognitive task type, and age of the workers practicing cognitive type of task at (I.T.O power plant station, centrifugal pump industry WPIL India Limited, and Shriram Piston & Rings limited) industries. Categorization of noise and its levels (high, medium, and low) was based on a survey conducted for this purpose.

A total of 155 questionnaires were distributed among the workers of industries under reference. Likert scale has been used to evaluate the answers densities which ranges between "strongly disagree" to "strongly agree". Cognitive workers performance was evaluated based on self administrated questionnaire survey, which consisted of 55-questions, covering all possible reported effects of cognitive task on cognitive task performance.

Some Studies on Noise and Its Effects on Industrial/Cognitive Task Performance and Modeling 173

and stress outcomes. Work compatibility is defined as a latent variable integrating the positive and negative impact characteristics of work variables in the human-at-work system in the form of a prescribed relationship. The theoretical basis of work compatibility is described at length in terms of concepts and models. In addition, approximate reasoning solutions for the compatibility variables are presented in terms of three models, namely, linear, ratio, and expert. A test case of 55 service workers in a hospital setting has been used to validate work compatibility with respect to severe musculoskeletal and high stress outcomes. The results have demonstrated that the expert compatibility model provided the stronger and more significant associations with work outcomes in comparison to the linear and ratio compatibility models. In conclusion, although the work compatibility validation is limited by both the cross-sectional design and sample size, the promising findings of this exploratory investigation suggest that further studies are warranted to investigate work compatibility as a diagnostic tool to

Genaidy, et al. (2007) [4] Although researchers traditionally examined the 'risk' characteristics of work settings in health studies, few work models, such as the 'demandcontrol' and 'motivation-hygiene theory', advocated the study of the positive and the negative aspects of work for the ultimate improvement of work performance. The objectives of the current study were: (a) to examine the positive and negative characteristics of work in the machining department in a small manufacturing plant in the Midwest USA, and, (b) to report the prevalence of musculoskeletal and stress outcomes. A focus group consisting of worker experts from the different job categories in the machining department confirmed the management's concerns. Accordingly, 56 male and female workers, employed in three shifts, were surveyed on the demand/energizer profiles of work characteristics and self-reported musculoskeletal/stress symptoms. On average, one-fourth to one-third of the workers reported 'high' demand, and over 50% of the workers documented 'low' energizers for certain work domains/sub-domains, such as 'physical task content'/'organizational' work domains and 'upper body postural loading'/'time organization' work sub-domains. The prevalence of workers who reported 'high' musculoskeletal/stress disorder cases, was in the range of 25-35% and was consistent with the results of 'high' demands and 'low' energizers. The results of this case study confirm the importance of adopting a comprehensive view for work improvement and sustainable growth opportunities. It is paramount to consider the negative and positive aspects of work characteristics to ensure optimum organizational performance. The Work Compatibility Improvement Framework, proposed in the reported research, is an important endeavor toward the ultimate improvement and sustainable

John, et al. (2009) [5]The main objective of this study was to test the research question that human performance in manufacturing environments depends on the cognitive demands of the operator and the perceived quality of work life attributes. The second research question was that this relationship is related to the operator's specific task and time exposure. Two manufacturing companies, with a combined population of seventy-four multi-skilled, crosstrained workers who fabricated and assembled mechanical and electrical equipment, participated in an eight month, four-wave pseudo panel study. Structural equation modeling and invariance analysis techniques were conducted on the data collected during cognitive task analysis and the administration of questionnaires. Human performance was

evaluate musculoskeletal and stress outcomes in the workplace.

growth of human and organizational performance.

The model was implemented on neural Fuzzy Logic Toolbox of MATLAB using Sugeno technique. The modeling technique was based on the concept of neural Fuzzy Logic, which offers a convenient means of representing the relationship between the inputs and outputs of a system in the form of IF-THEN rules. Model has been built under The Recommended Exposure Limit (REL) for workers engaged in occupation such as engineering controls, administrative controls, and/or work practices is 90 dB(A) for 8 hr duration OSHA. In order to validate the model 20% data sets were used for testing purpose.
