**4.1 Introduction**

Noise is one of the physical environmental factors affecting our health in today's world. Noise is generally defined as the unpleasant sounds, which disturb the human being physically and physiologically and cause environmental pollution by destroying environmental properties. The general effect of noise on the hearing of workers has been a topic of debate among scientists for a number of years. Regulations limiting noise exposure

Kumar (2008) [28] Studied the case of high level of noise in rice mills and to examine the response of the workers towards noise. They was done a noise survey was conducted in eight renowned rice mills of the north-eastern region of India. They were following the guidelines of CCOHS for noise survey. Their model as same like above author model. But

Based on the literature surveyed as presented in the previous section, it was observed that noise as a pollutant produces contaminated environment, which affects adversely the health of a person and produces ill effects on living, as well as on non-living things. The prominent adverse effects of noise pollution on human beings include noise-induced hearing loss, work efficiency, annoyance responses, interference with communication, the effects on sleep, and social behavior. The effects on work efficiency may have serious implications for industrial workers and other occupations. The effects of noise on human performance have also been investigated by researchers based on sex, laterality, age and extrovert introvert characteristics. However, these factors do not affect human performance significantly. Therefore, depending on the nature of the task, human performance gets affected differently

After the literature review, we are now much better able to understand why the benefits of low noise level at workplace, taking into account the nature of cognitive task performed, are also important. A part from the health and well-being advantages for the workers themselves, low noise level also leads to better work performance (speed), fewer errors and rejects, better safety, fewer accidents, and lower absenteeism. The overall effect of all this is better productivity. For an industrial environment (moderately type of cognitive task), total productivity increase as a result of reducing noise level, the indirect correlation between worker's age and the increase in production, improvement in attitude, the availability of workers, and working efficiency. There have been several studies to demonstrate the effect of either ages or noise on the performance of various tasks of industrial relevance. It was shown that increasing cognitive work difficulty was predisposed to increased reduction in cognitive work efficiency in industries. But second site we have already discussed that,

In the present study an attempt has been made to develop a neural fuzzy expert system to predict human cognitive task efficiency as a function of noise level, age of the worker and cognitive task type. We have observed that cognitive task type affects the efficiency of worker in various level of noise in industries. The model is implemented on Fuzzy Logic

Noise is one of the physical environmental factors affecting our health in today's world. Noise is generally defined as the unpleasant sounds, which disturb the human being physically and physiologically and cause environmental pollution by destroying environmental properties. The general effect of noise on the hearing of workers has been a topic of debate among scientists for a number of years. Regulations limiting noise exposure

under the impact of different levels of noise and cognitive task type.

when level of noise increase then this reduces the efficiency of the worker.

they was taking the size of grid is 1m X 1m.

**3. Problem statement** 

Toolbox @ MATLAB 2007.

**4. Methodology 4.1 Introduction** 

of industrial workers have been instituted in many places. For example, in the U.S., the Occupational Noise Exposure Regulation states that industrial employers must limit noise exposure of their employees to 85 dB (A) for 8 hr period.

Based on the literature surveyed as presented in previous section, it was observed that a great majority of people working in industry are exposed to noise with different cognitive task type. In this study, attempt has been made to find out the combined effects of noise level and cognitive task type on industrial worker's performance. Attempt has also been made in present study to identify the noisy industries located in Delhi and around Delhi. Different industries with or without noise were categorized based on measured sound pressure level.

Sound pressure level for industries clearly shown in Appendix-A. In this context, measurement the sound pressure level and cognitive task type, questionnaire studies have been conducted at automobile, power plant and steel textile industries in and around Delhi and also noise counters has been drawn for noisy industries. Assuming that the working environment (Temperature, Humidity, illumination level, other facilities), are same in the industries under reference; categorization has been made as presented in the Table 4.1(a) and 4.1(b).



Table 4.1. (a) Industries name & their category with reference to noise level.

Table 4.1. (b) Industries name with reference to workers age groups.

In addition to this, the questionnaire data was segregated based on various sections of above-mentioned industries. Performance rating was obtained based on questionnaire survey for different noise levels and type of cognitive task (simple, moderate, and complex). On the collected performance rating data, we have implemented our model using Sugeno technique (Fuzzy Logic Tool box) of MATLAB. It is a three input-one output system. The input variables are noise level, Age of the worker or operator, and cognitive task type and the reduction in cognitive task efficiency is taken as the output variable. The whole methodology shown in Figure 4.1

Some Studies on Noise and Its Effects on Industrial/Cognitive Task Performance and Modeling 183

A 330 MW Pragati power station is located in New Delhi, latitude (28°37 ׳ -28°38 ׳ ( at longitude (77°14 ׳ -77°15 ׳ ( near (Income Tax Office) ITO beside the highway at 0.3 Km from World Health Organization (WHO) building as shown in Figure 4.2. A centrifugal pumps WPIL India Limited, located in Ghaziabad, latitude (28°40 ׳57 (at longitude (77°25׳41 (as

Fig. 4.2. Geographical location of I.T.O power plant (New Delhi).

Fig. 4.3. Geographical location of centrifugal pumps WPIL India Limited (Ghaziabad).

Fig. 4.4. Geographical location of Shriram Piston & Rings Ltd (Ghaziabad).

**4.2.1 Description of study area** 

shown in Figure 4.3.

#### **4.2 Material and methods**

In the present study industrial noise measurement technique carried out at three different industries (ITO power plant station, centrifugal pump industry WPIL India Limited, and Shriram Piston & Rings Limited). Selection of industry was based on requirement of study i.e., worker working under different noise levels as well as cognitive task type (simple, moderate, and complex). Questionnaire established with a group of questions refer to parameters will be effected by the noise levels as well as type of cognitive task. Questionnaire asked questions about the age, skill discretion, psychological job demands, etc. Likert scale is used to evaluate the answers density from strongly disagree to strongly agree. Operators and supervisor fulfils the questionnaire on the working day after 8 hrs continuous working, Questionnaire form contains 55 questions. Only workers doing cognitive task were taken in this study. To check the reliability of the survey, the cronbach's alpha value was calculated. Similar sets of items of the questionnaire were identified and cronbach's alpha was calculated [2]. If the value is more than 0.7, then the survey was considered to be reliable. Present model include three inputs and one output, first input is noise level measured by sound level meter, second and third inputs were age and cognitive task type, assessed by questionnaire, and one output was reduction on cognitive task efficiency assessed by using the questionnaire also.

Fig. 4.1. Flow diagram for methodology
