Status and noise reduction analysis of robotics lab in an academic institute by using acoustic materials

Abstract

In recent decades, noise has emerged as one of the most annoying and tiring factors in working environments, be it in factory, workshop, academic or research setup. This paper presents the noise status and noise reduction analysis of Robotics lab in an academic institute. The average equivalent continuous noise level ( $L_{A e q}$ ) inside the Robotics lab (64.90–75.99 dB) was within or close to permissible limits of 75 dB as per Indian standards for industrial environment; but the operation of Mig and Spot welding were a source of noise nuisance to the adjoining academic area due to the sound transmission from the Robotics lab. The noise reduction analysis in the study demonstrated the usage of acoustics (glass, curtain, cardboard and thermocol) in windows as sound barriers that dampens the transmission of indoor noise. The Sound Transmission Loss (STL) was observed to be highest in the range of 18.12–22.62 dB (28.88–29.59%) by using the combination of glass and curtain as acoustic barrier in windows of the Robotics lab; thereby, reducing noise nuisance significantly in the academic area. The study revealed the necessity of effective acoustic barrier in labs/workshops under-industrial conditions in academic institutes and proposed a model for predicting STL for the combination of glass and curtain from $L_{A e q}$ value.

Keywords

Robotics lab welding noise acoustic barrier sound transmission loss

Introduction

In recent decades, noise pollution has emerged as one of the most significant environmental problems due to rapid urbanization and fast expansion of industrial operations.^1–3 Industrial noise is one of the most annoying and tiring factors in working environments, be it in factory, workshop, academic or research setup.^4–9 Studies have revealed that noise of factories/workshops account for about 80% noise pollutants.¹⁰ It has detrimental physiological and psychological effects on a person’s health and, in extreme cases, may lead to hearing impairment.^11–18 Investigations have indicated students being exposed to noise in educational institutes, particularly engineering and technology institutes where workshops/laboratories operate under-industrial set up.^{5–7,9,19–22} Exposure to high noise levels from workshops/laboratories cause disturbances in teaching-learning process, such as classroom discussion, task performance, problem-serving and mental stress.^{14,20,23–26}

Therefore, it is crucial to utilize efficient acoustic (sound insulation) or sound absorption materials in workshops/laboratories in educational institutes for noise mitigation. Although the terms ‘sound insulation’ and ‘sound absorption’ are frequently used interchangeably in everyday speech but they are fundamentally distinct. Sound absorbing materials are intended to enhance sound quality, minimize echo and annoying reverberation inside a place but don’t dampen the noise; whereas, sound insulation serve as an acoustic barrier to the sound source by preventing sound waves from entering or leaving a place.^27,28 Researchers have studied the sound transmission loss (STL) or insertion loss (IL) in different types of enclosures using variety of materials. Ming & Pan,²⁹ observed that insertion loss in different type of enclosures (aluminium and fibrous glass covered with rockwool layers) varied with different range of frequencies. Asdrubali³⁰ reported that airborne sound insulation of natural material is similar to the glass. Ayub et al.³¹ reported best results with double-layer panels when the inner perforated plate has lower porosity material (coir fiber) and was backed with an air gap. Tao et al.³² studied the combination of multiple perforated plates, air gap and coir fiber for enhancing sound absorption quality and reported that the absorption coefficient of panel was governed by the porosity of the perforated plates. Gao et al.³³ reviewed active and passive metamaterials (artificial composite materials) for noise reduction and concluded that metamaterials can reduce very low frequency noise that may not be possible by conventional acoustic materials.

Now a day, industrial robots or mechanized equipment have been widely used for high-volume productivity to yield the best cost per unit performance in comparison to manual and hard automation.³⁴ Welding is an integral part of advanced manufacturing and robotics welding has become the symbol of modern industrial welding technology that has now become indispensable because manual welding yields low production rates due to harsh work environment and extreme demands.³⁵ Despite the benefits of using robotics systems, the welding process (tig, mig and spot welding) are a source of noise, particularly in the academic environment where the prevention of sound waves (noise) leaving a place (workshop/laboratory) becomes important consideration to safeguard the teaching-learning process in the surrounding academic area. In view of this, noise study of the Robotics lab/workshop was carried out with the following objectives –

⁃ noise assessment status – indoor (working environment under-industrial conditions) and outdoor (noise assessment in academic area due to transmission of sound from Robotics lab/workshop);

⁃ noise reduction analysis by using different types of acoustic materials for windows of Robotics lab/workshop; and

⁃ develop a model or mathematical relationship between sound transmission loss by acoustic material(s) and noise level.

Further, suggestions and recommendations have been made based on the outcome of the present study.

Materials and methods

Study area

The study was carried out for Robotics lab located in Siemen Centre of Excellence in the academic area of National Institute of Technology Kurukshetra, Haryana (India). The lab is being used by students and faculty for academic, research and consultancy purposes. There are three machines in Robotics lab, namely Model KR10 R1420, KR10 R1420 and KR210 R2700 for Tig, Mig and Spot welding respectively. The Hall consisting of (18.5 m × 11.6 m × 3.2 m) and the top of hall is covered with the false ceiling and the floor is covered with the epoxy coating which prevent the floor from degradation from the vibration caused by the machinery. The operating areas of the machines are on one side of the hall near the windows. All the windows (2.6 m × 1.32 m) adjacent to the operating areas are single glazed with 3 mm thick glass. The image of the Robotics lab and the layout plan with the noise measurement points/locations are presented in Figure 1. The welding machines are being operated individually, i.e., one at a time. Indoor measurements were thus made for noise produced by Tig, Mig and Spot welding machines in the space designated for operational activity at locations I1, I2a & I2b, and I3 respectively under-industrial conditions. Outdoor noise measurements were made near the windows at locations O1, O2 and O3 during the operation of Tig, Mig and Spot welding respectively. The locations were selected such that the noise reduction by various acoustic materials can be analyzed. For noise reduction analysis, the following acoustic materials have been used for windows – glass (3 mm thick), curtain (1 mm thick) made up of polyester, cardboard (5 mm thick), thermocol (15 mm thick) and a combination of curtain and glass (1 & 3 mm thick respectively).

Figure 1.

Photograph and layout plan of Robotics Lab with noise monitoring locations.

Noise measurement

Noise measurements were made during January-February 2023 with the class-1 digital sound level meter (SLM) Casella CEL-620B1 using ‘A’ frequency weighting network and fast response mode. The SLM was held at 1.3 to 1.5 m above the ground, and 3.0 to 3.5 m away from reflective surfaces, and with the microphone directed to the noise source.³⁶ Calibration of the SLM was performed at 114 dB (A), both before and after the day’s measurements using Casella CEL-120/1 class-1 acoustic calibrator.

Noise measurements were taken at all the seven locations (as shown in Figure 1) for 3 min’ duration per run so that machines get stabilize on a constant vibrations and variation of noise can be accurately monitored. Further, a set of three measurements was taken at each station so that chances of error will not be there.¹⁹

The following noise indices were used for noise measurement and/or assessment of results:

$L_{A e q}$ : Equivalent continuous noise level with A-weighted frequency, expressed in decibels (dB).

$L_{\max}$ : Maximum A-weighted frequency noise level with a fast response (125 millisecond), expressed in decibels (dB).

$L_{\min}$ : Minimum A-weighted frequency noise level with a fast response (125 millisecond), expressed in decibels (dB).

$L_{p e a k}$ : Highest instantaneous noise level with A-weighted frequency and no time weighting, expressed in decibels (dB).

$S T L$ : Sound Transmission Loss, expressed in decibels (dB).

The average $L_{A e q}$ values, for a set of three measurement at each location, were computed as logarithmic average of the relevant values by using the following formula:¹⁹

L_{A e q} = 10 \log_{10} [\frac{1}{n} \sum_{i = 1}^{n} 10^{\frac{L i}{10}}]

(1)

where,

n

= Number of readings; and

L i

= Noise Level.

Sound Transmission Loss (STL), or Insertion Loss (IL), is used to express the efficiency of the acoustic material and is calculated from equivalent continuous noise level by the following expression:³⁷

S T L (d B) = {S P L}_{R e f} (d B) - {S P L}_{t r} (d B)

(2)

where,

{S P L}_{R e f}

= Noise without use of acoustic, and

{S P L}_{t r}

= Sound after transmission.

The data was statistically analyzed and compared with permissible levels/standards for day time (06:00 a.m. to 10:00 p.m.) as recommended by by-law for environmental noise limits in India,¹⁸ as shown in (Table 1).

Table 1.

Indian ambient air quality standards in respect of noise.

Area	Category of area/zone	Permissible limits in $L_{A e q}$ dB
Area	Category of area/zone	Day time (06:00 a.m. to 10:00 p.m.)	Night time (10:00 p.m. to 06:00 a.m.)
(A)	Industrial area	75	70
(B)	Commercial area	65	55
(C)	Residential area	55	45
(D)	Silence zone	50	40

Note: (1) Silence zone is an area comprising not less than 100 m around hospitals, educational institutions, courts, religious places or any other area which is declared as such by the competent authority.

(2) Mixed categories of areas may be declared as one of the four above mentioned categories by the competent authority.

The Robotics lab has been considered under Category: Industrial Area for indoor locations (I1, I2a, I2b and I3), and the Academic Area of the Institute has been considered under Category: Silence Zone for outdoor locations (O1, O2 and O3) in the present study in accordance with the above Indian noise standards.

Analysis approach

The analysis of collected data was carried out in accordance with the scheme covering –

⁃ preparatory work, that includes determining the number of noise measurement points and their locations, starting the machine and defining its parameters,

⁃ diagnostic evaluation, that includes noise measurements, computation and analysis of study results,

⁃ drawing inferences, that includes comparison and evaluation of results as compared to the permissible levels as per Indian noise standards for industrial and silence area/zone during day time (Table 1),

⁃ development of mathematical model for predicting STL from acoustic material(s), and

⁃ conclusion and suggestions, along with recommendations for future research.

Results and discussion

The noise indices at the four designated indoor locations I1, I2a & I2b, and I3, and at the three outdoor locations O1, O2 and O3 with the existing acoustics (i.e. closed glass windows) are tabulated in Table 2.

Table 2.

Indoor and outdoor noise indices with existing acoustics.

Monitoring location		Indoor				Outdoor
Location code		I1	I2a	I2b	I3	O1	O2	O3
Welding operation		Tig	Mig		Spot	Tig	Mig	Spot
Noise indices (dB)	$L_{A e q}$	64.90	75.99	75.57	67.18	47.27	60.53	51.78
	$L_{A m a x}$	75.06	85.77	83.36	81.90	58.07	67.95	60.38
	$L_{A m i n}$	60.53	60.61	60.18	62.92	46.07	37.49	41.60
	$L_{A p e a k}$	88.95	104.67	102.48	109.04	74.17	90.14	72.62
Category area/zone		Industrial (machine shop)				Silence (academic)
Permissible levels (dB)		75 dB				50 dB

The deviation of average noise levels ( $L_{A e q}$ , in dB) from permissible limits at the four designated indoor locations I1, I2a & I2b, and I3, and at the three outdoor locations O1, O2 and O3 near the windows with the existing acoustics (i.e. closed glass windows) have been presented in Figure 2. The observed indoor noise levels at I1 and I3 during the operation of Tig and Spot welding machines were well within the permissible levels of 75 dB; whereas, at I2a & I2b during operation of Mig welding machine were marginally higher than the permissible levels of 75 dB and by 0.57–0.99 dB (0.76–1.32%). However, the $L_{A m a x}$ and $L_{A p e a k}$ were above 75 dB, so personal protection equipment (PPE) for operators such as ear muffs or ear plugs are suggested. The outdoor noise levels due to operations in robotics lab were observed to be within permissible levels of 50 dB at O1 (during the operation of Tig welding) but exceeded at O2 (during the operation of Mig welding) by 10.53 dB (21.06%) and at O3 (during the operation of Spot welding) by 1.78 dB (3.56%). It is, thus, revealed that the operation of Mig and Spot welding has the potential of causing noise nuisance to the adjoining class rooms in the academic area due to sound transmission from the operation of these machines in the existing window acoustics.

Figure 2.

Deviation of noise levels at indoor and outdoor locations with existing glass window acoustics.

The noise indices at the three designated outdoor locations O1, O2 and O3 without and with acoustics (i.e., with glass, curtain, cardboard, thermocol and glass and curtain both) have been tabulated in Table 3. The average noise levels (

L_{A e q}

, in dB) at the outdoor locations (academic area) with acoustics have been compared with the noise levels without acoustics and permissible noise levels in silence/academic area in Figure 3. A glance at the Figure 3, showed that the noise levels were reduced to varying degree at all locations by the usage of acoustics as sound barrier in windows. However, the noise levels were exceeding the permissible level of 50 dB with the usage of curtain, cardboard and thermocol as acoustic barrier in windows. The average

L_{A e q}

value with glass were within the permissible limit at O1 (during the operation of Tig welding), but exceeding the limit by 10.53 dB at O2 (during Mig welding) and by 1.78 dB at O3 (during Spot welding). The average

L_{A e q}

value with both glass and curtain as acoustic were within the permissible limit at O1 and O3 (during Tig and Spot welding), but exceeding the limit by 5.71 dB at O2 (during Mig welding).

Table 3.

Noise indices at outdoor locations without and with acoustics.

Noise indices (dB)	Location code	Without acoustics	With glass	With curtain	With cardboard	With thermocol	With glass and curtain
$L_{A e q}$	O1	61.47	47.27	57.57	56.56	59.86	43.35
	O2	78.33	60.53	73.53	73.23	76.60	55.71
	O3	67.58	51.78	63.38	61.39	64.70	47.58
$L_{A m a x}$	O1	72.27	58.07	68.37	65.97	67.87	54.26
	O2	85.75	67.95	80.95	80.05	82.85	63.18
	O3	76.18	60.38	71.98	74.23	74.67	56.10
$L_{A m i n}$	O1	60.27	46.07	56.37	53.97	55.87	42.12
	O2	55.29	37.49	50.49	49.59	52.39	32.78
	O3	57.40	41.60	53.20	52.00	54.71	37.50
$L_{A p e a k}$	O1	88.37	74.17	84.47	82.07	83.97	70.30
	O2	107.94	90.14	103.14	102.24	105.04	85.25
	O3	88.42	72.62	84.22	80.69	84.87	68.38
Permissible levels (dB)		50 dB during day time for silence zone (academic area)

Figure 3.

Noise levels at outdoor locations with acoustic material in comparison to without acoustics.

The computed Sound Transmission Loss (STL) was plotted for all the studied acoustic options in Figure 4.

Figure 4.

Sound transmission loss (STL) for acoustic materials at outdoor locations.

A glance at the Figure 4 showed that the STL (both in terms of dB and %) was minimum with thermocol (1.61–2.88 dB; 2.21–4.26%), followed by curtain (3.90–4.80 dB; 6.13–6.34%), cardboard (4.91–6.19 dB; 6.51–9.16%) and glass (14.20–17.80 dB; 22.72–23.38%). In the existing scenario of the Robotics lab, the windows have glass pans that are not acoustically sufficient to improve the STL to the desired extent, that is to reduce the $L_{A e q}$ value at outdoor locations within 50 dB as required for academic area. So, the option of a combination of the studied acoustic materials was to be explored for windows that can act as an effective acoustic barrier. As the windows are primarily used to admit daylight through transparent or translucent material, and also for controlled natural ventilation as well as the visual appearance of the building; therefore, a combination of glass and curtain was studied as other materials have limited application as acoustic barrier in windows. With this combination of glass and curtain as acoustic barrier, the STL improved significantly and was observed to be highest in the range of 18.12–22.62 dB (28.88–29.59%). However, the $L_{A e q}$ value at O2 (during Mig welding) was observed to be slightly higher (55.71 dB) than the permissible level of 50 dB in academic area. The results, thus, revealed the importance of glass and curtains as effective acoustic barrier that can be used in windows to prevent sound waves from entering or leaving a noisy place.

The experimental data was then used for developing a mathematical model for predicting the STL for the combination of glass and curtain from the $L_{A e q}$ value without acoustic at outdoor locations (Figure 5(a)). The following mathematical relationship was obtained:

S T L = 0.2577 L_{A e q} + 2.4522

(3)

Figure 5.

Prediction of STL for combination of glass and curtain as acoustic material for windows.

The coefficient of determination (R²) is very high (0.9842) of the above relationship that signify the accuracy of the model in prediction. Thereafter, the actual and predicted values of STL were plotted for validation of the model (Figure 5(b)). The scattering of ±3% along with the excellent computed statistical performance parameters, namely mean absolute error (−0.00016), root mean square error (0.23227) and correlation coefficient (0.992) suggests the application of the proposed model (Equation (3)) for predicting STL for the glass and curtain combination from $L_{A e q}$ values.

Conclusion

The sound levels measured in the Robotics lab of an academic institute showed that the noise inside the lab was within or marginally above the permissible limits as per Indian standards of 75 dB for industrial category; but the operation of Mig and Spot welding were a source of noise nuisance to the adjoining academic area due to the sound transmission from the Robotics lab during the operations of the machines. This necessitates the usage of acoustic barrier so that high indoor noise in the workshop/lab under-industrial conditions does not leave the place and transmits to surrounding academic area. The noise reduction analysis demonstrated the usage of acoustics (glass, curtain, cardboard and thermocol) as sound barriers. The Sound Transmission Loss (STL) was observed to be highest in the range of 18.12–22.62 dB (28.88–29.59%) by using the combination of glass and curtain as acoustic barrier in windows of the Robotics lab; thereby, reducing noise nuisance significantly in the academic area. The proposed model has the potential of predicting STL for the combination of glass and cardboard from $L_{A e q}$ value.

Suggestions and recommendations

It can be suggested and recommended from the above study results that:

⁃ personal protection equipment (PPE) such as ear muffs or ear plugs for workers during operation of the machines,

⁃ curtains must be drawn during the operation of the machines, and

⁃ double glazed windows can be used to further dampen the transmission of sound in academic area.

Footnotes

Acknowledgments

This study was carried out in the Robotics Lab of Siemens Centre of Excellence at National Institute of Technology Kurukshetra. The authors acknowledge the cooperation and support of the staff during the period of study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Surinder Deswal

References

Jayawardana

TSS

Perera

MYA

Wijesena

GHD

. Analysis and control of noise in a textile factory. Inter J Sci Res Pub 2014; 4(2): 1–7. https://www.ijsrp.org/research-paper-1214/ijsrp-p3634.pdf

Ibrahim

Ajao

Aremu

. Industrial noise level study in a wheat processing factory in Ilorin, Nigeria. Int J Appl Mech Eng 2016; 21(2): 511–523. DOI: 10.1515/ijame-2016-0030

Dilay

Ozkan

. Determination of noise level in working with milling machine in mechanical workshops. J Multidis Engin Sci Technol 2019; 6(11): 1112–11115. https://www.jmest.org/wp-content/uploads/JMESTN42353201.pdf

Chandna

Deswal

Chandra

, et al., 2009, Estimation of individual power of noise sources operating simultaneously. World academy of science. Engineering and Technology 3: 373–378. https://www.researchgate.net/profile/Arunesh-Chandra-2/publication/271520859_Estimation_of_Individual_Power_of_Noise_Sources_Operating_Simultaneously/links/54cb2f5e0cf22f98631e38b1/Estimation-of-Individual-Power-of-Noise-Sources-Operating-Simultaneously.pdf

Sadick

Issa

. Occupants’ indoor environmental quality satisfaction factors as measures of school teachers’ well-being. Build Environ 2017; 119: 99–109, DOI: 10.1016/j.buildenv.2017.03.045

Thattai

Sudarsan

Sathyanathan

, et al. Analysis of noise pollution level in a university campus in South India. IOP Conf Ser Earth Environ Sci 2017; 80: 012053. DOI: 10.1088/1755-1315/80/1/012053

Vilcekova

Meciarova

Burdova

, et al. Indoor environmental quality of classrooms and occupants’ comfort in a special education school in Slovak Republic. Build Environ 2017; 120: 29–40, DOI: 10.1016/j.buildenv.2017.05.001

Jozwik

Wac-Wlodarczyk

Michalowska

, et al. Monitoring of the noise emitted by machine tools in industrial conditions. J Ecol Eng 2018; 19(1): 83–93. DOI: 10.12911/22998993/79447

Sajin

Chin

Neo

. Acoustics vs. psychoacoustics: an objective and subjective analysis of classroom acoustics in Singapore. Noise Control Eng J 2019; 67(2): 80–97, https://www.medsci.cn/sci/show_paper.asp?id=7a685121c1a580a9

10.

Ekott

Anita

Akpan

, et al. Evaluation of noise pollution from a welding workshop with a maximum noise level of (96.91±0.83) dBA. World Journal of Applied Science and Technology 2021; 13(2): 201–208. Available at: http://wojast.org/wp-content/uploads/Vol13N2/201_208_corrected.pdf

11.

Atkinson

. Ecology of sound: the sonic order of urban space. Urban Stud 2007; 44(10): 1905–1917. https://www-jstor-org-443.web.bisu.edu.cn/stable/43197543

12.

Baliatsas

van Kamp

van Poll

, et al. Health effects from low-frequency noise and infrasound in the general population: it is time to listen? A systematic review of observational studies. Sci Total Environ 2016; 558: 163–169. DOI: 10.1016/j.scitotenv.2016.03.065

13.

Aygul

Ertugrul

Ersoy

. Measurement of noise level in the fair area. Appl Technol Innovat 2017; 13(1): 21–26. https://www.researchgate.net/publication/320275965_Measurement_of_noise_level_in_the_fair_area

14.

Mamun

MMA

Shil

Paul

, et al. Analysis of noise pollution impacting educational institutes near busy traffic nodes in Chittagong city. 1st International conference on green architecture (ICGrA), Dhaka, Bangladesh, 4-5 August 2017. https://www.researchgate.net/profile/Md-Mustiafiz-Al-Mamun/publication/319879633_Analysis_of_Noise_Pollution_Impacting_Educational_Institutes_near_Busy_Traffic_Nodes_in_Chittagong_City/links/600c8216299bf14088b8d52b/Analysis-of-Noise-Pollution-Impacting-Educational-Institutes-near-Busy-Traffic-Nodes-in-Chittagong-City.pdf

15.

Maqsood

Younes

Minallah

. Industrial noise pollution and its impact on the hearing capacity of workers: a case study of Gujranwala city, Pakistan. International Journal of Economic and Environmental Geology 2019; 10(2): 45–49. DOI: 10.46660/ojs.v10i2.261

16.

Pena

Montero

Rodrguez

. Noise and health. Rev Cubana Med Mil 2019; 48(4). https://revmedmilitar.sld.cu/index.php/mil/article/view/431/375

17.

Farooqi

ZUR

Sabir

Latif

, et al. Assessment of noise pollution and its effects on human health in industrial hub of Pakistan. Environ Sci Pollut Res Int 2020; 27(3): 2819–2828. DOI: 10.1007/s11356-019-07105-7

18.

Kallankandy

Deswal

. A comprehensive review of noise measurement, standards, assessment, geospatial mapping and public health. Ecol Quest 2023; 34(3): 1–26. https://apcz.umk.pl/EQ/article/view/41058

19.

Musca

Popescu

Ursu-Fisher

, et al. Noise assessment in a carpentry workshop. Appl Math Mech 2013; 56(1): 173–176. https://www.researchgate.net/publication/272506806_Noise_Assessments_in_a_Carpentry_Workshop

20.

Obot

Ibanga

. Investigation of noise pollution in the university. Int J Eng Res Technol 2013; 2(8): 1375–1385. https://www.ijert.org/research/investigation-of-noise-pollution-in-the-university-IJERTV2IS80234.pdf

21.

Ozer

Zengin

Yilmaz

. Determination of the noise pollution on university (education) campuses: a case study of Ataturk University. Ekoloji 2014; 23(90): 49–54. DOI: 10.5053/ekoloji.2014.906

22.

Vujica Herzog

Buchmeister

Spindler

. Assessment of school and industrial noise: measurements vs personal perceptions. DAAM International Scientific Book Chapter 2020; 3: 033–048. DOI: 10.2507/daaam.scibook.2020.03

23.

Debanath

Nath

Barthakur

. Environmental noise pollution in educational institutes of Nagaon town, Assam, India. Global Journal of Science Frontier Research Environment & Earth Science 2012; 12(1): 1–5. https://globaljournals.org/GJSFR_Volume12/1-Environmental-Noise-Pollution-in-Edu.pdf

24.

Keerthana

Singhvi

Chitravel

, et al. An analysis of noise pollution in Tirupur city. Scholars J Eng Technol 2013; 1(3): 154–168. DOI: 10.36347/sjet

25.

Lee

Francis

Wang

. How tonality and loudness of noise relate to annoyance and task performance. Noise Control Eng J 2017; 65(2): 71–82. DOI: 10.3397/1/376427

26.

Farooqi

ZUR

Sabir

Zeeshan

, et al. Vehicular noise pollution: its environmental implications and strategic control. In: Ersoy

Waqar

(eds). Autonomous vehicle and smart traffic. London, UK: Intechopen, 2020, pp. 3–19. DOI: 10.5772/intechopen.85707

27.

Benkreira

Khan

Horoshenkov

. Sustainable acoustic and thermal insulation materials from elastomeric waste residues. Chem Eng Sci 2011; 66(18): 4157–4171. DOI: 10.1016/j.ces.2011.05.047

28.

Marques

Barcelos

Silva

HRT

, et al. Recycled polyethylene terephthalate-based boards for thermal-acoustic insulation. J Clean Prod 2018; 189: 251–262. DOI: 10.1016/j.jclepro.2018.04.069

29.

Ming

Pan

. Insertion loss of an acoustic enclosure. J Acoust Soc Am 2004; 116(6): 3453–3459. DOI: 10.1121/1.1819377

30.

Asdrubali

. Survey on the acoustical properties of new sustainable materials for noise control. Acta Acustica united Acustica 2006; 92(1): 1–11. https://www.researchgate.net/publication/228358338_Survey_on_The_Acoustical_Properties_of_New_Sustainable_Materials_for_Noise_Control

31.

Ayub

Fouladi

Ghassem

, et al. Analysis on multiple perforated plate sound absorber made of coir fiber. Int J Acoust Vib 2014; 19(3): 203–211. DOI: 10.20855/ijav.2014.19.3354

32.

Tao

Ren

Zhang

, et al. Recent progress in acoustic materials and noise control strategies–A review. Appl Mater Today 2021; 24: 101141. DOI: 10.1016/j.apmt.2021.101141

33.

Gao

Zhang

Deng

, et al. Acoustic metamaterials for noise reduction: a review. Adv Mater Technol 2022; 7(6): 2100698. DOI: 10.1002/admt.202100698

34.

Kah

Shrestha

Hiltunen

, et al. Robotic arc welding sensors and programming in industrial applications. Int J Mech Mater Eng 2015; 10(13): 13–16. DOI: 10.1186/s40712-015-0042-y

35.

Laiping

Shanben

Tao

. The modeling of welding pool surface reflectance of aluminum alloy pulse GTAW. Mater Sci Eng, A 2005; 394(2): 320–326, DOI: 10.1016/j.msea.2004.11.063

36.

Hunashal

Patil

. Assessment of noise pollution indices in the city of Kolhapur, India. Social and Behavioral Sciences 2012; 37: 448–457. DOI: 10.1016/j.sbspro.2012.03.310

37.

IS . Indian Standards 10988: Method of measuring noise from machine tools (excluding testing in anechoic chambers). New Delhi: Indian Standards, 1984. https://www.services.bis.gov.in/php/BIS_2.0/bisconnect/standard_review/Standard_review/Isdetails?ID=MTM3Njc%3D