Figure 1 - uploaded by Oscar Rikhotso
Content may be subject to copyright.
Source publication
![Hearing conservation and control levels [45].](profile/Oscar-Rikhotso/publication/335438499/figure/tbl2/AS:796677690626054@1566954171346/Hearing-conservation-and-control-levels-45_Q320.jpg)
The chemical manufacturing industry employs sophisticated mechanical equipment to process feedstock such as natural gas by transforming it to usable raw material in downstream sectors. Workers employed at these facilities are exposed to inherent occupational health hazards, including occupational noise. An online and grey literature search on Scien...
Contexts in source publication
Context 1
... evidence of noise exposure in the manufacturing sector inclusive of the chemical manufacturing sector is highlighted by the extent of NIHL compensable claims. Figures 1-3 show that NIHL contributed a fair percentage of occupational illnesses between the three countries notwithstanding differences in defining compensable NIHL by each country. In SA, NIHL is by far the highest reported occupational illness. ...
Context 2
... the US, skin diseases or disorders, respiratory conditions and poisonings amongst others contributed to the total reported illnesses shown in Figure 1. ...
Citations
... • DP 2.2.1.1 -The distance between the user and the spoken input receiver (m) was decided to span between 5cm (for head-mic or wearable microphone) and 1m (for fixed microphone or voice assistant). The design range of 95cm is based on the assumption that the person is speaking at a comfortable tone, at approximately 60dB [25] and assuming that the average dB within an industrial shopfloor is between 85dB and 115dB [26]. • DP 2.2.2.1 -The keyboard and mouse's input latency (ms) as this has been proven to directly influence the user's performance [27] was set at between 2 and 50ms for a standard keyboard and mouse (design range of 48ms). ...
Human-centricity is at the frontier of the novel Industry 5.0 paradigm, in which the well-being of the operator is not solely acknowledged but is actively heeded to. One application of this is in human-robot collaboration (HRC). Working in proximity to a collaborative robot has stemmed productivity, flexibility and assistance, but has also amassed concerns for safety. Designing physically safe HRC workstations is well established in scholarly work and international standards. However, attention must also be directed towards the cognitive facet of safety. Unlike physical safety requirements such as speed or distance, which are reasonably quantifiable; quantification of cognitive requirements may not be as straightforward, owing to the subjectivity of user emotions. Consequently, this work contributes a Kansei Engineering approach geared towards identification and quantification of requirements related to cognitive safety requirements in HRC workstations. The outcomes of this study shall then be implemented within a broader Axiomatic Design (AD) of a physically and cognitively safe HRC workstation, underlining the suitability of using Kansei Engineering to quantify cognitive requirements in preparation of Axiom 1 and Axiom 2 of the Axiomatic Design process.
... The findings of noise exposure values documented in prior research indicated that the mean noise levels in the studies ceramic sector were comparatively lower than those in other industries: textiles (weaving: 88-86 dB (A), and preparing: 63-93 dB (A)) in Ethiopia [51], beverage cans manufacturing (92-98 dB (A)), steel reinforcement forming for concrete (91-95 dB (A)), steel sheets forming and processing (87-91 dB (A)) in Saudi Arabia [52], manufacturing industry (82.8 dB (A)) in China [53], automotive industry (85 dB (A)) in China [54], transportation equipment manufacturing industry (84.3-90.3 dB (A)) in China [55], construction equipment operators (>85 dB (A)) in Iran [56], automotive assembly industry (83.41 dB (A)) in Iran [57], ceramic industry (82.3 -92.6 dB (A)) in Iran [26], workshops of car oil change (95 dB (A)) and aluminum makers (98.4 dB (A)) in Iran [58], food manufacturing (90-92 dB (A)) in US, food processing (88-94 dB (A)) in UK, paper manufacturing (90-92 dB (A)) in US, printing and publishing (82-93 dB (A)) in US, petroleum and coal products manufacturing (87-92 dB (A)) in US [59], chemical industry (91-100 dB (A)) in South Korea [60], steel industry (90-100 dB (A)) in UK [59], small scale hand tools manufacturing industry (81-110 dB (A)) in India [61], and petrochemical industry (88-93 dB (A)) in Iran [62]. Nonetheless, the noise levels and exposure profile may vary based on the industry's equipment type and manufacturing process. ...
... The findings of noise exposure values documented in prior research indicated that the mean noise levels in the studies ceramic sector were comparatively lower than those in other industries: textiles (weaving: 88-86 dB (A), and preparing: 63-93 dB (A)) in Ethiopia [51], beverage cans manufacturing (92-98 dB (A)), steel reinforcement forming for concrete (91-95 dB (A)), steel sheets forming and processing (87-91 dB (A)) in Saudi Arabia [52], manufacturing industry (82.8 dB (A)) in China [53], automotive industry (85 dB (A)) in China [54], transportation equipment manufacturing industry (84.3-90.3 dB (A)) in China [55], construction equipment operators (>85 dB (A)) in Iran [56], automotive assembly industry (83.41 dB (A)) in Iran [57], ceramic industry (82.3 -92.6 dB (A)) in Iran [26], workshops of car oil change (95 dB (A)) and aluminum makers (98.4 dB (A)) in Iran [58], food manufacturing (90-92 dB (A)) in US, food processing (88-94 dB (A)) in UK, paper manufacturing (90-92 dB (A)) in US, printing and publishing (82-93 dB (A)) in US, petroleum and coal products manufacturing (87-92 dB (A)) in US [59], chemical industry (91-100 dB (A)) in South Korea [60], steel industry (90-100 dB (A)) in UK [59], small scale hand tools manufacturing industry (81-110 dB (A)) in India [61], and petrochemical industry (88-93 dB (A)) in Iran [62]. Nonetheless, the noise levels and exposure profile may vary based on the industry's equipment type and manufacturing process. ...
This study aimed at providing a framework for prioritizing workplaces in terms of noise control in the ceramic industry, as exposure to industrial noise has long been recognized as an occupational hazard. A TES-1354 device was used to measure the noise level. The WHC continuous noise index was used to calculate the amount of noise pollution brought on by process equipment. Finally, the industry's workplaces were prioritized for noise control using the noise control prioritization index (NCPI), which considers three factors: the number of individuals exposed, the duration of exposure, and the weighting factor based on the intensity of exposure to noise. The sound pressure level (SPL) values in the studied industry were measured between 69 and 93.70 dB (A). Furthermore, 20.53% of all measured stations were in the high-risk limit (SPL ≥ 85 dB(A)), while 79.47% fell within the safe range (69 ≤SPL<85 dB(A)). For stone crushing workplace, WHC continuous noise index values were found to be near 1, indicating unpleasant working conditions for workers. Additionally, the highest value of NCPI was estimated for the stone crusher workplaces. Our findings indicate that the stone crusher workplace is the priority for noise emission control.
... Examples of effective cost saving strategies achieved by noise control includes buying quite equipment and machinery (Nelson, 2011;Beamer et al., 2016). Uncontrolled noise in industry, a result of insufficient engineering control solutions (Veebeek et al., 2014;Rikhotso et al., 2019), imposes financial costs on workers, employers, and compensation systems (Leigh et al., 2003;Leigh et al., 2004;Leigh, 2006Leigh, , 2011. Consequently, companies rely on the use of HPDs as a primary control measure, which has a number of inherent shortcomings such as incorrect selection (Rikhotso et al., 2018), uncertain regulatory guidance on labelling requirements (Rikhotso et al., 2021), improper fit and use (Maisarah and Said, 1993;Canetto et al., 2009;Balkhyour et al., 2019). ...
The Occupational Health and Safety Act 1993 and its attending Regulations in South Africa, require employers to conduct cost analysis studies to inform decision-making related to exposure control for occupational health hazard such as noise. Cost analysis, as per South African National Standard/ISO 31000 risk assessment guideline, is an important input for the decision-making process of the risk management process. The costs of administrating a hearing conservation programme intended to minimise noise-induced hearing loss is an example of a cost analysis. This study enrolled four companies from the South African manufacturing and utilities sectors with the aim of establishing whether cost analysis is included during the noise risk assessment process; and determining administration costs of HCP administration. A HCP cost questionnaire was completed by each company's occupational hygiene professionals and risk officers. None of the companies in the study included cost analysis in their respective risk assessment processes. The overall costs, derived from the HCP cost item questionnaire, was much greater for Company A (4 290 014 Rands) than all of the other companies combined (970 685 Rands). Hearing protection device expenditures across the four companies were the greatest expense, while audiometry was the smallest expense owing to service internalisation. The HCP expenditures are incurred on periodic basis, yearly or biennial, and are internalised in companies as direct costs. Cost analysis can enhance the noise risk assessment process by providing additional input to support the decision-making process related to noise control. This challenges the occupational hygiene profession to pursue new frontiers and decision-making models in the scope of noise risk management, beyond noise measurements and hearing protection device use recommendation.
... For example, the increased use of hand tools (electric, combustion, pneumatic and hydraulic) causes exposure to noise and HAV. For this reason, their effects have been analysed in many productive sectors such as construction [12,13], agriculture [14][15][16], forestry [17,18], metallurgy [19], textile industry [20], chemical manufacturing [21], automobile manufacturing [22], mining [23], the mining industry and mechanical engineering [24] etc. The issue of occupational noise and vibration exposure is so relevant that the Sixth European working conditions survey [25] reports that 28% of all workers are exposed to high noise levels for more than a quarter of the working day in different labour sectors. ...
... As can be expected, if we take into account both exposures, the recommended combined exposure time T CexpMax is less than T CexpVibMax or T CexpNoiseMax . Table 5 lists the values of the Dvibration and Dnoise for this combined recommended exposure time T CexpMax , by ensuring that the sum of both noise and HAV doses becomes equal to Equation (21). Table 5. Dvibration and Dnoise achieved for the combined recommended maximum exposure time T CexpMax . ...
In many production and industrial sectors, workers are exposed to noise and hand-arm vibrations (HAV). European directives have established the maximum limit values or exposure action values for noise and vibration independently. However, in many cases, workers who endure hand-arm vibration also receive high noise levels. This research suggests a procedure to aid the establishment of precautionary measures for workers with simultaneous exposure to both physical agents. This procedure defines a combined index based on the energy doses for both noise and HAV. From this combined index, the suggested methodology allows a recommended exposure time for workers with simultaneous noise and HAV exposure to be calculated. This methodology can be adapted to tackle the relative importance assigned to both agents according to the safety manager and new knowledge on combined health effects. To test this method, a measurement campaign under real working conditions was conducted with workers from the olive fruit-harvesting sector, where a variety of hand-held machinery is used. The results of the study case show that the suggested procedure can obtain reliable exposure time recommendations for simultaneous noise and HAV exposures and is therefore a useful tool for establishing prevention measures.
... This then points to OD prevalence being a result of neglected unsafe working conditions and a deterioration of implemented exposure control measures [125], including by companies listed in Table 1. With regard to shortcomings in NIHL prevention efforts specifically, the incorrect selection of hearing protection devices, inadequate noise training programmes, and lack of implementing noise engineering controls have been showed as contributory factors in its prevalence from a study conducted at a South African chemical manufacturing company [126][127][128]. ...
This paper explores the potential of Corporate Social Responsibility disclosures in providing alternative information on the extent of occupational health hazard impact on workers, by selected South African companies operating within the manufacturing and utilities sectors amidst an absent national occupational disease surveillance system. An online internet search was used to retrieve publicly available national occupational disease statistics published between 2001 and 2020, and Corporate Social Responsibility reports of selected South African case companies, published between 2015 and 2020. Content analysis was used to analyse the retrieved documents for both descriptive and numeric data. The collection and reporting of occupational disease data in South Africa is inconsistent. Corporate Social Responsibility disclosures related to occupational health metrics vary between companies. Occupational disease incidence was the least reported of the social aspects in Corporate Social Responsibility disclosures, and/or were reported as a single statistic or combined into occupational safety incidence rates in some instances, obfuscating the true extent of the impact caused by occupational health hazards on workers. Furthermore, noise-induced hearing loss remains the most prevalently reported occupational disease, in general. Corporate Social Responsibility reports point to occupational health hazards requiring regulatory intervention, whilst also providing an alternative information source for occupational disease statistics.
... However, the manufacturing, utilities, agriculture and trade sectors are often cited as the most hazardous [10], compared to office-based work associated with community service and finance. Employees at these industries are often exposed to physical, chemical and biological occupational health hazard types [10,19,[72][73][74][75], which are all linked to the ODs in Table 1. The paucity of the Compensation fund-derived OD and injury statistics complicates the process of attributing the specific sectors from which these accidents emanated. ...
... The manufacturing sector consequently has the highest number of noise-exposed workers [125,126]. Workers in different industries, such as coal-fuelled power plants, textile mills, chemical manufacturing plants and steel plants, are also exposed to noise levels above the regulated exposure limits during routine activities [19,74,112,[126][127][128][129][130]. Maximum noise levels measured in these sectors can reach 120 dB [128] and contain different spectral frequencies [131]. ...
Operations in general industry, including manufacturing, expose employees to a myriad of occupational health hazards. To prevent exposure, occupational health and safety regulations were enacted, with both employers and workers instituting various risk reduction measures. The analysis of available occupational disease and injury statistics (indicators of worker physical health) can be used to infer the effectiveness of risk reduction measures and regulations in preventing exposure. Thus, using the READ approach, analyses of occupational disease and injury statistics from South African industry, derived from annual reports of the Compensation Fund, were conducted. The publicly available database of occupational disease and injury statistics from the South African general industry is unstructured, and the data are inconsistently reported. This data scarcity, symptomatic of an absence of a functional occupational disease surveillance system, complicates judgement making regarding the effectiveness of implemented risk reduction measures, enacted occupational health and safety regulations and the status of worker physical health from exposure to workplace hazards. The statistics, where available, indicate that workers continue to be exposed to occupational health impacts within general industry, notwithstanding risk reduction measures and enacted regulations. In particular, worker physical health continues to be impacted by occupational injuries and noise-induced hearing loss. This is suggestive of shortcomings and inefficiencies in industry-implemented preventive measures and the regulatory state. A robust national occupational disease surveillance system is a regulatory tool that should detect and direct policy responses to identified occupational health hazards.
Compressors are a significant source of noise in various industries. Silencers can be utilized to mitigate this noise. This study aims to design and construct an expansion silencer that can effectively reduce the pulsating noise produced by a reciprocating compressor. This study employed a model-experimental approach to investigate the performance of four different sizes of expansion silencers in controlling the pulsating noise in the suction part of the compressor. Initially, the silencers' sound transmission loss and pressure loss were simulated using the finite element method with COMSOL software. Subsequently, the sound transmission loss of the silencers was measured according to the E261109 standard using an impedance tube. Finally, the pressure loss of the silencers was measured using a Pitot tube upstream and downstream of the silencer at various flow rates. The results of the modeling showed that increasing the diameter of the silencer leads to an increase in transmission loss at all frequencies. Additionally, raising the length of the silencer only increased the number of sound transmission loss peaks in the frequency bandwidth without significant change in sound transmission loss. Furthermore, the results of the experimental measurements with an impedance tube revealed that increasing the diameter results in increased transmission loss, while increasing the silencer length leads to an increase in the number of transmission loss peaks without altering the transmission loss. Moreover, the modeling and experimental pressure loss results indicated that increasing the diameter of the expansion chamber causes an increase in pressure loss, while increasing the length of the expansion chamber results in a minor change in pressure loss. Finally, the research results showed relatively good agreement between modeling and experimental outcomes.
Research on noise studies informs that noise disturbance is caused by many sources which can come
from industrial and non-industrial categories. Noise is a study in the realm of ergonomics, so development to
take an important role in knowing the handling and preventing health problems in the future is needed. A data
collection of several journals indexed by Scopus and registered with Google Scholar with a total of 40 articles
on noise has been carried out with a period of publication over the last decade, 2011-2021. The results of the
analysis found that air pollution is part of the dominant noise effect from the non-industrial sector rather than
the industrial sector in ratio. Among the non-industrial categories include traffic density, airport activity, train
noise, and others. Meanwhile, industrial activities generally originate from the sound of machines that
produce or operate for the duration of the work. All sources of noise must be reduced as they can cause
hearing loss.
