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«FICHA TÉCNICA Título Segurança e Higiene Ocupacionais - SHO 2012 - Livro de Resumos Autores/Editores Arezes, P., Baptista, J.S., Barroso, M.P., ...»

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Pode-se concluir que as boas práticas de gestão da segurança e saúde no Trabalho e dos resíduos gerados no processo produtivo das empresas dos diversos setores de atividades são indicadores de uma atuação empresarial ética e socialmente responsável.

5. REFERÊNCIAS Associação Brasileira de Empresas de Limpeza Pública e Resíduos Especiais (ABRELPE) (2009). Panorama dos Resíduos Sólidos no Brasil.

Conselho Nacional do Meio Ambiente (2008). Resolução n. 307, de 05 de jul. de 2002: Estabelece diretrizes, critérios e procedimentos para a gestão dos resíduos da construção civil. Brasília: Conama.

Dias, L. M. A. (2009). Inspecting Occupational safety and health in the construction industry. Turin: ILO/ITC.

European Commission (2001). Promoting an European Framework for corporate social responsibility. Bruxelas: European Comission.

Grajew, O. (2001). Por um mundo mais seguro: a crise mundial coloca em evidência a responsabilidade das empresas na busca e na construção de uma sociedade mais justa. São Paulo Exame.

John, M. J.; Agopyan, V. (2001). Reciclagem de resíduos da construção. Seminário Reciclagem de resíduos sólidos domiciliares.

Norma Regulamentadora n.º 18 (2011). Condições e meio ambiente do trabalho na indústria da construção. Brasília: Ministério do Trabalho e Emprego.

Pinto, T. P. (1999). Metodologia para gestão diferenciada de resíduos sólidos da construção urbana. Tese (doutorado). Escola Politécnica da Universidade de São Paulo. São Paulo.

Occupational Safety and HygieneInternational Symposium on

Ergonomics Aspects and Mental Workload of Operators of Electric Power Control Centers: Case Studies in Northeast Brazil Melo, Miguela, Masculo, Franciscob, Vitorio, Daianac, Silva, Luiz Buenod a Federal University of Paraíba, Pos Graduação em Engenharia de Producao, Cidade Universitaria, Joao Pessoa-PB, Brazil, 58051-970, mobcmelo@ct.ufpb.br, bmasculo@ct.ufpb.br, cmvdaiana@hotmail.com, dbueno@ct.ufpb.br

1. INTRODUCTION Currently, the electricity sector is made up of dozens of companies in many different states and regions, which can reach much of the country. The activities performed and services provided by the electric sector are essential to the whole population and this is an important ingredient to the development of a country. One of the biggest challenges that companies face is increasingly related to the health and the welfare of workers especially those directly linked to system operation, in technical operations.

The activities of the operators of Electric Power Control Centers are carried out through cognitive tasks that are complex and specialized. They have as a standard item the prevention of incidents that disrupt the electrical system, or when it is no longer possible, the process of trying to return to a normal situation, which is called system recovery. They have to do it by mobilizing knowledge and reasoning for which they received adequate training from the point of view of the existing rules. However, there are some factors that need to be improved, since there are still incidents and accidents, caused mainly caused by fatigue, lack of concentration or due to inadequate operator / screen / machine / computer.

The operators of these areas are subject to a high degree of uncertainty because the actions of supervisory control and there is a need for an operator to handle various types of data and information, often responding to several requests efficiently and in a timely manner (Oliveira, 2009).

Thus, it is clear that the development of tasks, requiring more complex development processes related to the activities of control and diagnosis, and excels in such activities, where the human error can cause serious risks and losses.

The Electric Power Control Centers have a basic activity such as monitoring the functioning of the power substation, where it is essential to make decisions and process information continuously. For this, there is a request of frequent mental technicians involved in these centers because of the need to maintain attention, memory and reasoning request.

Among the factors involved in the decision-making capacity these may be cited (Santos; Zamberlan, 1992):

• Postural requirements: Depending on factors such as existing equipment, lighting, state of continuous attention, the task requires, and may lead to worker fatigue and impact on health and productivity of the same company;

• The difficulty in interpreting the data: What can happen either due to environmental conditions such as noise, inadequate lighting and temperature as well as the qualitative and quantitative aspects of the presentation of information?

• Those related to the visual aids and verbal information.

• The duration of activity The impacts that may arise due to problems in electric power substations can lead to severe disorders resulting from failures in electricity supply and affect also the concessionaire itself, which is subject to fines and penalties by ANEEL (Electric Energy Brazil National Agency). Thus, this fact drives the electricity companies to have human resources capable of making decisions quickly and effectively in order to attend the events, both as emergency contingency (Neves,2007).

Currently the automated equipment performs the greater proportion of mechanical and repetitive activities, while humans perform activities in dynamic contexts, requiring flexibility and quick adaptation to effective performance. This adaptation to constantly changing circumstances due to the variability of processes and supervisory function of employees requires complex skills and cognitive abilities. In this scenario, the incorporation of cognitive component analysis of the work became a necessity, so that we can satisfactorily answer the complex skills involved in the operation of modern systems and shift work (Akerstedt et al. 1998; Baulk et al. 2009). Moreover, new technologies allow man and technology to be closer, while increasing productivity gains.

The aim of this study is to evaluate the mental workload of operators of electric power control centers in order to identify the factors that most contribute to the perception of the workload by employees and identify possible situations of overload.

1.1. Mental Workload and Cognitive Ergonomics The concept of workload originally derived from studies of occupational psychology, but was later taken up and developed by ergonomics. It covers the physical effort, the cognitive and psychoaffective (emotional) to meet the demands of the task and is divided into physical and psychic pressure. On the other hand, the physical workload is mainly due to the technical requirements for processing the work object and can be present both in the workplace and outside it, where it is cited as an example, noise, temperature and lighting. On the other hand, the mental burden is related in a general way to the stress or psychological unbalance in the organization. The concepts of mental workload are related to cognitive ergonomics, since this branch deals with the cognitive aspects related to the task through the cognitive architecture that involves the description of the different elements that constitute the cognitive system and their relationships. Mental workload refers to the workload related to psychological and cognitive aspects of the task (Meijman et al. 1997, Murata et al., 2005). The association between mental workload and cognitive architecture was proposed by Richard (1990) and can be seen in Figure 1.

Figure 1 - Cognitive architecture associated to mental workload concept.

In the model presented, the consideration that automated reasoning has a mental burden lower than those associated with resolving problems. This initial guess can be confirmed or not in a particular work situation.

In the Electric Power Control Centers there is a basic activity functioning surveillance system, where it is essential to make decisions and process information continuously. For this, there is a common mental request of personnel involved in these operation centers because of the need to maintain attention, memory and reasoning request (Ku et al., 2010).

They have to do it by mobilizing knowledge and reasoning for which they received training, which under the terms of the current standards are adequate, however, there are some factors that need to be improved, there are still incidents and accidents, caused mainly caused by fatigue, lack of concentration or due to inadequate operator and computer screen (Carvalho et al., 2005).


This research was a descriptive study, and its results were analyzed quantitatively in electric power substation in Northeast Brazil, comprising 27 operators.

The instrument used was the National Aeronautics and Space Administration Task Load Index known as the NASA-TLX (NASA, 2008), developed by the NASA Ames Research Center in 1986, after 3 years of studies involving over 40 laboratories research and flight simulations. The NASA-TLX method works with physiological indicators associated with subjective methods in situations simulated in the laboratory or in real situations and operational work, taking great advantage of being applicable to various operators and activities without the need of change in its structure. The NASATLX was developed from the concept of mental workload of standard DIN 33405:1987-02s predecessor, in accordance with standard ISO 10075.

It is a multidimensional assessment procedure that gives an overall score of the workload based on a weighted average of the scores obtained in the six factors of NASA-TLX scale. These six factors are as follows: levels of achievement, effort and frustration, which have strong influence from the characteristics of individual operators, and the requirements of mental, physical, and time factors that are determined by the work situation (NASA, 2008).

With regard to satisfaction with the performance of the staff, the level of effort with respect to how much one has to work physically and mentally to achieve a good performance, as well as the level of frustration, there are factors that inhibit the performance of work, such as insecurity, irritation, lack of stimulation, and setbacks are important. On the other hand, the mental requirement involves mental activity needed to complete the work, and the physical requirement corresponds to physical activity required for the performance of work requirement and time on the level of pressure needed to achieve the same as shown in the Table 1.

Table 1 - Factors considered in the NASA-TLX Instrument Factors considered Low Limit High Limit Mental Demand Tasks considered easy, simple, goals achieved without Tasks difficult, complex, requiring much difficulties mental effort to achieve the goal Physical Requirement Light, slow, easily accomplished tasks Heavy, quick, strong, and lively tasks

–  –  –


The overall weighted average ranged from 8.81 to 17.77 (MV= 14.24, SD = 4.40). In order to obtain an overview of the overall scores given by the weighted sample, descriptive analysis was performed, as mean, standard deviation and quartiles according to Table 2.

–  –  –

The higher the average Mental Requirement (MR), the more the individual feels that demand in the workplace. The average was 17.77 MR. The distributions of scores by percentile shows that 75% of the sample has a score of 20.00.

Taking into account that the scale of the domains varies from 10 to 20, the mid-point (which represents a point of indifference or neutrality) is 19.00, scoring 19.00 indicates that 75% of the sample has high scores in MR.

With regard to the Physical Demands (PD), we found that 25% of the sample has to score 7.00. Thus, one quarter of the sample has low scores. Half of the sample (50%) had scores of up to 11.00, which equates to a low score on a scale ranging from 1 to 20. The average PD is 10.25. It is observed that the demand for physical effort is indeed very small, since most of the time the operators are sitting, they stand only in certain situations to monitor the machines or when directed into the courtyard to perform inspections on equipment.

With regard to the Temporal Requirement (TR), it is in general the average of 17.00 which shows high levels of mental demands. This is confirmed by the distribution by quartile, while 25% of the sample has to score 17.00 in the scores of temporal requirement. Half of the distribution has to score 19.00. Thus, the sample of operators has high time requirements. The Level of Effort (LE) brings together the physical and mental demands and the study has an average of

15.88. It is observed that 25% of the sample has scores up to 17.00, thus, one quarter of the sample has moderate score, 50% of the sample have scores to 19.00. As mental demands present high values, while the physical demands, low values, there is a level of effort to moderate score.

The distribution of scores by quartile shows that, with respect to Level of Achievement (LA), 25% of the sample has a score of 15.00, while 75% has a high score of 19.00. The average of 15.74 shows a high score. We conclude that the operators are happy when they successfully perform the activities they are intended.

Level of Frustration in the field (LF), 50% of the sample has a low score of 10.00 and scores of 75% of the sample is

14.00. As a result, operators have low values in relation to the level of frustration in this way; they feel safe when they realize their work. This security may be a consequence of routine training that the company does, thus giving subsidies to employees to perform their activities.

In this light, it appears that among the analyzed categories that make up the overall rate the highest weighted average corresponds to Mental Requirement ( X = 17.77), followed by Temporal Requirement ( X = 17.00). The lowest averages relate to Physical Requirements ( X =10.25) and the frustration level ( X = 8.81).


- The measurement of the mental requirements average level was high EM=17.77 (range 1.00 to 20.00). The distribution of scores by percentile shows that 75% of the sample has maximum score to EM=20.00.

-With this method there will be subsidies for an assessment of mental workload and ergonomic aspects of the operators at the Electric Power Control Centers.

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