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Universidad Autónoma de Ciudad Juárez. Corresponding author's Email: [email protected] Author Note: Eng. Virginia De la Torre has an Industrial ...
The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014

Workload Assessment in Industrial Settings: A Proposal Applying the Analytic Hierarchy Process Virginia De la Torre1, Juan Luis Hernandez2, Jorge Luis García1, and Gabriel Ibarra Mejia1 1

Universidad Autónoma de Ciudad Juárez Departamento de Ingeniería Industrial and Manufactura 2

Universidad Autónoma de Ciudad Juárez Departamento de Diseño

Corresponding author's Email: [email protected] Author Note: Eng. Virginia De la Torre has an Industrial and Systems Engineering from Universidad Autonoma de Ciudad Juarez, Mexico, is actually a student of Master degree on Industrial Engineering with specialty on Ergonomics at the same University. Dr. Juan Luis Hernandez-Arellano has a Doctoral degree on Engineering Science from Universidad Autonoma de Ciudad Juarez and is a Professor in the Design Department at Universidad Autonoma de Ciudad Juarez. Dr. Jorge Luis Garcia Alcaraz has a Doctoral Degree in Industrial Engineering Science from Instituto Tecnologico de Ciudad Juarez, actually joined the Department of Industrial Engineering at the Universidad Autonoma de Ciudad Juarez. Dr. Gabriel IbarraMejia has a MD and MS degree from Universidad Autonoma de Ciudad Juarez, he also has an MS degree in Ergonomics from Lulea Tekniska Universited in Sweden, and a PhD in Environmental Science and Engineering from the University of Texas at El Paso, actually joined the Department of Industrial Engineering at the Universidad Autonoma de Ciudad Juarez. Abstract: The perceived workload by workers is a construct that has been analyzed and assessed more qualitatively than quantitatively. The beginning of the assessment of subjective constructs started using perceptual scales; an example is the Rating Perception Scale (RPE) Borg 0-10 or the Cooper-Harper scale. For workload assessment, methods such as NASATLX and SWAT have been developed. However, variables considered by these methods are not enough to assess the workload in industrial settings. This research reports a proposal of a method for the assessment of workload using the Analytic Hierarchy Process for the development of a workload index. The new method considers eight groups of variables: Mental demand (5 items), physical demand (5 items) global effort (2 items), temporal demand (1item), performance (1 item), frustration (4 items), environmental factors (5 items) and body postures (4 items). The study was conducted at a manufacturer of Constant Velocity (CV) joints located in central Mexico. In order to develop the new method; tasks of CNC lathes operators who perform physical and mental tasks were analyzed. The results of the workload indices obtained with the new method were correlated with the index of workload NASA-TLX getting low correlations. Keywords: Workload, AHP, Industrial Settings

1. Introduction Modern systems of work show a potential change of physical activities to mental activities, increasing the jobs with mental activities and reducing the jobs with physical activities (Dalmau, 2007; Mondelo, Gregori and Barrau, 1994). Weiner (1982) defines workload as the measure of various stressors that affect the performance and responsiveness of a worker. De Pablo (2004) refers that workload is a set of psychological and physical job demands. For Sebastian, Idoate, Llano and Almanzor (2008) workload are requirements imposed by the task, were physical and mental resources are necessary to perform the task successfully. Furthermore, Hart and Stavenland (1988) define mental workload as a result of the interaction between the requirements of the task, the circumstances under which it is executed and the skills, behaviors and perceptions of the subject. DiDomenico and Nussbaum (2011) indicate that the mental workload is higher during elbow flexion and increased frequency of movements. However, Mehta, Harrop, and Agnew (2009) found that the shoulder muscle activity increases with increased physical exertion and decreased when the task involves mental processing. Additionally, worker health can be affected when efforts, movements, or awkward postures are performed (Mondelo et al., 1994). Other authors (Jung and Jung, 2001; Kawada and Ooya, 2005; Llaneza, 2002) indicate that the increased of physical and mental workload is related to increased injury and illness. One of the most used methods to assess workload is the National Agency Space Administration Task Load Index (NASA-TLX; Hart and Staveland, 1988), which is sensitive to identify differences of mental workload and to identify the ISBN: 97819384965-2-3

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The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014 difficulty of the task. Therefore, the method could differentiate between easy and difficult tasks (Lopez, 2010). It also provides the overall level of workload and detects a valid and reliable manner charging sources (Diaz et al., 2010). Jung and Jung (2001) developed the Overall Workload Assessment Technique (OWAT) to assess workload for various tasks and workplaces based on the Analytical Hierarch Process (AHP). Workload is assessed by four factors, physical job demands, environmental factors, postural discomfort, and mental job demands. Items considered in each factor are assessed using different likert scales. Overall workload level (OWL) is offered as an index using a 0-1 range. This research is based on NASA-TLX and OWAT methods to developed the Combined Workload Assessment (CWA). The objectives in this research are: 1) propose a new method for the assessment of combined workload using the Analytical Hierarch Process (AHP) and 2) apply the new method in a sample of Control Numerical Computerized (CNC) lathes operators. This research was conducted in a company located in the state of Guanajuato, in Central Mexico. Constant Velocity (CV) joint are manufactured in the company. Only one production process was analyzed (metal machining) where CNC lathes are utilized.

2. Methodology 2.1 Study design The presented study is observational, cross-sectional, and correlational. Only the descriptive results and correlations between data obtained from the NASA TLX subjective method and proposed method are reported here.

2.2 Sample of workers CNC lathe operators were surveyed in two production lines that perform machining parts named "Tulip" and "bell". Inclusion criteria for participants in the research were: • Have at least 6 months doing the same activity. • Have training to do their jobs. • Perform the machining of bell and tulip Worker’s selection was not random because of the availability of staff to participate. The study was approved by the academic committee of the Master in Industrial Engineering from the University of Ciudad Juarez. The workers were informed of the objectives of research emphasizing the confidentiality of the information obtained from them.

2.3 Materials 2.3.1 NASA-TLX The data recorded with the NASA-TLX method was held by the following: the purpose of the application of NASATLX method was explained to workers, as are the factors evaluated, the definition of the dimensions to be measured, and to answer the survey were asked to analyze the requirements of them job. The data obtained with the NASA-TLX method was evaluated in two phases. In first, the six variables are assessed independently using a visual analog five-point scale response. In the second phase, pairwise comparisons were made between six variables. NASA-TLX final workload score has a range from 0 to 100.

2.3.2 Combined Workload Assessment (CWA) The CWA was developed based on the NASA-TLX and OWAT methods. Eight dimensions integrate the CWA method: mental-demand, physical demand, global effort, performance, frustration, environmental factors, and postural factors. The proposed method used two phases, scoring and weighing. In the first phase, workload in each variable is defined by the worker using a visual analog scale which consists of 9 points-response, where 1 corresponds to "None", 3 "Low", 5 "Medium", 7 "high", 9 "Extremely high". Values 2, 4, 6, 8 are intermediate between each consecutive number. In the second phase, comparisons are made to determine the factors that contribute to mental and physical workload. To collect different levels of weighting in the second evaluation the Analytical Hierarchy Process (AHP) are used. Dimensions and items included in CWA method are shown in table 1.

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The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014 Table 1. Dimensions and items consider in CWA method. Dimensions Mental demand

Physical demand

Global effort

Performance Temporal demand

Items Make decisions Think Make calculations Remember Watch/Looking for Lifting Press Push Turn Control Mental effort Physical effort

Dimensions Frustration

Items Unsafe Stressed Irritated Unhappy

Environmental factors

Weather Lighting Vibration Noisy Chemicals Standing Bend Squat Twist

Postural factors

Performance Timework

2.4 Methods To reach the overall goal of this research field exploration was performed. Identification of workstations was performed with the help of security and health personnel, and medical personnel of the company.

2.5 Data Analysis To evaluate the CWA subjective method, the first step was to determine the reliability and validity of the questionnaire using Cronbach's alpha, because the questionnaire data are of ordinal type applied. In the second phase the mathematical method Analytic Hierarchy Process (AHP), was used to collect different weighting factors. Since this approach calculates the ratio of the subjective judgment of each type of workload and weighs each workload impacted based on the perception of the subject (Jung and Jung, 2001). Finally the results obtained by the proposed method CW was compared with the results of the NASA-TLX method, using Pearson correlation among the results of the method on each task evaluated. For all statistical analyzes a significance level of α was used = 0.05. All data were analyzes performed using the computer system SPSS version 18 and Excel 2007.

3. Results 3.1 Demographic data Participants' informed consent was obtained. The total sample was 17 workers. 2 were women and 15 men. Academic level: 7 have high school education and 10 have technical education. Average of weight is 73.10 kg (±15). Average of stature is 169.94 cm (±7.33). Average of age is 30.26 years (±7.39). Workers have an average of 2 years of experience operating CNC lathes. The scheme includes extended work shifts of 12 hours for 4 days a week and rested for two days, after the break change shifts is given.

3.2 Evaluation of the workload 3.2.1 Ranking with NASA-TLX method Figure 1 shows the NASA-TLX overall workload perceived by CNC lathes operators. The maximum is 85 and present in the area of machining bell.

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The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014

Figure 1. NASA-TLX overall workload.

3.2.2 Ranking the Combined Workload Assessment method Internal consistency for CWA method using the Cronbach's alpha index is 0.839. An example of the analysis of data collected with the CWA method by means of pairwise comparisons using the mathematical method of Hierarchical-AnalysisProcess AHP is presented in Figure 2. In this example, a result of CWA index for worker 6 is presented. Workload Tulips machining Worker 6 : 0.6688

Physical Demand 0.012

Mental Demand 0.06

Decision 0.45

Think 0.26

Effort 0.20

Calculation 0.15

Lifting 0.24

Invironmental 0.08

Postures 0.06

Look 0.04

Remember 0.07

Pull 0.19

Frustration 0.33

Performance 0.10

Push 0.42

Time 0.9

Turn 0.03

Control 0.08

Mental eeffort 0.1

Physical effort 0.83

Unsafe 0.51

Stressed 0.08

Climate 0.47

Standing 0.04

Irritated 0.27

Lighting 0.26

Discontent 0.11

Vibration 0.11

Crouch 0.60

Figure 2. CWA example

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Performance 0.16

Noise 0.04

Squat 0.23

Chemicals 0.10

Squatting 0.10

The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014 Figure 3 shows the results for CWA for tulip and bell machining tasks.

CWA Workload

60

66

52

44 44 41 39

40

33

64

51 55

40

43 49

27

64

56

55

B-S17

B-S16

B-S15

B-S10

B-S9

T-S14

T-S13

T-S12

T-S11

T-S8

T-S7

T-S6

T-S5

T-S4

T-S3

0

T-S2

20 T-S1

Workload

80

Worker

Figure 3. Workload, CWA assessment staff machining

3.3 Correlations Table 2 contains the results obtained with the NASA-TLX and CWA methods for tulip and bell machining tasks.

Table 2. Data from staff machining Method Worker NASA-TLX CWA

Process 1 67 52

2 49 44

3 81 44

4 75 41

Tulip 6 7 81 69 66 33

5 76 39

8 81 40

9 60 43

10 76 49

11 77 27

12 64 51

13 83 55

14 76 64

Bell 15 16 85 80 56 64

17 70 55

Correlations obtained between results of NASA-TLX and CWA methods are shown in Table 3. Low correlations were found in both tasks. Table 3. Pearson´s correlations between NASA-TLX and CWA Piece/process Tulips. Sample=12 Bell. Sample= 4

Pearson cor. Sig.

NASA-TLX 1

CW .120 .709

1

.398 .602

Pearson cor. Sig.

4. Discussion and conclusion Data analysis collected with the NASA-TLX subjective method and the proposed method CWA indicate moderate workloads. This is probably because the workers perform their activities mostly standing manipulating parts with one or both hands. Borghini et al., (2012) indicates that the perceived level of workload can be affected by the experience, skills or just individual differences. Which may be related to performance and cognitive resources available for task execution (Szalma, 2008). For its part DiDomenico and Nussbaum (2005) indicate that postural stability and cognitive tasks influence the individual performance decrement. As a limit to the assessments made and methods used, was the lack of data of equal size 36

The XXVI Annual Occupational Ergonomics and Safety Conference El Paso, TX, USA June 5-6, 2014 in each evaluated task, similarly, the date and time at which data were taken, also take into account the days worked and data collection schedule. On the other hand low correlations between the NASA - TLX and CWA methods were found. This may be because the sample of workers surveyed was small (13 for “tulip” and 5 for “bell” machining). Therefore, the method should be applied to a larger sample of workers and include the use of other machinery classified as AMT. It is concluded that the proposed method (CWA) is valid in terms of content and reliability, but the correlation with the NASA - TLX method is low. Researchers interested in continuing this research could focus on expanding and unifying the samples of workers collect data at a time and day for a certain job, consider the issue of shifts extended work, and the workload according to the day of the week worked.

5. References Dalmau, I. (2007). Evaluación de la carga mental en tareas de control: técnicas subjetivas y medidas de exigencia. Spain. Doctoral thesis .pp8, 14-37,88-133,299-322. De Pablo, H. C. (2004). Manual de ergonomía. Incrementar la calidad de vida en el trabajo. Spain. Editorial: Formación Alcalá. pp. 203-229,415. Díaz, E. Rubio, S. Martín, J. & Luceño, L. (2010). Estudio Psicométrico del Índice de Carga Mental NASA-TLX con una Muestra de Trabajadores Españoles. Revista de Psicología del Trabajo y de las Organizaciones Vol. 26, n. 3, 191199. 2010. DiDomenico, A. & Nussbaum. M. A. (2011). Effects of different physical workload parameters on mental workload and performance. International Journal of Industrial Ergonomics . 41. Pp.255-260.2011. Hart, S. G. & Staveland, L. E. (1988). Development of a multidimensional workload rating scale: results of empirical and theoretical research. Volumen 52, 139. 183.http://humanfactors.arc.nasa.gov/groups/TLX/downloads/NASATLXChapter.df. Recovered April 2013. 1988. Jung, H. & Jung, H. S. (2001). Establishment of overall workload assessment technique for various tasks and workplaces. International Journal of Industrial Ergonomics.28.pp341–353. 2001. Kawada, T. & Ooya, M. (2005).Workload and Health Complaints in Overtime Workers: A Survey. Archives of Medical Research. Elsever.36. pp 594–597. Llaneza J, (2002). Ergonomía y psicología aplicada. Manual para la formación del especialista. 1 ͣ edition. Spain. Editorial LEX NOVA. Pp 83, 85, 223- 298,407, 408. López Núñez, M. I. (2010). Generalización al ámbito laboral de dos instrumentos de medida subjetiva de la carga mental. Universidad Complutense de Madrid. Doctoral thesis. 91, 93, 329-335. Mehta, R., Harrop, S. and Agnew, M. J. (2009). Effects of Physical and Mental Demands on Muscle Activity of the Upper Extremity. Human Factors and Ergonomics Society.53rd Annual Meeting. 2009. Mondelo, P. R., Gregori, E., and Barrau, P. (1994). Ergonomía 1 Fundamentos. Edición Virtual:www.edicionsupc.es. Barcelona.pp145-179. Sebastián, C. M. L, Idoate, G. V. M, Llano L. M. and Almanzor, E. F. E. (2008) SOFI-SM: cuestionario para el análisis de la fatiga laboral física, mental y psíquica. Digital magazine safety and health at work. N. 2. Pág. 1-22.2008. Weiner, J. S. (1982). The measurement of human workload. Ergonomics 25, 953– 965.

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