A systematic review of comparative studies on ergonomic assessment techniques

International Journal of Industrial Ergonomics 74 (2019) 102865

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A systematic review of comparative studies on ergonomic assessment techniques Mangesh Joshi *, Vishwas Deshpande Department of Industrial Engineering, Shri Ramdeobaba College of Engineering and Management, Ramdeo Tekdi, Gitti Khadan, Katol Road, Nagpur, Maharashtra, 440013, India

A R T I C L E I N F O

A B S T R A C T

Keywords: OWAS REBA RULA Comparison Ergonomic assessment Comparative study Work-related musculoskeletal disorders

This review provides a systematic overview of the comparison of ergonomic assessment techniques’ output in variety of industrial sectors. The relevant publications have been classified into broad categories such as comparison of applied industry sector, trend analysis, ergonomic assessment techniques been compared, comparative studies between two er­ gonomic assessment techniques, frequently compared techniques, levels of Action categories used. The summary of extracted data from included papers is provided. Authors have compared the results based on observational techniques which are easy to understand and apply. Available publications related to such comparison is limited. Authors have compared and analysed the corre­ lation between the outputs of techniques but only few researchers pointed out the exact reason of variation in outputs applied in the same task. Hence, establishing applicability of each technique required. To identify the causes of variation, the sensitivity study of exposure factor-Task-posture assessment techniques is highly required. There are few techniques which are not yet compared for checking agreement or correlation, serving as a research gap. Authors have studied and published literature review specific to one technique of ergonomic assessment. Few authors have compared the outputs from various ergonomic assessment techniques in particular sector and investigated the correlation between them. No study has been carried out till date to review available literature on comparative study of comparisons made. In this paper, two research gaps have also been identified.

1. Introduction In current industrial work scenario, the problem of work-related musculoskeletal disorders (WMSDs) is very common. Musculoskeletal disorders (MSDs) are one of the major causes of illness (Storheim and Zwart, 2014) and the second most cause of disability worldwide, measured by years lived with disability (YLDs). The most frequent condition is the low back pain. WMSDs commonly include disorders of muscles, tendons, tendon sheaths, peripheral nerves, joints, bones, lig­ aments etc. The main cause of occurrence of MSDs is accumulation of repetitive stress over time. Musculoskeletal conditions affect billions of people around the world. Disability-adjusted life years (DALY) for musculoskeletal conditions increased by 61.6% between 1990 and 2016, with an increase of 19.6% between 2006 and 2016. Osteoarthritis was observed to have a 104.9% rise in DALYs (or 8.8% when age-standardized) from 1990 to 2016 (Lancet, 2017). These figures of

MSDs’ condition are in line with the expectation of author (Weinstein, 2000). The global prevalence of MSDs ranges from 14% to around 42% (Sharma R, 2012); on the other hand in India, epidemiological research indicates the community-based prevalence of nearly 20% (Sandul and Mohanty, 2018) and occupation-specific prevalence found up to 80% in various studies in India (Srivastava &, 2011) (Paul et al., 2019) (Mur­ uganantham et al., 2015) (Deepthi et al., 2015) (Sankar et al., 2012) (Majumdar et al., 2014) (Ghosh et al., 2010). It may be due to high dependency on the use of manpower due to its ease and cheap avail­ ability in developing countries like India. The generation of awareness of ergonomics risks’ causes and its prevention is necessary. Failing to this, the workers are exposed to low to very high risk depending on the in­ tensity and type of the task performed by them. As a primary require­ ment, the workstation planner/designer must consider ergonomic aspects and follow ergonomic principles while designing a workstation.

* Corresponding author. E-mail addresses: [email protected] (M. Joshi), [email protected] (V. Deshpande). https://doi.org/10.1016/j.ergon.2019.102865 Received 5 July 2019; Received in revised form 30 August 2019; Accepted 7 October 2019 Available online 17 October 2019 0169-8141/© 2019 Elsevier B.V. All rights reserved.

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

The designer must know the risk exposure factors and its effects on muscles associated with the designs. The anthropometry data, job/­ product characteristics must be taken care of well in advance to avoid occurrence of musculoskeletal disorders (MSDs). To address the issue of WMSDs, authors working in the field of human factors and/or ergonomics are often interested in finding risk involved in the work activities, postural loading, effect of vibration, use of tools, coupling, awkward postures, frequency of movements and its duration, work envelopes, design of ergonomic workstation etc. Many methods were developed to access the exposure risk related factors. Some techniques were developed to address some specific industrial sectors such agricultural or forestry sector. Some of them are generalized which can be applicable in any industrial sector. Some of the techniques such as Niosh lifting equation or MAC charts access the risks involved in material handling tasks. The techniques use the combinations of expo­ sure risk factors for its assessment. Few techniques such as Rapid Entire Body Assessment (REBA), Rapid Upper Limb Assessment (RULA), and Ovako Working posture Assessment System (OWAS) follow standard­ ized tables in which combination of head’s, back’s, arms’ and legs’ position identifies a postural score and suggests level of risk involved in the task. The techniques like Strain Index, OCRA are based on the multipliers; maximum sustainable limit of a factor is adjusted by multiplying it with a value of exposure factors which gives a score in form of an Index. Since, the factors involved in each technique and the way of calculation of score is different, authors felt the need of comparing the output/conclusion obtained by each method. The OWAS was developed by a Finnish steel company (Karhu et al., 1977). It consists of four-digit number. First number representing the back classification, second indicating Arm, third number indicating the positional number of lower limbs and the last number indicates the load handled. The four-digit code thus obtained has some meaning attached to it which is nothing but four action categories. Total 252 posture combinations are possible in OWAS (4 � 3 x 7 � 3 ¼ 252 cases). The Rapid Upper Limb Assessment method (RULA) (Lynn and Corlett, 1993) delivers an overall score based on postural loading on the whole body including particular attention to the neck, trunk, shoulders, arms and wrists. The overall score also integrates the time during which the posture is held, the force required and the repetitiveness of the move­ ment. The Rapid Entire Body Assessment method (REBA) (Hignett and McAtamney, 2000) method delivers an overall score that considers all the body parts such as trunk, legs, neck, shoulders, arms and wrists. The overall score integrates the same additional factors as RULA with an addition of quality of the hand-coupling. The OCRA index is based on the ratio between Actual Technical Actions (ATA), obtained by analyzing the task, and Reference Technical Actions (RTA). The RTA value con­ siders the frequency and repetitiveness of movements, use of force, type of posture, recovery period distribution and additional factors such as vibration and localized tissue compression. The OCRA method provides two separate indices (shoulder and elbow/wrist/hand) for each of the right and left sides of the body. EN 1005–3 is a general-purpose method that helps ergonomists assess the risk related to force application during work. The acceptable force is obtained by applying various multipliers, i.e., speed, duration and frequency of actions, to a basic capability, which is represented by the maximum capability of the 15th percentile worker. The Quick Exposure Check (QEC) is posture-based method. It combines the observer’s assessment with the worker’s answers for questionnaires. It allows assessment of MSD risk factors contributing to the back, arms, neck and upper extremities at a workstation. In addition to an overall score for the whole body (QEC General), this method provides a risk index for each targeted area such as back, shoulder-arm, wrist-hand and neck. The Job Strain Index (JSI) quantifies exposure to MSD risk factors for the hands and wrists. It provides an index that takes into account the level of perceived exertion, duration of effort as a percentage of cycle time, number of efforts, hand and wrist posture, work speed and shift length. The comparative study conducted by (Drinkaus et al., 2003)

investigated two methods (RULA and SI) for output comparison in automotive assembly plants. The results indicated that the risk assess­ ment outcomes of these two ergonomic assessment tools for the upper extremities did not correlate. The cause of deviation may be due to the different weightages given to risk exposure factors in calculating a score or a conclusion. RULA is posture based techniques whereas, SI is in­ tensity driven. There might be several causes of variation in output (Moradi et al., 2017). carried out ergonomic risk assessment of auto mechanics. The result of study showed highest prevalence of WMSDs was associated with the back and waist (Fazi et al., 2019). applied RULA method for Risks assessment at automotive manufacturing company. Findings reveals extremely high risks and the changes need to be done immediately (Mohsen et al., 2016). evaluated ergonomic physical risk factors in a truck manufacturing plant (Ojha and Vinay, 2015). evalu­ ated ergonomic risk assessment of assembly workers of Indian auto­ mobile industry by using RULA. The findings of the study showed existence of moderate to high risk of work-related musculoskeletal dis­ orders (Chakravarthy et al., 2015). applied OWAS, RULA method in an automobile assembly line. The study findings classified the activities in yellow zone i.e. of moderate risk zone (Qutubuddin et al., 2013a, b). tested RULA, REBA and QEC in bus body building unit. The findings revealed moderate to high risk of Work-related Musculoskeletal disor­ ders. The same findings were reflected in the study of (Ismail et al., 2009). The study conducted by (Jones & Kumar, 2008) in a repetitive high-risk sawmill occupation, resulted in meaningful variation in risk levels assigned with performance of the trim-saw job. In the study of author who (Shanahan et al., 2013) compared REBA, RULA, and SI. The findings revealed the ranking of rod working tasks using RULA and REBA outcome measures were similar. Similar, such studies had been conducted till date considering different available assessment techniques. The comparative study of all of such output comparisons is carried out in this paper. This study is conducted to address following major objectives. 1.1. Objective of this study The study aims at investigating: � � � �

Commonly used observational techniques by the ergonomists Correlation between the outputs of techniques compared Comments made on applicability of assessment techniques. Comment on study limitations

2. Methods This systematic review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology ((Ales­ sandro, 2009), (Moher et al., 2009)). PRISMA is a well-accepted meth­ odology for conducting and reporting systematic reviews in any engineering domain. 2.1. Inclusion criteria The review of literature was focused only on peer-reviewed journal papers. The research papers were searched and included as per inclusion criteria mentioned below: � The study was a field/controlled laboratory study conducted in any sectors. � The study addressed at least two methods for ergonomic risk inves­ tigation with considerable sample size. � Papers indexed in Scopus, SCI, and ICI etc. � Papers were written in English language. 2

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

in conference proceedings. The research publications are categorized in several classes depending on the information to be analysed. The results of 39 articles were presented either in tabular form or in the graphical form containing bar graphs, Line charts or Pie charts. The articles are arranged as per the year of publication. The maximum articles were found in the year 2013. The first paper was published in the year 2003. The graph (Fig. 2) shows the trend analysis of year-wise number of publications.

2.2. Study search and selection Fig. 1 shows the PRISMA methodology flow chart for study identi­ fication, screening, eligibility, and inclusion. This study is characterized as a systematic review of published articles from the year 1970–2019. The various combinations of keywords were used to generate maximum articles from the various sources including journal publications, book publications, study reports of national societies, conference proceedings etc. The combinations used in the searched were Comparison, Ergo­ nomic assessment, REBA, RULA, QEC, OCRA, SI, OWAS and similar possible combinations of various ergonomic assessment techniques combined using the Boolean operator “AND”, and the Boolean operator “OR”. After removing duplicates and screening, a total of 39 full text papers were identified and included in the systematic review reported in this paper.

3. Results As per the review study conducted (Takala et al., 2010), 30 obser­ vational methods are available for ergonomic risk assessment. In addi­ tion to those 30 observational techniques, NERPA (Sanchez-Lite et al., 2013), ALLA (Kong et al., 2017), HARM (Douwes & de- Kraker, 2012), SWEA (Authority-Swedish-Work-Environment, 2012), PERA (Chander and Cavatorta, 2017), WERA (Abd Rahman et al., 2011) and SES (Zare et al., 2014) are also developed. A total of 18 ergonomic assessment techniques were compared in the current reviewed literature. The meaning and abbreviations used are provided in Table 1. Author (David, 2005) provided main features and functions of assessment techniques which are summarized (Table 2). The features and functions of the techniques which were not included by (David, 2005) are also included in Table 2. In the review of 39 papers, ergonomic interventions are carried out in 11 sectors such as Food, Forestry, Automotive, manufacturing, Con­ struction etc. The highest percentage of studies (19%) is carried out in forestry work and manufacturing industries followed by 16% in auto­ motive and 14% in medical industry. The activities involved in these sectors vary from low risk level to very high-risk level. The details of sector wise comparative studies and its percentage are summarized in Fig. 3. Authors have compared Eighteen techniques of ergonomic assess­ ment and tested existence of correlation between them with the statis­ tical techniques. Table 3 shows the methods which are compared in 39 research articles. Table 4 gives number of such comparative studies conducted between two ergonomic assessment techniques. The techniques such as REBA (22%), RULA (21%), SI (12%), OWAS (11%), OCRA (10%), and QEC (7%) are found to be frequently compared by the authors in ergonomic their studies. The other methods compar­ ison percentage is shown in Fig. 4.

2.3. Data extraction Table 3 provides the techniques compared by the researchers in various articles. Table 6 provides the summary of an excel sheet pre­ pared for the data collection to extract the following required data from each comparative study: � � � � � � � � � �

Author(s) Year of publication Title Journal Application Sector Data collection methodology Software tools used for data analysis Test statistic used for establishing correlation Sample size Limitations and Conclusion of the study.

2.4. Data presentation Papers are referred from two main sources journals and conference proceedings. Out of the sixty-five papers reviewed, thirty-five useful papers were found in international journals and four papers were found

4. Discussions Table 6 provides exhaustive summary of various comparative studies carried out. It includes various details regarding method of data collection adopted, statistical tests used for correlation analysis, conclusion drawn etc. In the correlation of the outputs, authors applied different techniques in different industrial settings and came to a finish of not getting similar comparative correlation. The investigation of correlation between the outputs of various techniques was backed up by many statistical tests such as non-parametric ANOVA, non-parametric Kruskal–Wallis H-test, Wilcoxon W-test, Spearman r correlation coeffi­ cient estimation, Contrast analysis, Cohen’s linearly weighted kappa, Kolmogorov–Smirnov test etc. As per the reviewed literature, few techniques such as Participatory Ergonomics (Vink et al., 1995), a Method of Ergonomic Workplace Evaluation (Grzybowski, 2001), (Village et al., 2009), Digital Image-based Postural Assessment (Furlanetto et al., 2012) and Postural Ergonomic Risk Assessment (PERA (Chander and Cavatorta, 2017),) are not covered under comparison. The comparative study of all techniques in light to heavy duty work may provide a different direction for study. Currently it can be viewed as a research gap in literature. Each ergonomic assessment technique considers different factors or procedure to arrive at a conclusion on associated risk level. Drawing conclusion/output from the obtained scores or indices depends on

Fig. 1. Flowchart of study search and inclusion. 3

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

Fig. 2. Trend analysis of 39 studies. Table 1 Abbreviation used.

Table 2 Features and Function of Various Techniques under consideration.

SN

Abbr.

Meaning

Reference

Technique

Main Features

Functions

1

OWAS

Karhu et al. (1977)

OWAS

2

REBA RULA

4

ULRA

5 6

SI ALLA

7

OCRA

8

QEC

9

LUBA

10

NERPA

11

ART

12

HARM

13

SWEA

American Conference of Governmental Industrial Hygienists Threshold Limit Value Ergonomic work place analysis EN 1005-3 standard

ACGIH-Worldwide (2012)

Time sampling for body postures and force Categorization of body postures and force, with action levels for assessment Categorization of body postures and force, with action levels for assessment ULRA expresses the upper limb load and the risk of developing MSDs with Repetitive task indicator. Combined index of six exposure factors for work tasks Ergonomic checklist for various agricultural tasks Measures for body posture and force for repetitive tasks Exposure levels for main body regions with worker responses, and scores to guide intervention Classification based on joint angular deviation from neutral and perceived discomfort Scoring system based on individual physical conditions for reporting the final score Qualitative approach, the numerical scoring system allows users to calculate a job exposure score. Risk assessment of developing arm, neck or shoulders symptoms (pain) resulting from A complete guidebook for workstation design. A tool which considers both the peak exposure and the cumulative exposure Threshold limit values for hand activity and lifting work Questions on physical load and posture for repetitive tasks Combined index for maximum acceptable force by joints modified by various multipliers. Colour coded classification of each posture variable

Whole body posture recording and analysis Entire body assessment for dynamic tasks

3

Ovako Working posture Assessment System Rapid Entire Body Assessment Rapid Upper Limb Assessment Upper Limb Risk Assessment Strain index Agricultural Lower Limb Assessment Occupational Repetitive Actions Quick Exposure Check Loading on the Upper Body Assessment New Ergonomic Posture Assessment Assessment of Repetitive Tasks Hand Arm Riskassessment Method Model for assessment of repetitive work by the Swedish Work Environment Authority 4D Watback

14 15

4D Watback ACGIH TLV

16

EWA

17

EN 10053 standard SES

18

Scania Ergonomic Standard

REBA

Hignett & McAtamney (2000) Lynn & Corlett (1993)

RULA

Roman-Liu (2005) Roman-Liu (2007) Moore & Garg (1995) Kong et al. (2017)

ULRA

Occhipinti (1998)

SI

David et al. (2008)

ALLA

Kee & Karwowski (2001)

OCRA QEC

Sanchez-Lite et al. (2013) Ferreira et al. (2008)

LUBA

Douwes & de- Kraker (2012)

NERPA

Authority-Swedish-Work-Environment (2012)

ART

Neumann et al. (1999)

HARM SWEA 4D Watback

Ahonen et al. (1989)

ACGIH TLV

CEN (2002)

EWA

Zare et al. (2014)

EN 1005-3 standard SES

4

Upper body and limb assessment Upper body and limb assessment for repetitive tasks Assessment of risk for distal upper extremity disorders A lower limb body posture assessment tool Integrated assessment scores for various types of jobs Assessment of exposure of upper body and limb for static and dynamic tasks Assessment of postural loading on the upper body and limbs Upper extremity musculoskeletal disorders Assessment of repetitive tasks of the upper limbs Assessment in light manual tasks Guidelines for Prevention of Musculoskeletal Disorders Suitable for back assessment Exposure assessment manual work Assessment of upper extremities Exposure assessment Standard Applicable for Whole body or specific body regions

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

Fig. 3. Sectors-wise published work (%). Table 3 Techniques used in published work. SN

Ref.

Year

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 Total

Drinkaus et al. (2003) Manavakun (2004) Fernanda et al. (2006) Bao et al. (2006a, 2006b) Kee & Karwowski (2007) Jones & Kumar (2007) Jones & Kumar (2008) Spielholz et al. (2008) Jones & Kumar (2010) Motamedzade et al. (2011) Joseph et al. (2011) Chiasson et al. (2012) Wintachai & Charoenchai (2012) Qutubuddin et al., 2013a, b Qutubuddin et al., 2013a, b Shanahan et al. (2013) Roman-Liu et al. (2013) Sahu et al. (2013) Noh & Roh. (2013) Gallo & Mazzetto (2013) Garcia et al. (2013) Mukhopadhyay et al. (2014) Zare et al. (2014) Nadri et al. (2015) Kjellberg et al. (2015) Mukhopadhyay & Khan (2015) Hussain et al. (2016) Rosecrance et al. (2017) Kong et al. (2017) Upasana & Vinay. (2017) Saliha et al. (2017) Yazdanirad et al. (2018) Pal & Dhara. (2018) Kulkarni & Devalkar (2018) Sain & Makkhan (2019) Antonucci (2019) Enez & Nalbanto� glu (2019) Cremasco et al. (2019) Hellig et al. (2019)

2003 2004 2006 2006 2007 2007 2008

SN from Table 1 1

2010 2011 2011 2012 2012 2013 2013 2013 2013 2013 2013 2013 2013 2014 2014 2015 2015 2015 2016 2017 2017 2017 2017 2018 2018 2018 2019 2019 2019 2019 2019 39

2

3

Y

Y Y

Y

Y Y Y

Y Y Y

Y Y

Y

Y Y Y Y Y

Y Y Y Y Y

Y Y Y

Y Y

Y

Y Y Y

Y Y

Y

Y

Y Y Y

Y Y Y Y Y Y Y

Y

Y Y 13

Y Y Y Y

Y

26

25

6

7

8

9

10

11

12

13

14

15

Y

16

17

18

Y

Y Y Y Y

Y Y

Y Y

Y

Y

Y Y

Y

Y Y Y

Y

Y

Y

Y

Y

Y Y

Y

Y

Y

Y Y Y

Y Y

5 Y

Y

Y Y

Y

4

Y

Y

Y

Y

Y Y

Y Y

Y

Y

Y

2

Y

Y

Y

Y

Y Y

Y

Y

Y Y

Y

Y

Y

14

1

number of conclusion categories/risk levels. The problem in comparing output of two methods is two different number of conclusion categories of two methods. REBA has five action categories (Table 7) and RULA (Table 8) has only four action categories. The difference in number of conclusion categories may introduce some error in comparison of outputs. Some postures may get classified

12

Y

8

1

1

1

1

1

1

7

1

Y 2

1

into some other action level categories in comparison. In comparing two techniques, two ways were adopted by the researchers. One way was to convert action categories in same comparable base number. Many studies adopted this methodology for comparison. Other way was to use original number of categories and rank the activities as per the obtained scores from each method. After ranking, comparison was made on the 5

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

Table 4 No of Comparative Studies between two ergonomic assessment techniques. SN from Table 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Ergonomic Assessment Techniques Considered for Comparison (SN from Table 1) 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

– 11 8 0 2 1 3 2 0 0 0 0 0 0 0 0 1 0

11 – 20 0 8 1 7 6 0 0 0 0 0 0 4 1 1 0

8 20 – 1 9 1 6 4 1 1 0 0 0 0 4 1 1 1

0 0 1 – 0 0 1 0 0 0 0 0 0 0 0 0 0 0

2 8 9 0 – 0 9 2 0 0 1 1 1 0 7 1 1 0

1 1 1 0 0 – 0 0 0 0 0 0 0 0 0 0 0 0

3 7 6 1 9 0 – 3 0 0 1 1 1 1 5 1 1 0

2 6 4 0 2 0 3 – 0 0 1 1 1 1 1 1 1 0

0 0 1 0 0 0 0 0 – 1 0 0 0 0 0 0 0 0

0 0 1 0 0 0 0 0 1 – 0 0 0 0 0 0 0 0

0 0 0 0 1 0 1 1 0 0 – 1 1 0 0 0 0 0

0 0 0 0 1 0 1 1 0 0 1 – 1 0 0 0 0 0

0 0 0 0 1 0 1 1 0 0 1 1 – 0 0 0 0 0

0 0 0 0 0 0 1 1 0 0 0 0 0 – 0 0 0 0

0 4 4 0 7 0 5 1 0 0 0 0 0 0 – 1 1 0

0 1 1 0 1 0 1 1 0 0 0 0 0 0 1 – 1 0

1 1 1 0 1 0 1 1 0 0 0 0 0 0 1 1 – 0

0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 –

The highest number of comparisons were made between REBA and RULA which accounts to 20 studies, followed by OWAS- REBA in 11 studies (Table 4).

Fig. 4. % of Comparative studies.

basis of rank order given to activities. Table 5 shows various techniques used in the comparison, their original number of action categories and actual converted number of action categories. There exist different methods of ergonomic assessment, out of which researchers select method which are based on charts for steps wise score calculation, formulae to calculate index or scores or checklist which gathers data from field workers. The correlation between factual data gathered, obtained scores, and an index is mandatory for a validated technique. In the published literature, there are evidences of the

conduction of assessment techniques’ validation (Bruijn et al., 1998). Every technique had been validated. But when the output/conclusion furnished by each technique were compared, the results differ signifi­ cantly. The techniques when compared, classify postures in different categories of risk involved such as low risk, medium risk, high risk, and very high risks category. As already been discussed in the previous sections, authors convert original action categories into a common comparable base number such as 3 or 4 depending on the selected technique for comparison. This conversion may affect the normality of 6

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

Table 5 Levels of Action categories: Original and used for comparison. SN of Table 3

Technique 1

Technique 2

Name

AC

Name

AC

1 2 3 4 5 6 7 8 9 10 11

RULA OWAS REBA SI OWAS REBA REBA SI REBA REBA OCRA

4 4 5 4 4 5 5 4 5 5 4

SI REBA RULA ACGIH REBA ACGIH ACGIH ACGIH ACGIH QEC QEC

4 5 4 3 5 3 3 3 3 4 4

12

REBA

5

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

OWAS REBA REBA REBA ULRA REBA REBA OWAS OWAS OWAS RULA REBA SI OWAS OWAS SI OWAS REBA OWAS RULA OWAS REBA RULA SI

4 5 5 5 3 5 5 4 4 4 4 5 4 4 4 4 4 5 4 4 4 5 4 4

EN 1005-3 stan. REBA RULA RULA RULA OCRA RULA RULA REBA RULA REBA SES QEC ART REBA REBA OCRA REBA RULA REBA LUBA REBA RULA ULRA OCRA

37 38 39

OWAS REBA OWAS

4 5 4

a

TLV TLV TLV TLV TLV

REBA RULA EN 1005-3 standar.

Technique 3

4 5 4 4 4 4 4 4 5 4 5 3 4 3 5 5 4 5 4 5 4 5 4 3 4 5 4 4

Name

AC

Technique 4

Technique 5

Technique 6

Technique 7

Technique 8

Name

Name

Name

Name

Name

AC

AC

RULA SI SI

4 4 4

OCRA OCRA

4 4

RULA RULA

4 4

SI

4

OCRA

4

RULA

4

4D Watbak ACGIH TLV RULA QEC

3 OCRA

4

QEC

4

4 4

SI

4

SI OCRA

4 4

RULA

4

SI

4

OCRA

4

HARM RULA

3 4

SWEA SI

3 4

OCRA OCRA

4 4

RULA

4

ALLA

4

RULA NERPA RULA

4 4 4

QEC

4

QEC

4

ACGIH TLV

3

3

AC

AC

AC

Action Category Levels For comparison 3 4 4 3 4 3 3 3 3 3 3

SI

QEC

4

EWA

4

4

RULA

4

3 4 Original 4 Original 3 Original Original Original Original Original 4 3 3 Original 4 3 4 Original Original 4 Original Original – 3

ACa ACa ACa ACa ACa ACa ACa

ACa

ACa ACa ACa ACa

4 Original ACa 4

Original number of action categories (AC).

posture distribution in various risk zones. As a result, the output of technique may get shifted either towards high, medium or low risk zone. For example, in a comparison between the outputs of REBA, RULA, HARM, REBA has five action categories, RULA has four and HARM has only three categories of risk level. The action categories are converted into 3 levels to have a common base for comparison. In such comparison, the posture distribution must be normal and same for all the techniques. The posture distribution is unattended while converting the action cat­ egories forming a small but significant research gap. It is suggested to carry out a systematic study of sensitivity analysis. It is required for evaluating sensitivity of the conclusion furnished by assessment techniques. This analysis may reveal factors causing varia­ tion in output. The output sensitive body members may be different for the different techniques. OWAS is focused more on lower limbs (more categories for lower limbs) whereas REBA, RULA are more focused on upper limbs. The OWAS tends to underestimate risks, if an activity in­ volves more use of upper limbs. On the other hand, if the activity in­ volves both upper and lower limbs, REBA will be more suitable than RULA and OWAS. The ergonomic assessment techniques were designed considering a specific set of risk exposure factors. Each work element of activities may not have all the exposure factors. Hence, a technique may not be suitable for ergonomic assessment of all work elements. In the surveyed

literature, one technique was applied to every work element involved in the task without considering its’ applicability. In some cases, the output might be correct. Because of this methodology, there might be the variation in the results obtained by different methods which needs to be investigated further. The suitability/applicability of technique to the task performed must be established. Breaking lengthy activities into work elements considering exposure factor variation and the application of different techniques of assessment to individual work elements must be carefully carried out. With reference to the comparative studies conducted between two assessment techniques (Table 9), it is clear that output of majority of the studies did not correlate. The maximum 66.67% correlation was observed between OWAS and OCRA but number of studies are less. The sample size conforming the correlation is significantly less than the studies conforming non-correlation except between SI and ACGIH TLV comparison. One study confirmed correlation of results with sample size of 567 and sample size of non-conformance studies are 242. With these results, there is still a question on accuracy of these studies. 5. Conclusion and future scope The 39 included papers from various resources were examined thoroughly and efforts were focused on extracting every piece of 7

Author

Title

Journal/Conf. proceeding

Application Sector

Data Collection Method

Software analysis tools

Test Statistic Used

Sample Size

Concluding Remarks

Study Limitations

Drinkaus et al. (2003)

Comparison of ergonomic risk assessment outputs from Rapid Upper Limb Assessment and the Strain Index for tasks in automotive assembly plants A comparison of OWAS and REBA observational techniques for assessing postural loads in tree felling and processing Comparison of methods RULA and REBA for evaluation of postural stress in odontology services

Work

Automotive

On site observation

Manual analysis

kappa coefficient (K), Monotonicity gamma

244

The results of RULA and SI do not agree.

–

FEC – FORMEC – 2004 conference

Forestry

Video recording

–

–

248

Observed postural load by REBA was higher than by OWAS

–

Int. Conference on Production Research – Americas’ Region 2006

Medical

Photograph

MS Excel 7.0.

Descriptive statistics

39

–

Quantifying repetitive hand activity for epidemiological research on musculoskeletal disorders – Part I and II: comparison of different methods of measuring force level and repetitiveness A comparison of three observational techniques for assessing postural loads in industry

Ergonomics

Epidemiological research

On site observation, Self-Reports

SAS program (version 9; SAS

Descriptive statistics, One-way ANOVA Duncan’s multiple-range test Spearman rank-order correlation coefficients kappa stat.

733

1. Average RULA posture score of 5.5 with fast change. 2. Average REBA score of 7.07 indicating medium risk and change soon. Moderate to substantial agreement. The Strain Index identified more ‘hazardous’ jobs than the ACGIH HAL method

Int. J. of Occupational Safety and Ergonomic (JOSE)

Iron and steel, electronic automotive, and chemical industries, hospital.

–

–

Wilcoxon sign test

301

1. Postural stress by RULA was higher than that by REBA, OWAS. 2. Postural stress by REBA was higher than that by OWAS. Posture and exertion variable definitions were observed to significantly affect the component scores and/ or risk output of all methods. Meaningful variation in risk levels assigned between methods was observed

RULA may have some limitations in estimating postural load for unbalanced body postures

Moderate agreement was observed

–

Manavakun (2004)

Fernanda et al. (2006)

(Bao et al. (2006a, 2006b))

8 Kee & Karwowski (2007)

Comparison of ergonomic risk assessments in a repetitive high-risk sawmill occupation: Sawfiler

Int. J. of Industrial Ergonomics

Saw Mill

Motion Data with electro goniometers, Exertion data with Surface EMG Psychophysical measure - Interview

–

1. Non-parametric Kruskal–Wallis H-test 2. Wilcoxin W-test (significance level of .05)

15

Jones & Kumar (2008)

Comparison of ergonomic risk assessment output in a repetitive sawmill occupation: Trim-saw operator Reliability and validity assessment of the hand activity level threshold limit value and strain index using expert ratings of mono-task jobs

Work

Saw Mill

Electro goniometers, EMG

–

1. The non-parametric Kruskal-Wallis H test 2. The Wilcoxin W test

29

Journal of Occupational and Environmental Hygiene

Healthcare and Manufacturing

Video recording

SAS 9.1 (Cary, N.C.)

Spearman rho weighted kappa,

567

–

Wilcoxin Signed Ranks test

87

Spielholz et al. (2008)

Saw Mill

–

1. Sample size 2. Unavailability of Occupational health records to derive incidence rates. 1. Sample size 2. Occup. Health records used to derive incidence rates

(continued on next page)

International Journal of Industrial Ergonomics 74 (2019) 102865

Jones & Kumar (2007)

M. Joshi and V. Deshpande

Table 6 Summary of extracted data from included papers.

Author

Title

Journal/Conf. proceeding

Jones & Kumar (2010)

Comparison of Ergonomic Risk Assessment Output in Four Sawmill Jobs

Motamedzade et al. (2011)

Comparison of Ergonomic Risk Assessment Outputs from Rapid Entire Body Assessment and Quick Exposure Check in an Engine Oil Company Measurement Consistency Among Observational Job Analysis Methods During an Intervention Study

Int. J. of Occupational Safety and Ergonomic (JOSE) Journal of Research in Health Sciences

Joseph et al. (2011)

Application Sector

Data Collection Method

Software analysis tools

Test Statistic Used

Sample Size

On site observation and interview Spearman correlation coefficient, Wilcoxon signed-rank test and Kruskal-Wallis test

40

Methods exhibit a strong correlation in identifying risky jobs, and determining the potential risk.

Int. J. of Occupational Safety and Ergonomic (JOSE)

Food Industry

On site observation and interview

–

Spearman r correlation coefficient, Nonparametric correlation on the ordinal indices

7

–

Pearson’s correlation coefficient

567

Comparisons showed positive association between QEC and OCRA indices, and between the QEC back index and 4D Watbak. The findings show that no two methods are in perfect agreement

Pearson correlation coefficient

25

RULA and REBA shows high level of risk whereas OWAS shows high risk in few activities. The results of RULA and QEC are inline whereas results of REBA are slightly concentrated near higher side. Methods are in agreement

–

The ranking of tasks using RULA and REBA outcome measures were similar to the rank by perceived Lifting Effort In most cases, the values of the indicators obtained with OCRA and ULRA were similar. In addition, the correlation between these indicators was quite strong. 1. RULA score are on higher side than REBA in few activities

1. Sample size, 2. The single occupation assessed 3. The nature of the posture data used. Small Sample size

Wintachai & Charoenchai (2012)

The comparison of ergonomics postures assessment methods in rubber sheet production

Proceedings of the 2012 IEEE IEEM

Rubber Sheet Production

On site observation

JMP statistical software for Windows (SAS Institute Inc. version 9.0.2) Win OWAS

Qutubuddin et al., 2013a, b

Ergonomic risk assessment using postural analysis tools in a bus body building unit

Industrial Engineering Letters

Automotive

On site observation

–

Scatter Plot

38

Qutubuddin et al., 2013a, b

An ergonomic study of work-related MSDs risks in Indian Saw Mills A comparison of RULA, REBA and Strain Index to four psychophysical scales in the assessment of nonfixed work Comparison of risk assessment procedures used in OCRA and ULRA methods

J. of Mech. and Civil Engineering

Saw Mill

On site observation

–

–

110

Work

Construction

On site observation

–

Contrast analysis One way ANOVA

25

Ergonomics

Electronic

Video Recording, electro goniometers dynamometer (ZPC system from JBA, Poland).

–

Non-parametric Spearman correlation

18

Int. J. of Occupational Safety and Ergonomic (JOSE)

Manufacturing

On site observations

–

Chi Square, ANOVA, Descriptive statistics

130

–

–

–

–

(continued on next page)

International Journal of Industrial Ergonomics 74 (2019) 102865

On site observation and interview

9

Manufacturing, Forestry, Food

A comparative ergonomics postural assessment of potters and sculptors in the unorganized sector in West Bengal, India

1. The small sample size 2. Inclusion of jobs which are at risk only. Relationships between each evaluation method and the injury data were unknown.

SPSS Version 13.0

Int. J. of Industrial Ergonomics

Sahu et al. (2013)

Limited agreement was observed

On site observation

Comparing the results of eight methods used to evaluate risk factors associated with musculoskeletal disorders

Roman-Liu et al. (2013)

Study Limitations

Automotive

Chiasson et al. (2012)

Shanahan et al. (2013)

Concluding Remarks

M. Joshi and V. Deshpande

Table 6 (continued )

Author

Title

Journal/Conf. proceeding

Application Sector

Data Collection Method

Software analysis tools

Test Statistic Used

Sample Size

Concluding Remarks

Study Limitations

Noh & Roh. (2013)

Approach of Industrial Physical Therapy to Assessment of the Musculoskeletal System and Ergonomic Risk Factors of the Dental Hygienist Ergonomic analysis for the assessment of the risk of work-related musculoskeletal disorder in forestry operations Working postures of dental students: ergonomic analysis using OWAS and rapid upper limb assessment. Ergonomic risk factors in bicycle repairing units at Jabalpur

J. Phys. Ther. Sci

Medical

Video Recording

–

–

3

RULA slightly over estimated postures. Value of SI in not in line with the scores of RULA, REBA for X ray activity

–

Journal of Agricultural Engineering

Forestry

Video recording

KINOVEA,

–

18

All approaches presented a good feasibility in their application

–

Med Lav.

Dentistry

Photography

Kappa statistics

283

No agreement was observed

–

Work

Automotive

photograph and video

–

–

–

–

Zare et al. (2014)

Development of a Biomechanical Method for Ergonomic Evaluation: Comparison with Observational Methods

International Journal of Bioengineering and Life Sciences

Automotive

Data logger, Video Recorder, Sensors (Inclinometers, Accelerometers, and Goniometer

Excel, MATLAB

–

–

Nadri et al. (2015)

Comparison of ergonomic risk assessment results from Quick Exposure Check and Rapid Entire Body Assessment in an anodizing industry of Tehran, Iran

JOHE

Chemical

Video and Photograph

The kappa and gamma scores One-way ANOVA

82

Kjellberg et al. (2015)

Comparisons of six observational methods for risk assessment of repetitive work - results from a consensus assessment The evaluation of ergonomic risk factors among meat cutters working in Jabalpur, India

Proceedings 19th Triennial Congress of the IEA,

Service

Video Recording

Data analysis was performed using SPSS software (version 16, SPSS Inc., Chicago, IL, USA). –

Cohen’s linearly weighted kappa

10

1. REBA, RULA, OCRA scores were very high. 2. SI score was less in painting task. 1. Findings showed that RULA & SES methods were in agreement with the results of biomechanical methods except for neck and wrist postures. The risk assessment outcomes do not agree. Thus, there is no possibility of applying them interchangeably for postural risk assessment, at least not in this industry. No two methods were in perfect agreement.

International Journal of Occupational and Environ. Health

Food

Direct observation, Questionnaire and interview technique

–

–

15

–

Using Ergonomic Risk Assessment Methods for

Human Factors and Ergonomics

Furniture Manufacturing

video recording

–

–

12

1. OWAS revealed that none of the postures were within the safe limit. 2. REBA, RULA, OCRA scores were also high for considerable number of activities. 3. SI score is Very high only for Cutting.

Gallo & Mazzetto (2013)

Garcia et al. (2013)

Mukhopadhyay et al. (2014)

10 Hussain et al. (2016)

–

Small sample size

–

– (continued on next page)

International Journal of Industrial Ergonomics 74 (2019) 102865

Mukhopadhyay & Khan (2015)

M. Joshi and V. Deshpande

Table 6 (continued )

11

Determination of work postures with different ergonomic risk assessment methods in forest nurseries Comparing the Effectiveness of Three Ergonomic Risk Assessment Methods—RULA, LUBA, and NERPA—to Predict the Upper Extremity Musculoskeletal Disorders Identifying musculoskeletal issues and associated risk factors among clay brick kiln workers

Saliha et al. (2017)

Sain & Makkhan (2019)

Kulkarni & Devalkar (2018)

Pal & Dhara. (2018)

Work Related Musculoskeletal Disorders and Postural Stress of the Women Cultivators Engaged in Uprooting Job of Rice Cultivation Postural analysis of building construction workers using ergonomics

Work posture assessment of tailors by RULA and REBA analysis

(Upasana and Vinay., 2017)

Yazdanirad et al. (2018)

Comparisons of Ergonomic Evaluation Tools (ALLA, RULA, REBA and OWAS) for Farm Work

Kong et al. (2017)

International Journal of Construction Management

Indian J Occup. Environ Med

Industrial Health

Indian J Occup. Environ. Med

International Journal of Science, Environment and Technology Fresenius Environmental Bulletin

Int. J. of Occupational Safety and Ergonomic (JOSE)

Int. J. of Industrial Ergonomics

in Mfg.& Service Industries

Designing Inclusive Work Practices: A Case Study

Risk assessment of cheese processing tasks using the Strain Index and OCRA Checklist

Journal/Conf. proceeding

Title

Rosecrance et al. (2017)

Author

Table 6 (continued )

Construction

Agriculture

Brick kiln

Medical, Automotive

Forest nurseries

Garment Manufacturing

Agriculture

Food Industry

Application Sector

Video Recording

Photographs and Discussion

Observation and Discussion

Observation and Discussion

Video recording

Observation and Discussion

–

Video Recording and Discussion

Data Collection Method

–

IBM SPSS version 20

IBM SPSS software (version 22)

SPSS version 16.

Ergo Fellow (Version-2.0) software

–

All statistical analyses were completed using SAS/STAT software (SAS Institute, Cary, NC) version 9.3 (2012). –

Software analysis tools

–

1. Student’s t-test 2. Chi-square test

Logistic regression

1. Kolmogorov–Smirnov test 2. Spearman’s correlation test 3. Wilcoxon test

–

–

Hit rate, quadratic weighted κ, one-way analysis of variance, and ttest analyses

Descriptive statistics, Bowker’s test of symmetry, Spearman’s rank-order correlation coefficient (rs), and Cohen’s weighted kappa coefficient (k).

Test Statistic Used

6

112

There are differences in the RULA and REBA scores.

Postural analysis showed that kiln workers are exposed to very high risks in spading and mould filling tasks which is given by RULA and REBA OWAS underestimated risk level than REBA, RULA, QEC

Low-risk levels in NERPA, medium-risk levels in LUBA, and high-risk levels in RULA are evaluated better.

210

154

RULA score was highest followed by QEC, OWAS, REBA

ALLA gave different results than OWAS, REBA, RULA which author claims in line with 16 Ergo Experts’ assessment RULA overestimated the posture than REBA

OWAS predicts fewer severe risk postures as compared with REBA. Strain Index and OCRA Checklist yielded fair to moderate agreement, but not identical.

Concluding Remarks

175

60

196

21

Sample Size

(continued on next page)

–

–

The present study was limited to the Rajasthan state of India only, other regions can be included in future studies

Lack of investigation of tasks applying to high postural load

–

–

–

The results may not be applicable to job exposures of other manufacturing tasks, especially those that are highly variable and involve multiple task functions

Study Limitations

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

M. Joshi and V. Deshpande

International Journal of Industrial Ergonomics 74 (2019) 102865

– Two investigated methods OWAS and EN 1005–4 showed a variance of validity ranging from small to large regarding the assessment of static working postures. IBM SPSS Statistics 25 surface electromyography device (Desktop DTS Receiver, Noraxon, Scottsdale, AZ, USA) Lab Exp. Work

Kinovea software Video Recording and Photography Forestry Int. J. of Environ. Research and Public Health

REBA score

Conclusion/Risk level

1 2 3 4 5

1 2–3 4–7 8–10 ≥ 11

Negligible risk Low risk, change may be needed Medium risk. Further investigate. Change soon. High risk. Investigate and implement change Very high risk. Implement change

Action Category

RULA score

Conclusion

1 2 3 4

1–2 3–4 5–6 6–7

Acceptable posture Further investigate, change may be needed Further investigate. Change soon. Investigate and implement change

Table 9 Studies in perfect agreement (%). Comparison between

No of studies

Number of Study Results Correlated

Avg. Sample SizeCorrelated

Avg. Sample Size-No Correlation

Study results Correlated (%)

OWAS REBA OWAS RULA OWAS - SI OWAS OCRA REBA RULA REBA - SI REBA OCRA REBA - QEC REBA ACGIH TLV RULA - SI RULA OCRA RULA - QEC RULA ACGIH TLV SI - OCRA SI - QEC SI - ACGIH TLV OCRA- QEC OCRA ACGIH TLV

11

4

19

595

36.36

8

3

20

213

37.50

2 3

1 2

NA 17

15 NA

50.00 66.67

20

5

44

117

25.00

8 7

3 3

20 17

140 175

37.50 42.86

6 4

2 0

39 –

234 175

33.33 0.00

9 6

3 2

20 15

158 175

33.33 33.33

4 4

1 0

38 –

285 175

25.00 0.00

9 2 7

3 0 1

18 – 567

122 289 242

33.33 0.00 14.29

3 5

1 0

7 –

289 144

33.33 0.00

information for comparison. Authors compared the results of observa­ tional techniques which are easy to understand and apply. The number of available publication related to such comparison is limited. Applica­ tion of ergonomic assessment techniques has been done in variety of sectors and comparison of outputs of each method is made. Few methods categorized one posture at high risk and other method categorized the same posture at medium risk. The cause of the deviation is still hidden and unidentified. The correlation was established between the compared methods supported by statistical tests. The result of compar­ ative studies carried out by authors demonstrated the variation in out­ comes in most of the cases. In the literature surveyed, few attempts have been made to identify the causes of variation. On the other hand, results suggested to use more than one technique for postural evaluation. Similarly, establishing

Hellig et al. (2019)

Risk Assessment for Musculoskeletal Disorders in Forestry: A Comparison between RULA and REBA in the Manual Feeding of a Wood-Chipper Investigation of observational methods assessing workload of static working postures based on surface electromyography Cremasco et al. (2019)

Enez & Nalbanto� glu (2019)

Action Category

Table 8 RULA scoring table.

Spearman rank correlation coefficients

24

– RULA method is found more suitable than the REBA method

3119 Forestry Int. J. of Industrial Ergonomics

Photography, Video recording, On site observation

–

1. One-sample Kolmogorov–Smirnov 2. Kruskal–Wallis H test as a nonparametric test, 3. Man–Whitney U test –

1

–

–

applying the methods in hypothetical scenarios to reveal differences emerging when the boundary conditions are varied In the study, the results of OWAS differed statistically from REBA. 21

Comparative analysis of three methods of risk assessment for repetitive movements of the upper limbs: OCRA index, ACGIH (TLV), and strain index Comparison of ergonomic risk assessment outputs from OWAS and REBA in forestry timber harvesting Antonucci (2019)

Int. J. of Industrial Ergonomics

–

Hypothetical data

–

–

Concluding Remarks Title Author

Table 6 (continued )

Journal/Conf. proceeding

Application Sector

Data Collection Method

Software analysis tools

Test Statistic Used

Sample Size

Study Limitations

Table 7 REBA scoring table.

12

International Journal of Industrial Ergonomics 74 (2019) 102865

M. Joshi and V. Deshpande

applicability of techniques in particular sector is missing. There are few techniques which are not yet compared for checking agreement or correlation, serving as a research gap.

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