Session No. 521

Selecting Ergonomic Analysis Tools

Paul S. Adams, Ph.D, P.E., CSP, CPE

Senior Consultant Applied Safety & Ergonomics, Inc.

Ann Arbor, Michigan

Introduction Musculoskeletal disorders, or MSDs, account for a significant portion of the injuries/illnesses

experienced by most work organizations. Ranging from back strains to carpal tunnel syndrome, it

is common for employers to find MSDs accounting for 40% or more of their injury cases, and 60%

of their workers compensation costs. Safety professionals, engineers, and human resource

managers have turned to the science of ergonomics to understand and address work conditions that

increase the risk of MSDs. Manufacturing managers are also looking to ergonomics for

applications that improve efficiency and productivity.

Preventing MSDs and increasing productivity generally requires a two-pronged application of

ergonomics: a reactive program of identifying, analyzing and correcting “problem jobs”, and a

proactive process of integrating ergonomics into process and product design. Highly trained and

skilled ergonomists can often identify and solve problems “on the fly”, but the “expert” approach

often lacks employee involvement, a key ingredient for success. Many organizations do not have

the benefit of having internal ergonomists readily available, so they look to their safety

professionals or outside consultants for these specialized services.

Whether ergonomics is handled by plant teams, safety professionals, or trained ergonomists, there

is often a need for systematic assessments to identify and quantify injury risk and opportunity

potential. Ergonomic analysis tools are designed to meet these needs. In general, ergonomic tools

attempt to answer three fundamental questions:

1. Is there a problem or opportunity with a task?

2. If a problem or opportunity exists, what is the nature of the risk or inefficiency?

3. How much injury risk or potential productivity benefit exists?

Ergonomic tools can also be used to assess intervention success post hoc.

One issue facing many safety professionals and ergonomists is selecting ergonomic analysis tools

that will enable them and their organizations to answer the fundamental questions above. Selecting

ergonomic tools warrants careful study and consideration. Proper selection can yield relevant data,

widespread use by employee ergonomic teams, and process credibility with managers. Choosing

inappropriate tools can frustrate teams, confuse managers, and yield data that do not adequately

assess risk. This can compromise the entire ergonomics process and its credibility.

The intent of the presentation is to provide participants with:

An understanding of the key factors to consider when selecting ergonomic analysis tools

A process for systematically considering these factors and comparing tools

A summary of the capabilities and applicability of several commonly used analysis tools

Factors to Consider When Selecting Analysis Tools Selecting ergonomic analysis tools requires an understanding of the users or analysts, the types of

tasks being analyzed, the characteristics of the tools themselves, and the intended use of collected

data. The key considerations within each of these four areas are summarized below.

Analyst Characteristics Knowledge of ergonomics- Analysts exposed to college coursework in ergonomics often have

sufficient knowledge of the field to readily identify risk factors and appreciate the limitations of

various tools. These are important prerequisites for effectively and consistently applying some of

the more academic tools, such as the Strain Index, the University of Michigan’s 3DSSPP, the

Lumbar Motion Monitor (LMM), and the Garg Metabolic Energy Expenditure Model, and perhaps

even the NIOSH Revised Lifting Equation. Plant ergonomic team members with limited training

can be trained to use such tools, but the learning curve is flatter and inter-observer reliability is

likely to be higher than when applied by skilled ergonomists.

Ability to maintain application skills- Full time ergonomists routinely identify risk factors and

assess their relative importance. Familiarity with ergonomic literature and job analysis practice

enable ergonomists to maintain skills, whereas those who are less accustomed to collecting data

find it more difficult to achieve and maintain proficiency. For analysts in the latter category,

simpler tools are more apt to be applied correctly.

Frequency of tool use – Similar to the ability to maintain application skills, frequency of tool use

should be a strong consideration, especially for plant ergonomics teams. If tools are frequently

used, analysts will remember how they can be applied between applications, and the time required

to use the tool will remain fairly constant. If a tool is complex and difficult to learn due to

complicated steps in application, there may be a substantial relearning period between each

subsequent application. This tends to discourage use, and can compromise reliability.

Role in decision making regarding interventions – If the analyst knows what decisions will need to

be answered from the data collected, then a tool can be selected to provide that information without

wasting time collecting data that will not be used. Analysts who are not involved in selecting

interventions are often less able to predict what information will be needed. As a result, these latter

analysts may need to collect a broad, less specific data set in order to cover the bases.

Time available to conduct analyses – One of the biggest complaints from persons unfamiliar with

ergonomic analysis tools is the amount of time required to collect data. While computer based

tools such as the 3DSSPP and the LMM expedite data collection for lifting jobs, these tools are not

well-suited for novice analysts. For paper based tools, more time spent collecting data typically

equates to more specific information resulting. For example, if time to analyze a job involving the

upper extremities is limited, analysts may need to choose tools that provide a general assessment of

risk, such as Hand Activity Level (HAL), rather than a more detailed tool like the Strain Index (SI).

Task Attributes Existing job versus task being designed – A typical method for analyzing jobs is to videotape a few

workers performing the tasks, directly measure forces and distances, and then collect posture and

frequency data from the videotape. If tasks are still in the design phase, then simulated data must

be used. Tools with simulation capability, such as the University of Michigan’s 3DSSPP, tend to

be much more useful for initial design than tools that rely on actual measurements.

Body region affected – Many tools are only designed to address one body region or type of

ergonomic stressor. For example, the NIOSH Revised Lifting Equation (NIOSH RLE) only helps

analyze lifting and lowering as it pertains to stress on the low back.

Work activity level – Many of the more academically oriented tools, such as the NIOSH RLE, have

application constraints that must be either violated or ignored when analyzing complex tasks, such

as lifting while kneeling or seated.

Ergonomic risk factors involved – Some tools place a higher emphasis on posture, while others

emphasize repetition and force. It is important to select tools that capture the predominant risk

factors on a job. For example, Rapid Entire Body Assessment (REBA) is a useful tool when

analyzing jobs with awkward postures, but poorly suited for analyzing jobs with high strength or

energy expenditure demands.

Task variability and frequency – Actual production jobs often vary widely in the movements

workers use in performing them, and may also vary widely in frequency and intensity. Tools that

rely on a “snapshot” approach can yield distorted results if the sample size is not increased to

account for this variability.

Worker control of workspace, movements, and pace – Work on an assembly line is often very

regimented, resulting in consistent movement patterns and pacing. Complex tasks with long cycle

times tend to provide workers with much greater flexibility, and movement patterns, pace, and even

workstation layout may vary widely both among and within workers. Tools relying on a snapshot

approach, such as the NIOSH RLE, can analyze one small component of complex tasks, but cannot

provide a global assessment of risk that may be provided by a more general checklist or computer

enhanced data aggregation tool.

Tool Capabilities and Limitations Research underlying tool development – Analysis tools published in academic research journals

tend to be based on meticulous laboratory studies with careful control over potentially confounding

variables. These tools are arguably more defensible for studying risk factors that fall within the

limits followed in the original research. Commercial tools tend to take a more global approach and

are typically much more flexible, but they also tend to lack validating research. If the results of an

analysis are likely to be challenged, then choosing tools based on scientific rigor may be required.

Body parts and physiological functions analyzed – Tools such as the Strain Index (SI) and Garg

Metabolic Energy Expenditure Prediction Model (MEEP) are designed to analyze specific body

parts or task attributes (upper extremity cumulative trauma risk and whole body energy

expenditure, respectively). Neither of these example tools would be of much use in analyzing

occasional heavy lifting.

Risk factors analyzed – Most research based tools either discount or constrain their applicability

when secondary risk factors may be involved, even though such factors may contribute

significantly to actual injury risk. For example, the NIOSH RLE considers force, frequency,

posture and coupling, but cannot be properly applied if the worker is seated, kneeling, or standing

on an unstable surface.

Sensitivity / resolution – Checklists tend to be most useful in identifying the presence of risk

factors, but provide little guidance in determining relative risk. Further, the Strain Index provides

relatively good sensitivity to variations in upper extremity stressors, whereas the Hand Activity

Level (HAL) yields significantly less resolution.

Repeatability / inter-observer reliability – The ideal tool is one that yields the same results

independent of the analyst or subject. Inter-observer variance has been a common complaint for

some of the more rigorous research based tools, such as the Strain Index. Extensive training can

enhance reliability, but analysts outside of the research community may find it difficult to acquire

and maintain skill sufficient to achieve reliable results.

Usability – To achieve widespread use by “occasional” analysts, a tool must be easily learned and

remembered, and relatively simple and quick to use. Commercial tools place a premium on

usability, arguably at the expense of academic rigor. For plant ergonomic teams, HAL is much

more usable than SI, even though the information resulting from the analysis is less specific and

perhaps less useful.

Learning curve / complexity – Closely related to usability is the time required to become

adequately proficient in tool use. Field practitioners such as members of plant ergonomic teams

may be expected to learn a limited set of tools in a single day of training. Tools such as SI, NIOSH

RLE, 3DSSPP, and LMM typically require training sessions of 4 or more hours each.

Specificity – As mentioned above, some tools do a better job of analyzing specific issues, such as

posture, than others. If it is obvious that posture is the primary risk factor, then selecting a posture

analysis tool will likely yield more value than a tool that incorporates posture with several other

risk factors.

Measurement artifacts and intrusiveness – Collecting posture data off videotape is relatively

unobtrusive and generally allows the worker to perform tasks without modifying natural movement

patterns. The LMM attaches an exoskeleton to a worker, which can substantially alter natural

movement patterns and posture selection, especially if the work is performed in a congested area.

Anything that changes natural movement patterns and postures introduces measurement artifacts

that can compromise the validity of the results.

Computerization – Some tools are computer-based models (e.g., 3DSSPP and LMM) and require

the analyst to have technical competency. Simple checklists do not depend on this skill.

Cost – Commercial job analysis tools have their appeal in their global applicability and usability,

but they also cost money either in license fees or availability only through expensive training

courses. Software tools such as 3DSSPP and LMM also have a purchase price that may be a

barrier to some users.

Data Application Screening to identify problem jobs and risk factors – Many job analysis tools assume that the

analyst has already properly identified ergonomic risk factors present on the job and offer a means

for quantifying or assessing the relative level of those factors. Checklists and commercial tools

tend to provide some assistance for the novice in identifying risk factors and screening problem

jobs.

Quantification of risk – Quantifying risk is a controversial subject and has been the subject of much

academic debate. A basic assumption is that high risk factor values will equate to increased injury

experience, but while such a relationship may be statistically significant, it has generally not

achieved predictability, or even practical significance in many cases. Many tools quantify

exposures and risk factor levels, but validation of actual risk is elusive. Commercial tools that

claim to find an X% less risk on one job versus another exceed sound science.

Acceptability of subjective data – Engineers accustomed to hard numbers and data find it difficult

to accept the subjective, qualitative findings of many ergonomic studies. Commercial ergonomic

tools that incorporate numeric values for risk tend to achieve face validity from engineers and may

be appealing, but confidence in such data is frequently misguided. Tools such as the NIOSH RLE

provide useful quantitative data, but users need to appreciate the limitations of the underlying

model.

Research vs. “general impression” – If the ultimate user of an analysis is a business leader, it may

be appropriate for a tool to provide a general idea of relative risk; data collection and analysis

meeting academic rigor may be viewed as a waste of precious time. Conversely, a tool used for

research purposes must have a high level of repeatability and underlying scientific rigor.

Credibility requirements – The level of credibility ascribed to an ergonomics study is highly

dependent on the expectations and knowledge of the ultimate user. While some managers may be

satisfied with the face validity of commercial tools and be well-served by them, others may

demand scientific validity that will hold up in court. The latter would require the analyst to choose

validated assessment tools based squarely on academic studies, rather than simple ergonomic

principles.

Simulation and use to assess hypothetical solutions – If the user needs to compare competing

solutions or design strategies, then it is important to select tools that facilitate answering the “what

if” questions. The NIOSH RLE and 3DSSPP are examples of tools that are especially useful for

such applications.

Common Ergonomics Analysis Tools Table 1 provides a very brief description for several of the most commonly used ergonomic

analysis tools, as well as source information. These tools include:

- NIOSH RLE (Revised Lifting Equation)

- RULA (Rapid Upper Limb Analysis)

- REBA (Rapid Entire Body Assessment)

- Strain Index

- Snook & Ciriello Tables (aka. Liberty Mutual Tables or simply Snook Tables)

- HAL (Hand Activity Level)

- ACGIH Hand/Arm (Segmental) Vibration TLV’s

- Univ. of Michigan’s 3DSSPP (3-Dimensional Static Strength Prediction Program)

- Garg Model (Metabolic Energy Expenditure Prediction Program)

- LMM (Lumbar Motion Monitor System)

- Washington State Proposed OSHA Standard Appendix B

- GM-UAW Risk Factor Checklist

- Humantech BRIEF Survey

- Auburn Engineers ERGO Job Analyzer

ANALYSIS

TOOL

REFERENCE / SOURCE RISK FACTORS

EVALUATED

AREAS OF BODY

ADDRESSED

SAMPLE APPLICATIONS

NIOSH RLE Applications Manual for the Revised NIOSH

Lifting Equation, Waters, T.R., Putz-

Anderson, V., Garg, A., National Institute for

Occupational Safety and Health, January

1994 (DHHS, NIOSH Publication No. 94-

110).

Available from:

U.S. Department of Commerce Technology

Administration, National Technical

Information Service (NTIS)

5285 Port Royal Road

Springfield, VA 22161

NTIS Publication No. PB94-176930)

Phone: (703) 487-4650

http://www.cdc.gov/niosh/

For a web version of this tool:

www.industrialhygiene.com/calc/lift.html.

- Repetition

- Force

- Awkward postures

- Lower back - Manual handling involving lifting

weights > 10 lb.

- Palletizing / de-palletizing

- Package handling

RULA “RULA: A Survey Method for the

Investigation of Work-Related Upper Limb

Disorders,” McAtamney, L. and Corlett,

E.N., Applied Ergonomics, 1993, 24(2): 91-

99.

Available from:

Elsevier Science Regional Sales Office

Customer Support Department

P.O. Box 945

New York, N.Y. 10159

Phone: (212) 633-3730

www.elsevier.com

- Repetition

- Force

- Awkward postures

- Wrists

- Forearms

- Elbows

- Shoulders

- Neck

- Trunk

- Assembly work

- Sewing

- Meatpacking

- Grocery cashier

- Dentists and dental technicians

REBA “Rapid Entire Body Assessment (REBA),”

Hignett, S. and McAtamney, L., Applied

Ergonomics, 2000, 31: 201-205.

Available from:

Elsevier Science Regional Sales Office

Customer Support Department

P.O. Box 945

New York, N.Y. 10159

Phone: (212) 633-3730

www.elsevier.com

- Repetition

- Force

- Awkward postures

- Wrists

- Forearms

- Elbows

- Neck

- Trunk

- Back

- Legs

- Knees

- Patient lifting & transfer

- Nurses

- Janitors

- Grocery warehouse

- Telephone operators

- Dentists and dental technicians

- Ultrasound technicians

- Production workers

Strain Index “The Strain Index: A Proposed Method to

Analyze Jobs for Risk of Distal Upper

Extremity Disorders.” Moore, J.S., and

Garg, A., 1995; AIHA Journal, 56(5): 443-

458.

Available from:

American Industrial Hygienists Association

2700 Prosperity Ave., Suite 250

Fairfax, VA 22031

Phone: (703) 849-8888

www.aiha.org/

Web version: http://sg-

www.satx.disa.mil/hscoemo/tools/strain.htm

- Repetition

- Force

- Awkward postures

- Hands

- Wrists

- Small parts assembly

- Meatpacking

- Sewing

- Packaging

- Keyboarding

- Jobs involving highly repetitive

hand motions

Snook & Ciriello

Tables

“The Design of Manual Handling Tasks:

Revised Tables of Maximum Acceptable

Weights and Forces,” Snook, S.H., and

Ciriello, V.M., Ergonomics, 1991, 34(9):

1197-1213.

Available from:

Taylor & Francis Inc.

325 Chestnut Street, Suite 800

Philadelphia, PA 19106, USA

Phone: (800) 354-1420

www.tandf.co.uk/journals/

- Repetition

- Force

- Awkward postures

- Back

- Trunk

- Shoulders

- Legs

- Food service

- Janitorial

- Package delivery

- Garbage collection

- Nursing homes

- Jobs involving pushing/pulling

carts

- Jobs involving carrying objects

Hand Activity Level 2000 Threshold Limit Values and Biological

Exposure Indices. American Conference of

Governmental Industrial Hygienists

(ACGIH), ISBN: 1-882417-36-4.

Available from:

American Conference of Governmental

Industrial Hygienists, Inc.

1330 Kemper Meadow Dr., Suite 600

Cincinnati, OH 45240

Phone: (513) 742-2020

www.acgih.org/

See also:

www.hsc.usf.edu/~tbernard/HollowHills/HA

L_TLV_M14.pdf

- Repetition

- Force

- Hands

- Wrists

- Small parts assembly

- Meatpacking

- Sewing

- Packaging

- Keyboarding

- Jobs involving repetitive or

frequent hand motions

ACGIH Hand/Arm

Vibration TLV

1998 Threshold Limit Values for Physical

Agents in the Work Environment in 1998

TLVs and BEIs Threshold Limit Values for

Chemical Substances and Physical Agents

Biological Exposure Indices, pp. 109-131,

American Conference of Governmental

Industrial Hygienists.

Available from:

American Conference of Governmental

Industrial Hygienists, Inc.

1330 Kemper Meadow Dr., Suite 600

Cincinnati, OH 45240

Phone: (513) 742-2020

www.acgih.org/

- Vibration - Hands

- Arms

- Shoulders

- Grinding

- Chipping

- Drilling

- Sawing

- Chainsaw operation

- Production work using vibrating or

powered hand tools

U of M 3DSSPP University of Michigan – Center for

Ergonomics

1205 Beal Avenue

Ann Arbor, MI 48109-2117

(734) 763-2243

Available from:

University of Michigan - Office of

Technology Transfer

2071 Wolverine Tower

3003 South State Street

Ann Arbor, MI 48109-1280

Phone: (734) 763-0614

http://www.techtransfer.umich.edu/

- Force

- Postures

- Stability

- Back

- Trunk

- Shoulders

- Hips

- Knees

- Arms

- Lifting objects

- Manual materials handling

- Pushing/pulling carts

- Production work

- Non-routine tasks

- Maintenance

- Workstation planning & simulation

Garg Metabolic

Energy Expenditure

Prediction Model

Garg, A., Chaffin, D.B., and Herrin, G.D.,

"Prediction of Metabolic Rates for

Manual Materials Handling Jobs." American

Industrial Hygiene Association Journal,

1978, Vol. 39, No. 8, p. 661-674.

Available from:

University of Michigan - Office of

Technology Transfer

2071 Wolverine Tower

3003 South State Street

Ann Arbor, MI 48109-1280

Phone: (734) 763-0614

http://www.techtransfer.umich.edu/

- Physiological stress /

energy expenditure

- Whole body fatigue - Production work

- Palletizing

- Carrying objects

- Manual material handling

- Assembly work

LMM Marras, W.S., Allread, W.G., and Ried, R.G.,

(1999), "Occupational Low Back Disorder

Risk Assessment Using the Lumbar Motion

Monitor." in Karwowski, W., and Marras,

W.S., eds., The Occupational Ergonomics

Handbook. CRC Press: Boca Raton, FL,

1075-1100.

Available from: NexGen Ergonomics Inc. 6600 Trans Canada Highway

Suite 750

Pointe Claire (Montreal), Quebec

Canada

H9R 4S2Phone: (514) 685-8593 salesinfo@nexgenergo.com

- Force

- Postures

- Movement speed

- Back

- Trunk

- Manual materials handling

- Production work

- Maintenance

- Assembly work

Washington State

Appendix B

WAC 296-62-05174, “Appendix B: Criteria

for analyzing and reducing WMSD hazards

for employers who choose the Specific

Performance Approach,” Washington State

Department of Labor and Industries, May

2000.

Available from:

Washington Dept. of Labor and Industries

PO Box 44001

Olympia, Washington 98504

Phone: (360) 902-4200

www.lni.wa.gov/wisha/

- Repetition

- Force

- Awkward postures

- Contact stress

- Vibration

- Hands

- Wrists

- Forearms

- Elbows

- Shoulders

- Neck

- Trunk

- Back

- Legs

- Knees

- Assembly work

- Production work

- Meatpacking

- Maintenance

- Sewing

- Keyboarding

- Small parts assembly

- Patient lifting

- Package handling and delivery

- Garbage collection

- Regular use of vibrating hand tools

GM-UAW Checklist “UAW-GM Ergonomics Risk Factor

Checklist RFC2,” United Auto Workers –

General Motors Center for Human

Resources, Health and Safety Center, 1998.

Available from:

UAW-GM Center for Human Resources

Health and Safety Center

1030 Doris Road

Auburn Hills, MI 48326

- Repetition

- Force

- Awkward postures

- Contact stress

- Vibration

- Hands

- Wrists

- Forearms

- Elbows

- Shoulders

- Neck

- Trunk

- Back

- Legs

- Knees

- Assembly work

- Production work

- Small parts assembly

Humantech BRIEF

Survey

“Chapter 4: Evaluating Ergonomic Risk

Factors,” in Applied Industrial Ergonomics,

Version 4.0. Humantech, Inc. 2003.

Available from:

Humantech, Inc.

1161 Oak Valley Drive

Ann Arbor, MI 48108

Phone: (734) 663-6707

www.humantech.com

- Repetition

- Duration

- Force

- Awkward postures

- Vibration

- Low temperatures

- Soft tissue

compression

- Impact stress

- Hands

- Wrists

- Elbows

- Shoulders

- Neck

- Back

- Legs

- Production work

- Assembly work

- Maintenance

- Keyboarding

- Package handling

- Using tools

Auburn Engineers

ERGO Job Analyzer

Available from:

Auburn Engineers, Inc.

PO Drawer 3038

132 N. Gay Street, Suite 210

Auburn, AL 36831

Phone: (334) 826-8600

www.auburnengineers.com

- Repetition

- Duration

- Force

- Awkward postures

- Vibration

- Low temperatures

- Soft tissue

compression

- Impact stress

- Energy Expenditure

- Hands

- Wrists

- Elbows

- Shoulders

- Neck

- Back

- Legs

- Production work

- Assembly work

- Maintenance

- Keyboarding

- Package handling

- Using tools

Table 1: Summary of applicability of common ergonomic job analysis tools, along with resource information.

A Process for Comparing Tools Given the criteria discussed earlier, comparison matrices can be developed to help with the

selection process. The parameters used in these matrices should be tailored to the needs of the

organization. An example of a simple comparative analysis used to select tools for use by a plant

ergonomics team is presented below. Time and space do not allow a comprehensive assessment

of each of the tools listed in Table 1 for each of the selection criteria.

Example A plant ergonomics team at ABC Gum Company is interested in selecting tools to help with

analyzing ergonomic risk factors in the Packaging Department. Employees manually pack store

display units into larger cartons, and then manually palletize these boxes for shipment to a

distributor. The team knows that manual palletizing of filled boxes and repetitive hand packing

are the key tasks to investigate. The Department Manager is from Missouri and insists, “Show

me the problem and how bad it is.” The company ergonomist identifies six key criteria and four

tools for consideration. The resulting decision matrix is shown below.

CRITERIA NIOSH RLE Appendix B RULA SI

Applicable for

Back

Yes Yes No No

Applicable for

Wrist

No Yes Yes Yes

Learning Curve Fair to poor Very good Good Fair to poor

Usability Fair Good Good Fair

Repeatability Good Very good Good Poor

Specificity Very good Fair to poor Fair Very good

Table 2: Sample decision matrix comparing four job analysis tools.

As a result of this analysis, the team chooses to start with the Appendix B checklist. If this does

not convince the manager, the team plans to use both the NIOSH RLE and RULA to gather

additional supporting data.

Acknowledgement The author would like to thank Mr. Milt Brouwer, CPE, for his assistance in gathering

information for this presentation.