selecting ergonomic analysis tools - safety use by employee ergonomic teams, and process credibility...
TRANSCRIPT
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 [email protected]
- 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.