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ReferencesNavigation arrowAuthorsNavigation arrowRichard W. Marklin
Jun 18

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Richard W. Marklin

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Publications by Richard W. Marklin (bibliography)

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2009
 
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Saginus, Kyle A., Marklin, Richard W. and Voglewede, Phillip A. (2009): Dynamic Modeling of Hand Push Force to Close a Disconnect Switch at Switching Stations and Substations. In: Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting 2009. pp. 902-906.

“Electric utility switching stations and substations in the U.S. typically have hundreds of disconnect switches in outdoor yards that are manually closed and opened. For safety reasons, these switches are usually located at least 10 ft above the ground and require specialized methods to open and close the switch. The most common manual method to open or close a disconnect switch is through the use of an insulated pole that ranges from 6 to 20 ft long. Due to the shear number of required independent tasks (workers may have to open or close 100 disconnect within 30 min), the manual opening and closing of disconnect switches is physically demanding and presents risk of musculoskeletal disorders (MSDs), particularly to the upper extremities. The purpose of this study was to model the hand push force exerted by the worker on the insulated pole to close a disconnect switch. A force gauge was attached to the end of the insulated stick while a worker closed a switch. An average of 510 lbs of peak reaction force was measured when the switch was closed. Digital video revealed the average time interval for the worker to push the stick was 210 ms, from the time the motion was started to the time the switch was completely closed. Modeling in Siemens NX6.0 with ADAMS showed that a constant input force of 24 lbs on the stick was required by the worker to generate a peak reaction force of 510 lbs. Because most of the peak reaction force is transmitted to the upper extremities of the worker, these tasks expose the workers to MSDs. This type of dynamic analysis can be applied to many tasks that require a worker to use motion to exert a high peak reaction force. Furthermore, this method can enable researchers to assess the forces applied by a worker throughout the duration of a task, rather than just at the endpoint, which may provide more insight into which part(s) of a task present the greater risk of MSDs.”

© All rights reserved Saginus et al. and/or their publisher

1995
 
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Monroe, John F. and Marklin, Richard W. (1995): Quantitative Biomechanical Analysis of Wrist Motion in Bone-Trimming Jobs in the Red-Meat Packing Industry. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. pp. 595-599.

“This study was motivated by the serious impact that cumulative trauma disorders (CTDs) of the upper extremities have on industrial workers and on industry itself. To date, no quantitative data has been gathered on the kinematics of hand and wrist motion required in bone-trimming jobs in the red-meat packing industry. No information is known about what type and how much wrist motion is currently being used in bone-trimming jobs in the red-meat packing industry, or how much these motions increase the risk of occupational CTDs. The research conducted addressed this current research void and established a preliminary database of wrist and hand kinematics for a bone-trimming job in the red-meat packing industry. This kinematic database could augment the red-meat industry's efforts to reduce the severity and cost of CTDs. Ergonomics practitioners in the red-meat industry could use the kinematic methods employed in this research to assess the CTD risk of current and redesigned jobs that require repetitious, hand-intensive work. The study examined the wrist motions used by nine red-meat packing workers who performed bone-trimming jobs. These jobs are highly repetitive and hand-intensive. Quantitative measures of the kinematic parameters of wrist motions performed on the bone-trimming line were measured using goniometry. The wrist motion measures consisted of the following statistics in the radial/ulnar, flexion/extension, and pronation/supination planes: 1). mean, minimum, and maximum of wrist angle position, 2). mean, minimum, and maximum of angular velocity, and 3). mean, minimum, and maximum of angular acceleration. The kinematic data were compared to manufacturing industry's preliminary wrist motion benchmarks. These benchmarks were the means and variances of nine dependent variables of position, velocity, and acceleration from industrial workers who performed hand-intensive, repetitive work in jobs that were of low and high risk of hand/wrist CTDS (Marras and Schoenmarklin, 1993). Results of this comparison show that numerous wrist motion variables in both the left and right hands of bone-trimming workers are in the high-risk category. This quantitative analysis provides biomechanical support for the high incidence of CTDs in the bone-trimming line of the plant that was investigated.”

© All rights reserved Monroe and Marklin and/or Human Factors Society

 
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Changes to this page (author)

03 Nov 2010: Modified
27 Jun 2007: Added

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URL: http://www.interaction-design.org/references/authors/richard_w__marklin.html
Jun 18

“ Computer programs emerge as the outcome of complex human processes of cognition, communication and negotiation, which serve to establish the meaningful embedding of the computer system in its intended use context. ”

-- Floyd, 1992, p. 24

 
 

Featured chapter

Read the fascinating history of Wearable Computing, told by its father, Steve Mann

Read Steve's chapter !

 
 

Latest books

The Social Design of Technical Systems: Building technologies for communities
by Brian Whitworth and Adnan Ahmad

 
Start reading

The Encyclopedia of Human-Computer Interaction, 2nd Ed.
by Mads Soegaard and Rikke Friis Dam

 
Start reading
 
 

Help us help you!

 
 
 
 
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