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Record W4242320931 · doi:10.2523/86626-ms

Ergonomic Considerations in Physically Demanding Jobs

2004· article· en· W4242320931 on OpenAlexaffabout
Dennis Attwood, Dave Fennell

Bibliographic record

VenueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production · 2004
Typearticle
Languageen
FieldEngineering
TopicErgonomics and Human Factors
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsComputer scienceHuman–computer interaction

Abstract

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Ergonomic Considerations in Physically Demanding Jobs Dennis Attwood; Dennis Attwood RRS Engineering, LLC Search for other works by this author on: This Site Google Scholar Dave Fennell Dave Fennell Imperial Oil Resources Limited Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. Paper Number: SPE-86626-MS https://doi.org/10.2118/86626-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Attwood, Dennis, and Dave Fennell. "Ergonomic Considerations in Physically Demanding Jobs." Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. doi: https://doi.org/10.2118/86626-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search AbstractWithin the oil and gas industry, some physical jobs haven't changed for years. Even today, many of the tasks performed on-site and in the field are physically demanding - so much so that many tasks exceed the long-term physical capability of most operators. Over time, we have seen workers gradually 'wear out' physically and self-elect to move into tasks that are less demanding, but also less rewarding. In our opinion, it does not have to be this way. The objective of this paper is to demonstrate how physically demanding jobs can be analyzed and how practical, cost-effective changes can be made to reduce the physical stress on the operator. It is our goal to demonstrate how positions that are now seen as 'interim work' can be made into careers that workers can perform into their retirement.IntroductionIn 1700 Dr. Bernadino Ramazzini published the first edition of what was to become one of the most quoted books on occupational disease, De Morbus Artificum Diatriba [Diseases of the Worker]. Ramazzini was the first person to establish a link between hazards in the workplace and human illness and injury. In one passage, he stated (Mandel, 2003):"Various and manifold is the harvest of diseases reaped by certain workers from the crafts and trades that they pursue. All the profit they get is fatal injury to their health, mostly from two causes. The first and most potent is the harmful character of the materials they handle. The second I ascribe to certain violent and irregular motions and unnatural positions of the body, by reason of which the natural structure of the vital machine is impaired so serious disease gradually develops there from"Illnesses and injuries were often named from the occupation of the people who suffered the injury - "brick layers thumb, reed maker's elbow, flute player's hand". Many of these injuries were suffered early in the worker's career and required the worker to retire early from the occupation. We have the opportunity today to prevent a legacy of illnesses that future generations may refer to as 'driller's neck', 'floorman's elbow' or 'roughneck's back'.Elimination of the conditions that cause serious injuries due to repeated trauma is possible through the application of Human Factors principles. Human Factors/Ergonomics is defined as the systematic process of designing for human use through the application of our knowledge of people to the equipment they use, the environments they operate in, the tasks they perform and the management systems that guide the safe and efficient operations of the equipment they work with. Neglecting any of these elements could lead to the failure of the entire facility. The key word in the above definition is "systematic". Human Factors has been applied in heavy industry for many years. But, too often the application employs a trial and error approach - try a design then change it when is doesn't work — that is guided by common sense rather than by good science. The problem with not getting the design right the first time is that it can lead to inefficiencies, retrofit costs and, too often, the error from which we learn is found through a worker injury.The model presented in Figure 1 depicts the systematic process of designing for humans. It begins with understanding the standards that guide the way your operation is designed, operated and maintained. It then identifies and prioritizes the most significant issues in your operation, analyzes the critical issues and implements the best solutions. Finally, the model makes sure that the results of the solution are measured, so you know that it works.In the paragraphs to follow, the case studies that are presented were identified, analyzed against applicable standards, and solutions were generated and measured according to the model presented above. Keywords: lifting index, operator, well head, technician, injury, rig, application, ergonomics, biomechanical analysis, posture Subjects: Health, Safety, Ergonomics, Human factors (engineering and behavioral aspects) This content is only available via PDF. 2004. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.240
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2004
Admission routes2
Has abstractyes

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