- Title
- The use of psychometric test systems as a pre-selection tool for identifying successful harvesting machine operators
- Creator
- Schwegman, Kylle
- Subject
- Port Elizabeth (South Africa)
- Subject
- Eastern Cape (South Africa)
- Subject
- South Africa
- Date Issued
- 2022-04
- Date
- 2022-04
- Type
- Doctoral theses
- Type
- text
- Identifier
- http://hdl.handle.net/10948/55246
- Identifier
- vital:51102
- Description
- A shift towards fully mechanized forest activities, such as harvesting and, more recently, silviculture, has occurred from the early 2 000’s. The reason for mechanizing these activities differs for each country, although for most countries there is concern relating to the health and safety of forest workers. With mechanization in harvesting, the forest worker has moved away from the physical intensity of having to fell, debranch, debark and cross-cut trees into logs using either an axe or chainsaw, to operating a machine. Studies revolving around the human element (operator) have been conducted specifically relating to the ergonomics of the machines and how operators may influence machine productivity. Results showed that due to the repetitive nature of the work, the operators are exposed to associated stresses for longer periods. Typical injuries associated to these kinds of stressors are whole body vibrations (WBVs), repetitive hand and arm movements, non-neutral body postures and manual lifting, which lead to musculoskeletal symptoms in the lower back, neck and shoulders. However, as machine technology improves so does the ergonomic conditions which are experienced by machine operators. Machine productivity can be influenced by various factors, with the most influential being tree volume. However, a recent study showed that over 40% of variation in machine productivity has been observed amongst different machine operators operating similar machines. The specific reason for these differences has yet to be determined. However, decision making, motivation, planning capacity, concentration, memory, motor coordination, pattern recognition, logic reasoning, and spatial perception are abilities that have been described as important for successful harvesting work. The pre-selection of operators using psychometric and cognitive tests is not new to forestry, although very little information is available relating to the aptitude test known as the Vienna test system as well as the best possible demographic associated with successful harvesting operators. The overall aim of this study was to determine whether the high variation found amongst harvesting machine operators could be reduced initially through a preselection process which involves the use of aptitude tests (Vienna Test System) and demographic questionnaires. A study was implemented in Zululand, South Africa, testing whether there were significant productivity differences between nine machine operators.
- Description
- Thesis (PhD) -- Faculty of Science, School of Natural Resource Management, 2022
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (104 pages)
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
- Rights
- All Rights Reserved
- Rights
- Open Access
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Schwegman Kylle PhD Thesis 2022.pdf | 3 MB | Adobe Acrobat PDF | View Details Download |