A Cluster Approach for Task Assignment

被引:0
作者
Handley, Holly A. H. [1 ]
机构
[1] Old Dominion Univ, Norfolk, VA 23529 USA
来源
2019 13TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON) | 2019年
关键词
Human System Engineering; Task Assignment;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
One of the challenges of introducing new equipment is determining if the current personnel are a good fit, or if personnel changes should be made. This evaluation of role to task assignment is a common occurrence in the system architecting stage of systems that are installed in close environments, such as in operating centers, military vehicles or on ships. In these cases, the number and types of personnel is often fixed, and any changes need to include competency on both existing and predicted tasks. One method to determine the strength of a role to task assignment is based on keyword descriptors. Different personnel types, with different training backgrounds, can be compared to the task keywords to determine the best fit. However, the level of granularity of this approach can prove to be problematic, based as the number and range of keywords can become quite large. An alternative method is the clustering approach. In this case, similar types of training and similar types of tasks are grouped together and given a more general category description. The categories can also be weighted with importance factors to determine the most important skill clusters for the position. These higher level categories can then he used to determine the fit of the role to task assignment. The clusters can also be used in a visualization of a Fit Matrix to provide information to decision makers.
引用
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页数:6
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