Development of analytical technique, tool, and metric for seat comfort prediction

Akindeji O Ojetola, Tennessee State University


Long period of sitting occurs during our day to day life. It has been estimated that up to 80% of our active non-sleeping time are spent in some sort of sitting position ranging from work, recreation, entertaining, commuting, resting, and exercising. As a result, several health effects like numbness, nerve/circulation occlusions, pressure sore, low back pain, and vein thrombosis have been associated with protracted sitting. Numerous researches have been conducted in the area of seat comfort. It seems however, that the ability of a seat to provide comfort is still elusive. The evidence of this inability is in the myriad of products that claim to provide or improve comfort while seating. This research work is geared toward developing a technique, tool and metric for seat comfort prediction. The approach stems from using System Engineering (SE) by Quality Function Deployment (QFD) to inculcate the understanding of the consumers' wants into designing comfort into the seat design process. The data used for developing the QFD was from static comfort assessments of ejection seat and airline cushions experiments. The developed QFD could be used for either designing a new seat or modifying an existing one to increase seat comfort. The result of the QFD and other factors affecting seat comfort are used to develop seat comfort prediction model. This model could predict the level of comfort associated with a seat as perceived by a person sitting in a seat design, over the course of a period by taking into consideration, seat features, anthropometrics, and seat design parameter. Finally, a database of several cushion materials and seat structural material properties are created. An attempt is also made to analyze how altering some of the seat features affect seat comfort.

Subject Area

Industrial engineering|Mechanical engineering|Systems science

Recommended Citation

Akindeji O Ojetola, "Development of analytical technique, tool, and metric for seat comfort prediction" (2010). ETD Collection for Tennessee State University. Paper AAI3433416.