On Development of Methods for Expressing Customer Affective Response for Apparel Products

Abstract

In dimensional metrology, contact and non-contact measurement methods each have their own respective strengths and weaknesses. Touch-trigger probes have low uncertainty, and perform well inside deep holes, but have a relatively slow data acquisition speed. By contrast, non-contact digitizers collect high density surface point clouds in seconds, and are much less likely to suffer from sensor collision with the part, but have a higher uncertainty than touch probes. In sheet metal forming, iterative design of the stamping die is needed due to the springback of the sheet metal part. Holes or other features of first article parts may be significantly out of tolerance, so the tactile measurement path created from the Computer Aided Design (CAD) nominal has to be adjusted to avoid cosine error. In more serious cases, probe collisions or missed touches may occur. When measuring holes in thin sheet metal, determination of the touch probe path height is also a challenge if the actual surface location differs from the nominal.To solve this problem and seize the complimentary advantages of contact and non-contact measurement methods, a multi-sensor blue Light Emitting Diode (LED) snapshot sensor and touch-trigger probe inspection system was developed, and affixed to a Coordinate Measuring Machine (CMM). The tactile measurement path was adjusted according to the approximate positions and sizes of the features obtained from the scanner iv data. The system includes an in-house designed calibration target for scanner calibration and a lightweight 2-axis rotary table for multiple-orientation scanning as well. Software in programming language C for interacting with the scanner and the CMM was developed.

Developing a mapping from affective words to design parameters for affective design of apparel products

“…Firstly, the KES only considered the comfort feeling of the customer given a fabric material property, while our work considered a list of 30 AWs, which is obtained through a comprehensive data mining technique. 17 Secondly, the KES can only be used for analysis (i.e. from ADPs to AWs), while our work targets design (i.e.…”

“…Challenge 1 is studied in the authors' previous work, where a human's affects are represented by the so-called AWs 17 (also see Table 1). Challenge 2 is studied in the literature.…”