Academic article

Optimal Sorting of Raw Materials, Based on the Predicted End-Product Quality

Berget, Ingunn; Næs, Tormod

Publication details

Journal: Quality Engineering, vol. 14, p. 459–478, 2002

Issue: 3

International Standard Numbers:
Printed: 0898-2112
Electronic: 1532-4222

Open Access: none

Links:
DOI

Raw material variation is one of the most important factors causing unstable endproduct
quality. A methodology for sorting raw materials into homogenous groups
with constant and optimized processing within each group is presented. The sorting
criterion is based on the squared distance between the predicted response and its
target value. The raw materials are split into homogenous categories by a
partitioning algorithm related to the fuzzy-c-means algorithm. The method has been
tested for raw material properties in one and two dimensions and with different
degrees of fuzziness. The method shows good flexibility and can also be used with a
penalty function penalizing unfavorable process settings.