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Monitoring defects of ceramic tiles using fuzzy subtractive
clustering-based system identification method
Mohammed T. Hayajneh Æ Adel Mahmood Hassan Æ
Fatma Al-Wedyan
 Springer-Verlag 2009Abstract In this paper, a subtractive clustering fuzzy
identification method and a Sugeno-type fuzzy inference
system are used to monitor tile defects in tile manufacturing
process. The models for thetile defects are identified
by using the firing mechanical resistance, water absorption,
shrinkage, tile thickness, dry mechanical resistance and
tiles temperature as input data, and using theconcavity
defect and surface defects as the output data. The process
of model building is carried out by using subtractive
clustering in both the input and output spaces. A minimum
error model isdeveloped through exhaustive search of
clustering parameters. The fuzzy model obtained is capable
of predicting the tile defects for a given set of inputs as
mentioned above. The fuzzy model isverified experimentally
using different sets of inputs. This study intends to
examine and deal with the experimental results obtained
during various stages of ceramic tile production during
90-dayperiod. It is believed, that the results obtained from
the present study could be considered in other ceramic tiles
industries, which experienced similar forms of defects.
Keywords Fuzzy logic  Fuzzysubtractive clustering 
Ceramic tiles  Tile manufacturing  Defects 
Surface defects  Convexity defects 
Sugeno-type fuzzy inference system
1 Introduction
One of the greatest challenges facingthe industry of
ceramic in recent decades is the process of manufacturing
ceramic tiles without defects. Ceramic tiles are manufactured
by pressing clay and other materials into shape and
firingit at high temperatures, giving it the hardness and
durability it is known for. The body of a tile may then be
glazed, or left unglazed depending on its intended use
(Mazzacani and Biffi 1997)....
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