TY - GEN
T1 - Fuzzy estimations of process incapability index
AU - Kahraman, Cengiz
AU - Kaya, Ihsan
PY - 2011
Y1 - 2011
N2 - Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined manufacturing capability prerequisite. In the literature, some PCIs have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). These have been successfully applied by companies to compete with and to lead high-profit markets by evaluating the quality and productivity performance. In this paper, one of the most important PCIs, process incapability index ( ) (Cpp) which provides more process information than other process PCIs and is easily applied is analyzed together with the indices inaccuracy ((Cia) and imprecision ((Cip). In this paper, the index (Cpp) is also analyzed by using the fuzzy set theory to obtain a deep and flexible analysis. To produce fuzzy process incapability index ((C̃pp), fuzzy process mean (μ̃ pp) and fuzzy variance ((σ̃ pp), which are obtained by using the fuzzy extension principle, are used together with fuzzy SLs ((SL̃%s)) and fuzzy target value ((T̃). In order to find the membership functions of fuzzy inaccuracy index ((C̃ia) and fuzzy imprecision index ( (C̃ip), the α-cuts of the fuzzy observation are employed. Then the fuzzy estimations of the index pp C% are produced for triangular fuzzy numbers (TFN). The proposed index (C̃pp) is applied in a piston manufacturer firm.
AB - Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined manufacturing capability prerequisite. In the literature, some PCIs have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). These have been successfully applied by companies to compete with and to lead high-profit markets by evaluating the quality and productivity performance. In this paper, one of the most important PCIs, process incapability index ( ) (Cpp) which provides more process information than other process PCIs and is easily applied is analyzed together with the indices inaccuracy ((Cia) and imprecision ((Cip). In this paper, the index (Cpp) is also analyzed by using the fuzzy set theory to obtain a deep and flexible analysis. To produce fuzzy process incapability index ((C̃pp), fuzzy process mean (μ̃ pp) and fuzzy variance ((σ̃ pp), which are obtained by using the fuzzy extension principle, are used together with fuzzy SLs ((SL̃%s)) and fuzzy target value ((T̃). In order to find the membership functions of fuzzy inaccuracy index ((C̃ia) and fuzzy imprecision index ( (C̃ip), the α-cuts of the fuzzy observation are employed. Then the fuzzy estimations of the index pp C% are produced for triangular fuzzy numbers (TFN). The proposed index (C̃pp) is applied in a piston manufacturer firm.
KW - Decision making
KW - Fuzzy set theory
KW - Imprecision index
KW - Inaccuracy index
KW - Process incapability index
UR - http://www.scopus.com/inward/record.url?scp=80755141330&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80755141330
SN - 9789881925145
T3 - Proceedings of the World Congress on Engineering 2011, WCE 2011
SP - 1106
EP - 1110
BT - Proceedings of the World Congress on Engineering 2011, WCE 2011
T2 - World Congress on Engineering 2011, WCE 2011
Y2 - 6 July 2011 through 8 July 2011
ER -