TY - JOUR
T1 - Towards zero-defect manufacturing with a combined online - offline fuzzy-nets approach in wire electrical discharge machining
AU - Bufardi, Ahmed
AU - Akten, Olcay
AU - Arif, Muhammad
AU - Xirouchakis, Paul
AU - Perez, Roberto
N1 - © 2017 World Scientific and Engineering Academy and Society (WSEAS). Bufardi, A, Akten, O, Arif, M, Xirouchakis, P & Perez, R 2017, 'Towards zero-defect manufacturing with a combined online - offline fuzzy-nets approach in wire electrical discharge machining' WSEAS Transactions on Environment and Development, vol 13, pp. 401-409. The final publication is available at http://wseas.org/wseas/cms.action?id=15004.
PY - 2017
Y1 - 2017
N2 - Current practice of wire electrical discharge machining (W-EDM) is not defect free and still a number of parts produced by WEDM processes are rejected due to different defects. The main defects related to surface quality of W-EDMed parts include occurrence of surface lines, surface roughness, and recast layer (also called white layer). In this paper we characterize the different types of defects and for each of them we propose the appropriate approach to handle it. To achieve zero-defect manufacturing in W-EDM, one can intervene before starting machining operations through selecting the best combination of values of process parameters to meet required levels of performance for part quality characteristics, and during machining operations through monitoring machining conditions to predict any potential defect and take appropriate actions to prevent the effective occurrence of defects if and when predicted. This paper addresses both issues and a combined online - offline fuzzy-nets approach is proposed. It is noteworthy, that for the first time in the published literature, an approach is presented to prevent the occurrence of surface lines in W-EDM; this is accomplished by our experimentally validated system by: (i) high frequency sensing and processing of the current signal in the discharge zone; (ii) the development of a new algorithm for the detection and calculation of the duration of a series of consecutive short circuits; and (iii) the proactive adjustment of the pulse–off time through an adaptive fuzzy nets system.
AB - Current practice of wire electrical discharge machining (W-EDM) is not defect free and still a number of parts produced by WEDM processes are rejected due to different defects. The main defects related to surface quality of W-EDMed parts include occurrence of surface lines, surface roughness, and recast layer (also called white layer). In this paper we characterize the different types of defects and for each of them we propose the appropriate approach to handle it. To achieve zero-defect manufacturing in W-EDM, one can intervene before starting machining operations through selecting the best combination of values of process parameters to meet required levels of performance for part quality characteristics, and during machining operations through monitoring machining conditions to predict any potential defect and take appropriate actions to prevent the effective occurrence of defects if and when predicted. This paper addresses both issues and a combined online - offline fuzzy-nets approach is proposed. It is noteworthy, that for the first time in the published literature, an approach is presented to prevent the occurrence of surface lines in W-EDM; this is accomplished by our experimentally validated system by: (i) high frequency sensing and processing of the current signal in the discharge zone; (ii) the development of a new algorithm for the detection and calculation of the duration of a series of consecutive short circuits; and (iii) the proactive adjustment of the pulse–off time through an adaptive fuzzy nets system.
KW - critical process variable
KW - part quality characteristic
KW - vital process parameter
KW - WEDM
UR - http://wseas.org/cms.action?id=4031
M3 - Article
VL - 13
SP - 401
EP - 409
JO - WSEAS Transactions on Environment and Development
JF - WSEAS Transactions on Environment and Development
SN - 1790-5079
M1 - 42
ER -