Subject Area
Production Engineering and Mechanical Design
Article Type
Original Study
Abstract
Spare parts inventories assist maintenance staff to keep equipment in operating conditions. Thus the level of spares stocked has a direct bearing on machine availability. One of the causes of downtime equipment in the repair process is the lack of necessary spare parts at the time of repair and maintenance actions. The minimization of the spare parts storage cost in enterprises is very important. The models of this theory are built according to the classical scheme of mathematical programming. Construction of such models requires definite assumptions, for example, of orders flows, time distribution laws and others. On the other hand, experienced managers very often make effective administrative decisions on the common sense and practical reasoning level. Therefore, the approach based on fuzzy logic can be considered as a good alternative to the classical inventory control models. In this paper, a fuzzy logic approach is introduced. This approach requires neither complex mathematical models construction no search of optimal solutions on the base of such models. It is based on simple comparison of the demand for the stock of the given brand at the actual time moment with the quantity of the stock available in the warehouse. Depending upon it inventory action is formed consisting in increasing or decreasing corresponding stocks. Expert decisions are considered for developing the fuzzy models, and the approach is based on method of nonlinear dependencies identifications by fuzzy knowledge. The linguistic variables are considered for the membership functions. Simple IF-Then rules are used with expert advices.
Keywords
Inventory management; machine tool; spare parts; Fuzzy Logic; fuzzification; defuzzification
Recommended Citation
Rastorguev, G. and Elerian, F.
(2020)
"Spare Parts Management for the Repair of Machine Tools Using Fuzzy Logic Approach.,"
Mansoura Engineering Journal: Vol. 39
:
Iss.
2
, Article 3.
Available at:
https://doi.org/10.21608/bfemu.2020.102885