Machining conditions-based preventive maintenance

Akturk, M. Selim
Gürel, Sinan
In this study we propose an operating conditions-based preventive maintenance ( PM) approach for computer numerical control (CNC) turning machines. A CNC machine wears according to how much it is used and the conditions under which it is used. Higher power or production rates result in more wear and higher failure rates. This relationship between the operating conditions and maintenance requirements is usually overlooked in the literature. On CNC turning machines we can control the machining conditions such as cutting speed and feed rate, which in turn affect the PM requirements of the CNC machine. We provide a new model to link the PM decisions to the machining conditions selection decisions, so that these two decision-making problems can be solved together by considering their impact on each other. We establish that our proposed geometric programming model captures the related cost terms along with the technological restrictions of CNC machines. The proposed preventive maintenance index function can be used to provide an intelligent CNC machine degradation assessment.


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Karakayali, Ibrahim; Azizoğlu, Meral (Springer Science and Business Media LLC, 2006-03-01)
In this study, we address a job sequencing and tool switching problem arising in flexible manufacturing systems. We consider the single machine problem of minimizing total flow time. We prove that the problem is NP-hard in the strong sense and show that the tool switching problem is polynomially solvable for a given sequence.
Single machine scheduling with preventive maintenances
Batun, Sakine; Azizoğlu, Meral (Informa UK Limited, 2009-01-01)
We consider the single machine total flow time problem in which the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a branch-and-bound algorithm that employs powerful optimality properties and bounding procedures. Our extensive computational studies show that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times. We also study a two-alternative maintenance planning problem with min...
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This study addresses an allocation problem that arises in the semiconductor industry and flexible manufacturing systems where the tools should be loaded on computer numerical controlled (CNC) machines to process a number of operations. The time and tool magazine capacities of the CNC machines and the number of available tools of each type are limited. The objective is to maximize the total weight of operation assignments. We present a mixed integer programming formulation of the problem and show that the pr...
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Girit, Utku; Azizoğlu, Meral (Informa UK Limited, 2020-01-01)
Assembly line balancing is an important and well recognised operations research problem. The current line balance may not stay optimal, even feasible, due to the disruptions in one or more workstations. In this study, after the disruption, we aim to rebalance the assembly line by considering the trade-off between workload balancing (fairness measure) and total replacement distance for the tasks assigned to the different workstations (stability measure). We try to generate all non-dominated objective functio...
Part-mix allocation between automated and conventional manufacturing
KAYALlGIL, M. SINAN (Informa UK Limited, 1990-10)
The overall part-mix of a production system is allocated optimally between the existing conventional facilities and planned automated system to be acquired. Approximate mean value analysis (MVA) is utilized to evaluate performance of the automated system under trial part-mix allocations. Cost of processing and WIPs are taken as the sources of operational costs. Cost minimizing route allocations when alternatives exist are handled by a search procedure.
Citation Formats
M. S. Akturk and S. Gürel, “Machining conditions-based preventive maintenance,” INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, pp. 1725–1743, 2007, Accessed: 00, 2020. [Online]. Available: