Assessment of Reliability of CNC Machine Tool Using a Dual-Weibull Based on Failure Data

doi:10.23940/ijpe.26.07.p6.417425

Abstract

Abstract: Modern manufacturing sectors require continuous machining operations in the competitive business world of today. Unexpected machining failures result in significant production losses. Therefore, switching from expensive reactive repairs to optimal preventive maintenance schedules requires an accurate reliability assessment. Even though complex machinery includes several subsystems, traditional reliability studies treat it as a single work machine. It obscures the unique failure patterns of individual parts, resulting in erroneous estimates of the machine's total lifespan. This paper proposes a thorough reliability assessment model for a Computer Numerical Machine (CNC) grinding machine with an emphasis on sub-systems in order to fill this research gap. The primary goals of this work are to accurately characterize different sub-system failure behaviors and predict total machine reliability. 252 empirical failure data points from a manufacturing plant's records are used in the study. Machine reliability is evaluated using a thorough series system model that accounts for the mechanical and electrical subsystems. To analyze the unique degradation characteristics of each sub-system, a two-parameter Weibull model is proposed. The least-squares method is used to estimate the shape and scale parameters in order to quantitatively characterize the overall system reliability function. To validate the model, a direct comparison is made between the simulated system Mean Time Between failure (MTBF) and the actual observed MTBF from the raw failure data. The relative error percentage is used to validate the mathematical framework. The machine's overall error was 10.52%. The proposed study's practical implications are crucial for failure and maintenance planners since they enable them to develop maintenance schedules based on these findings.

Key words: reliability assessment, system Modeling, CNC machine tool, dual-Weibull model, MTBF

Praveen Saraswat, Rajeev Agrawal, Anand Soni, and Vaibhav Sharma. Assessment of Reliability of CNC Machine Tool Using a Dual-Weibull Based on Failure Data [J]. Int J Performability Eng, 2026, 22(7): 417-426.

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