Reliability prediction of a mechatronic hydraulic drive at the early design stages

Author:

Тikhenko ValentinORCID,

Abstract

The article deals with the reliability of technological machines that use hydraulic feed drives. A priority task in mechanical engineering is the design of mechanical systems with higher stability, reliability, and performance. Various mechatronic systems are used to solve this problem, including mechatronic motion modules for hydraulic drives of technological machines. It is noted that the study of the reliability of mechatronic systems presents a special problem since the interaction of mechanical, hydraulic, and electronic systems gives rise to some new aspects of the theory of reliability. The main technical solutions for reliability incorporated in the design directly impact the machine's functional and economic characteristics. When predicting reliability at an early stage of design, there is the greatest uncertainty (entropy) in assessing the possible states of the machine. As an object of study, a mechatronic hydraulic drive is considered an electro-hydraulic motion module, which can be used in feed drives for heavy metal-cutting machines or industrial robots with a large load capacity. An important parametric characteristic of such a drive is the positioning accuracy of the working body, its stability, and the preservation of values within the specified limits over time. A review of the methodology for assessing and predicting the reliability of mechanical systems is carried out. It is noted that several statistical methods require the accumulation of test results for serial models or prototypes, but many important factors may not be taken into account. The purpose of this article is to obtain the results of predicting the parametric reliability of mechatronic hydraulic drives by using the method of expert assessments (rank correlation) at the early stages of design. This method is based on the ability of independent experts (qualified experts in the field) to provide useful information in the face of quantitative uncertainty. When setting the problem of predicting reliability, the factors that affect the positioning accuracy of the hydraulic drive were ranked in order of importance (ranked). An analytical relationship was established between the weight of the factor and its number in the series. The arithmetic mean weight, the mean relative weight, the standard deviation of the factors that affect the parametric reliability of the drive, and the coefficient of variation are determined. The consistency of expert opinions was shown based on heuristic indicators using the concordance coefficient (Kendall criterion). The considered technique can be used to predict and evaluate the reliability of mechatronic systems that are being developed for use in various fields of technology.

Publisher

Lviv Polytechnic National University

Subject

Cell Biology,Developmental Biology,Embryology,Anatomy

Reference23 articles.

1. [1] G.O. Obors'kij et al., Nadiinist tekhnolohichnykh system ta obladnannia [Reliability of technological systems and equipment]. Odesa, Ukraine: Bahva Publ., 2013. [in Ukrainian].

2. [2] M. Rausand, A. Barros, and A. Hoyland, System Reliability Theory: Models, Statistical Methods, and Applications, 3rd ed. New York: A John Wiley & sons, inc., Publ., 2020.

3. [3] Z. He, H. Cao, Y. Zi, and B. Li, "Developments and thoughts on operational reliability assessment of mechanical equipment," Journal of Mechanical Engineering, vol. 50, no. 2, pp. 171-186, 2014.

4. [4] S. K. Polyans'kij, V. І. Les'ko and G. K. Chernega, Rozrakhunok pokaznykiv nadiinosti mashyn za statystychnymy danymy [Calculation of machine reliability indicators based on statistical data]. Kiїv, Ukraine: NUBA, 2010. [in Ukrainian].

5. [5] C. López, A. Baldomir and S. Hernández, "Some Applications of Reliability based Design Optimization in Engineering Structures", WIT Transactions on The Built Environment, 137, pp. 393-404. 2014.

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