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1

Assessing risk priority numbers of failures in the screw tightening machine of a hard disk drive production system

Paoprasert Naraphorn, Lin Wai Yan Htet, Muneekaew Thepniramit

Journal of Machine Engineering

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2022

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Vol. 22, No. 1

124--137

EN

In a competitive environment, many production industries must reduce costs while maintaining asset value and reliability. In the manufacturing process, the machine is essential because downtime can inhibit and stop production. This study investigated the breakdown trend of a hard disk drive production line in the manufacturing industry to recommend applying Reliability-Centered Maintenance (RCM) for improved productivity, reliability, and availability. This study focused on breakdown analysis, identifying potential failures, and classifying the main components of screw-tightening machines. The RCM method was used based on several tools: failure mode and effects analysis (FMEA), risk priority number (RPN), mean time between failures (MTBF), and mean time to repair (MTTR). The study identified which production line had the lowest availability and productivity due to high downtime and failure rates. In addition, the top-five failures were identified that severely disrupted production These breakdowns were overcome and their occurrence reduced was by calculating and evaluating MTBF and MTTR to help manage failures and indicate the efficiency of corrective action. Thus, this industry and others can achieve better equipment availability and machine reliability using the RCM method.

2

Markov reliability models of series systems with redundancy and repair facilities

Zhernovyi Yuriy, Kopytko Bohdan

Journal of Applied Mathematics and Computational Mechanics

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2021

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Vol. 20, nr 3

89--96

EN

In this paper, we use Markov models for studying the reliability of series systems with redundancy and repair facilities. We suppose that the units’ time to failure and recovery times are exponentially distributed. We consider the cases when 1≤ c ≤ m and m + 1 ≤ c ≤ m + n, for the system of n operating units, m unloaded redundant units and c repair facilities. Using the exponential distributions properties, we obtain stationary reliability indices of the series systems: steady-state probabilities, a stationary availability coefficient, mean time to failure, mean time between failures and mean downtime.

3

Process control using reliability based control charts

Jacob J. K., Sreejith P. S.

Journal of Achievements in Materials and Manufacturing Engineering

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2008

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Vol. 31, nr 2

498-504

EN

Purpose: The paper presents the method to monitor the mean time between failures (MTBF) and detect any change in intensity parameter. Here, a control chart procedure is presented for process reliability monitoring. Control chart based on different distributions are also considered and were used in decision making. Results and discussions are presented based on the case study at different industries. Design/methodology/approach: The failure occurrence process can be modeled by different distributions like homogeneous Poisson process, Weibull model etc. In each case the aim is to monitor the mean time between failure (MTBF) and detect any change in intensity parameter. When the process can be described by a Poisson process the time between failures will be exponential and can be used for reliability monitoring. Findings: In this paper, a new procedure based on the monitoring of time to observe r failures is also proposed and it can be more appropriate for reliability monitoring. Practical implications: This procedure is useful and more sensitive when compared with the λ-chart although it will wait until r failures for a decision. These charts can be regarded as powerful tools for reliability monitoring. λr gives more accurate results than λ-chart. Originality/value: Adopting these measures to system of equipments can increase the reliability and availability of the system results in economic gain. A homogeneous Poisson process is usually used to model the failure