Reliability, Availability, and Maintainability (RAM) Study of an Ice Cream Industry

Tsarouhas, Panagiotis

doi:10.3390/app10124265

Cited by 21 publications

(9 citation statements)

References 53 publications

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“…During the operation of technical facilities, the failure records form the basis for the development of reliability models. From this perspective, indices defining intervals to failure or between failure are useful [11,37]. These intervals can be expressed in operational units referring to the operating time of the object (h, mth) or to the mileage [km] in the case of vehicles.…”

Section: Reliability Estimationmentioning

confidence: 99%

Reliability Analysis of Military Vehicles Based on Censored Failures Data

2022

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The paper proposes a methodology of reliability testing as applied to vehicles used in military transport systems. After estimating the value of the reliability function using the Kaplan–Meier estimator, reliability models were developed and analysed. The neural model, which achieved the value of the correlation coefficient R exceeding 0.99, was determined to fit the empirical data the best. On the basis of the approximated reliability function of several models, the reliability characteristics of the tested sample of vehicles were determined. Plots of the failure probability density function for all three models had similar courses over a significant part of the function domain. A failure intensity function was also determined, which varied between models. For the exponential and Weibull model, the expected mileage between failures was calculated, which proved impossible for the neural model. The proposed methodology is capable of modelling reliability characteristics based on the observation of an assumed period of the exploitation process of the selected group of military vehicles.

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Section: Reliability Estimationmentioning

confidence: 99%

Reliability Analysis of Military Vehicles Based on Censored Failures Data

2022

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“…Here, an RL-based intelligent diagnostic is proposed to fulfil the next objective for improving the OEE of the curing machine in this investigation. Intelligent diagnostics automate the process for analyzing the status of the availability [22] of components in the curing machine. It also simplifies the planned short-and medium-term and unplanned long-term maintenance activities in modules of the curing machine.…”

Section: Rl-based Intelligent Diagnosismentioning

confidence: 99%

“…RAM analysis has helped the ice-cream industry [22] assess preventive maintenance intervals for planning and organizing effective maintenance schemes. Failure data were collected from RAM analysis over a period of 12 months.…”

Section: Introductionmentioning

confidence: 99%

Proactive Maintenance Model Using Reinforcement Learning Algorithm in Rubber Industry

Chandran¹,

Sudhakarapandian

2022

Processes

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This paper presents an investigation into the enhancement of availability of a curing machine deployed in the rubber industry, located in Tamilnadu in India. Machine maintenance is a major task in the rubber industry, due to the demand for product. Critical component identification in curing machines is necessary to prevent rapid failure followed by subsequent repairs that extend curing machine downtime. A reward in the Reinforcement Learning Algorithm (RLA) prevents frequent downtime by improving the availability of the curing machine at time when unscheduled long-term maintenance would interfere with operation, due to the occurrence of unspecified failure to a critical component. Over time, depreciation and degradation of components in a machine are unavoidable, as is shown in the present investigation through intelligent assessment of the lifespan of components. So far, no effective methodology has been implemented in a real-time maintenance environment. RLAs seem to be a more effective application when it is based on intelligent assessment, which encompasses the failure and repair rate used to calculate availability in an automated environment. Training of RLAs is performed to evaluate overall equipment efficiency (OEE) in terms of availability. The availability of a curing machine in the form of state probability is modeled in first-order differential-difference equations. RLAs maximize the rate of availability of the machine. Preventive maintenance (PM) rate for four modules of 16 curing machines is expressed in a transition diagram, using transition rate. Transition rate indicates the degree of PM and unplanned maintenance rates that defines the total availability of the four modules. OEE is expressed in terms of the availability of curing machines, which is related to performance and quality. The results obtained by RLA are promising regarding short-term and long-term efficiencies of OEE, which are 95.19% and 83.37%, respectively.

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“…On the one hand, the firms concentrate on the production process instead of gathering failure data. On the other hand, numerous firms refuse to supply their data on the reasons of competition (Tsarouhas, 2020a). Thus, the lack of quantitative data is one of the main issues for scientists to introduce qualitative approaches for the reliability estimation (Yazdi and Soltanali, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Maintenance scheduling of a cheddar cheese manufacturing plant based on RAM analysis

Tsarouhas

2021

IJPPM

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PurposeThe purpose of this research is to calculate and enhance the cheese cheddar manufacturing plant efficiency under actual workplace conditions by measuring reliability, availability and maintainability (RAM) indices. The authors highlight how RAM analysis is important in determining periodic maintenance and in scheduling and managing the appropriate maintenance policy.Design/methodology/approachThe current work is conducted using statistical approaches to evaluate failure and repair statistics. The RAM estimation was calculated on the basis of quantitative data obtained over a span of 32 months. Descriptive statistics, Pareto analysis, as well as the presumption of independence were ensured through trend and serial correlation tests. In addition, the reliability and maintainability of the cheddar cheese processing plant and its machines were calculated at various mission periods.FindingsThe primary goal of the implementation approach is to understand the fault patterns and the accurate quantitative assessment of the reliability and maintainability of the cheddar production plant. The findings revealed the essential aspects of the line, which need improvement by an appropriate maintenance program.Originality/valueThis study is intended to serve to highlight the RAM assessment and its impact on the performance of the real-time system. The benefit of the technique is the continual control of the manufacturing process by means of acceptable indexes, whose use corresponds to a continuous improvement process.

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Reliability, Availability, and Maintainability (RAM) Study of an Ice Cream Industry

Cited by 21 publications

References 53 publications

Reliability Analysis of Military Vehicles Based on Censored Failures Data

Reliability Analysis of Military Vehicles Based on Censored Failures Data

Proactive Maintenance Model Using Reinforcement Learning Algorithm in Rubber Industry

Maintenance scheduling of a cheddar cheese manufacturing plant based on RAM analysis

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