A STRUCTURED FRAMEWORK FOR RELIABILITY AND RISK EVALUATION IN THE MILK PROCESS INDUSTRY UNDER FUZZY ENVIRONMENT

This paper aims at proposing a novel integrated framework for studying reliability and risk issues of the curd unit in a milk process industry under uncertain environment. The considered plant’s complex series-parallel configuration was presented using the Petri Net (PN) modeling. The Fuzzy Lambda-Tau (λ-τ) approach was applied to study and analyze the reliability aspects of the considered plant. Failure dynamics of the curd unit has been analyzed with respect to increasing/ decreasing trends of the tabulated reliability indices. Availability of the considered plant shows a decreasing trend with an increase in spread values. For improving the system’s availability, a risk analysis was done to identify the most critical failure causes. Using the traditional FMEA approach, the FMEA sheet was generated on the basis of expert’s knowledge/experience. The Fuzzy-Complex Proportional Assessment (FCOPRAS) approach was applied within FMEA approach for identification of critical failure causes associated with different subsystem/components of the considered plant. In order to check the consistency of the ranking results, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) was applied within the FCOPRAS approach. Ranking results are compared for checking consistency and robustness of critical failure causes related decision making which would be useful in designing the finest maintenance schedule for the considered curd unit.  Overheating/moisture lead to winding failure (MSCP5), visible sediment of milk jam in filter (MBFP3), improper quality of oil (H4), blade breakage (CTK4), wearing in gears (PFM11), and cylinder leakage (CFM7) were recognized as the most critical failure causes contributing to system unavailability. The analysis results were supplied to the maintenance manager for framing a suitable time-based maintenance intervals policy for the considered unit

Data-driven system reliability and failure behavior modelling using FMECA

System reliability modelling needs a large amount of data to estimate the parameters. In addition, reliability estimation is associated with uncertainty. This paper aims to propose a new method to evaluate the failure behavior and reliability of a large system using failure modes, effects and criticality analysis (FMECA). Therefore, qualitative data based on the judgment of experts is used when data is not sufficient. The subjective data of failure modes and causes has been aggregated through the system to develop an overall failure index (OFI). This index not only represents the system reliability behavior but also prioritizes corrective actions based on improvements in system failure. In addition, two optimization models are presented to select optimal actions subject to budget constraint. The associated costs of each corrective action are considered in risk evaluation. Finally, a case study of a manufacturing line is introduced to verify the applicability of the proposed method in industrial environments. The proposed method is compared with conventional FMECA approach. It is shown that the proposed method has a better performance in risk assessment. A sensitivity analysis is provided on the budget amount and the results are discussed.Hadi A. Khorshidi, Indra Gunawan, and M. Yousef Ibrahi