Rasool et al. _________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ The base of the stock preparation unit lies in precise constancy control with effective concern. The design of stock preparation and approach flow systems essentially affects both cost and quality of the final paper product. Sheet properties and web run ability heavily rely on the stability of the blended furnish, refined fiber quality, and the accurate mixing of fillers and chemicals. The various technologies in pulping, refining, screening, and mixing can be customized to suit specific raw material characteristics, product category requirements, and mill conditions. Enhanced run capability and high-level paper quality with minimized production costs are attainable across paper, board, and tissue machines through these improvements. Consistency serves as the bedrock of the papermaking process, with its measurement and control directly effecting product variability and costs. Even minute enhancements in consistency control over the mill can yield material savings. Eventually, the success of improvements in the stock preparation unit is indicated by increased profitability and customer attainment. Beneficially enhance the process performance, it is very important to finitely measure customer satisfaction and identify critical factors regarding products or services. Several researchers suggested various methodologies for enhancement of reliability and performance of industrial processes. Wohl (1966) suggested methodology for system operational readiness and equipment dependability. Kumar et al. (1989) analyzed the availability of a washing system in the paper industry. Kumar et al. (1993) discussed the bleaching and screening system in the paper industry with good reduced and failed states and direct integration method is used to solve equations. Ebeling (2000) provided a comprehensive introduction of reliability and maintainability theory has been stated by Ebeling. Barabady & Kumar (2008) suggested reliability analysis of mining equipment as a study of crushing plant. Sharma & Kumar (2008) carried out the performance modeling of critical engineering systems using RAM approach. Malik and Barak (2009) conducted the economic analysis of a repairable system. Khanduja et al. (2009) suggested the performance analysis of the screening unit in a paper plant using Genetic Algorithm and analyzed the performance behavior of each subsystem of the screening unit using Genetic Algorithm. Iqbal and Uduman (2014) discussed the study of the stock preparation unit for paper making process and also optimized the performance of each subsystem of the stock preparation units in a paper plant by using Genetic Algorithm. Sharma and Vishwakarma (2014) used the Markov process in performance analysis of feeding system of sugar industry and emphasized the application of Markov processes. Abbas and Abdulsaheb (2016) examined an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. Aggarwal et al. (2016) developed reliability, availability, maintainability & dependability (RAMD) analysis of skim milk powder production subsystem and also recognized the most critical element responsible for low production of dairy plant. Aggarwal et al. (2017) carried out a mathematical model for performance evaluation of the serial processes in refining system of a sugar plant using RAMD approach. Garg (2017) proposed the performance analysis of an industrial system using soft computing based hybridized technique. Tsarouhas & Besseris (2017) developed maintainability analysis in shaving blades industry. Barak et al. (2018) suggested a stochastic model for two- unit repairable system under priority and inspection. Barak et al. (2018) proposed stochastic models for various redundant systems under various redundancy strategies. Pandey et al. (2018) proposed reliability analysis and failure rate evaluation for critical subsystems of the dragline. Ahmadi & Amin (2019) developed an integrated chance-constrained stochastic model for a mobile phone closed-loop supply chain network with supplier selection. Choudhary et al. (2019) analyzed reliability, availability and maintainability to examine a cement plant. Deenadayalan and Vaishnavi (2021) innovated deep learning based on modern techniques for reliability _____________________________________________________________________________________________ 2 Braz. J. Biom. ǡǤ 43 ǡǦͶ͵ʹǡʹͲʹͷǤ
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