System Availability Assessment and Optimization of Repairable Cooling Module of HVAC System using PSO Algorithm

Parameter optimization of PID control is always a hot spot in the research field of control, and control effect of PID depends on the parameter values: proportion, integral and differentiation. This paper puts forward a global best and local best PSO algorithm, which is an optimization strategy of PID, the result of this method making the system have small overshoot and short adjusting time. The optimization scheme of this paper will be used in the control of HVAC system. through simulation, it is shown that there is good effect, such as non-overshoot and short adjusting time. Compared with the traditional method, performance of this algorithm is well improved and optimized objective function is decreasing.

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Comments for ‘System availability assessment using stochastic models’

Applied Stochastic Models in Business and Industry ◽

10.1002/asmb.1926 ◽

2013 ◽

Vol 29 (2) ◽

pp. 110-111

Author(s):

Toshio Nakagawa

Keyword(s):

Stochastic Models ◽

System Availability ◽

Availability Assessment

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Soft computing for availability optimization of a crushing system of sugar plant using PSO

International Journal of Quality & Reliability Management ◽

10.1108/ijqrm-10-2020-0347 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Anil Kr. Aggarwal ◽

Amit Kumar

Keyword(s):

Mathematical Modeling ◽

Differential Equations ◽

Pso Algorithm ◽

Repair Rate ◽

System Availability ◽

Content Type ◽

First Order ◽

Availability Analysis ◽

Sugar Plant ◽

Optimal Values

PurposeIn this paper, the objective is to perform mathematical modeling to optimize the steady-state availability of a multi-state repairable crushing system of a sugar plant using the evolutionary algorithm of Particle Swarm Optimization (PSO). The system availability is optimized by evaluating the optimal values of failure and repair rate parameters concerned with the subsystem of the system.Design/methodology/approachMathematical modeling of the multi-state repairable system is performed to develop the first-order differential equations based on the exponential distribution of the failure and repair rates. These differential equations are recursively solved to obtain the availability under normalizing conditions. The availability of the system is optimized by using the PSO algorithm. The results obtained by PSO are validated by using the Genetic Algorithm (GA).FindingsThe availability analysis of the system concludes that the cane preparation (F1) is critical of the crushing system and the optimized availability of the system using PSO is achieved as high as 87.12%.Originality/valueA crushing system of the sugar plant is evaluated as it is the main system of the sugar plant. The maintenance data associated with failure and repair rate parameters were analyzed with the help of maintenance records/logbook and by conducting personal meetings with maintenance executives of the plant. The results obtained in the paper helped them to plan maintenance strategies accordingly to get optimal system availability.

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