Effectiveness improvement through total productive maintenance using particle swarm optimisation model for small and micro manufacturing enterprises

摘要

In many manufacturing industries, the total productive maintenance (TPM) is a significant maintenance methodology. In this paper we are employing the prior experimental result of a packaging industry, and then we develop a mathematical model based on real time experiment values in a small undisclosed Indian industry. We get an optimised value, by feeding the mathematical modelling values to the particle swarm optimisation and genetic algorithm, where only PSO values have a closer resemblance to the experimental values than the GA values. Then we develop theoretical result based on some suggestions and varied downtime, and the mathematical model is used to verify the theoretical result using particle swarm optimisation technique. We find all parameters based on theoretical suggestions and some mathematical functions, whereas the experimental result table comprises some parameters. Then these values are fed into the PSO algorithm, and finally we get the optimum output parameters compared to the existing result.