Battery production consistency impact analysis based on particle swarm trimmed mean fuzzy analytic hierarchy process

Aiming at the consistency analysis problem of power battery production, a novel swarm intelligence fuzzy analytic hierarchy algorithm is proposed, based on the censored scoring mechanism and particle swarm trimmed mean fuzzy analytic hierarchy process. First, the scoring data are obtained by designing the expert scoring table and processed with the trimmed mean value to obtain the fuzzy consistency matrix. After using the correction matrix and factor weights as the variables to be optimized, we construct the consistency function as the fitness function. Then, the particle swarm algorithm is used to optimize the minimum fitness value to solve the analysis results of battery process consistency. Finally, by the actual battery production line process simulation, the efficiency and superiority of the algorithm are verified and the battery production process analysis system is illustrated.