<![CDATA[This paper examined the behavior of selected maintenance downtime parameters of handling equipment in a container terminal and established the system's optimal parameters. Taguchi method, Taguchi–Pareto method, and Taguchi–ABC method were applied to analyze it. The chosen process parameters are the downtime, probability density function, and cumulative density function. The L25, L25, and L20 orthogonal arrays were selected for the Taguchi, Taguchi-Pareto, and Taguchi–ABC methods. Data were acquired from a container terminal in the southern part of Nigeria, and we deployed the Weibull function to analyze the parameters at three shape functions of β = 0.5, 1, and 3 from twenty-five experiments. The signal–to–noise quotient and analysis of variance were used to establish the optimal level and contributions of the parameters. The results indicated that using the Taguchi method, for all the shape parameters of β = 0.5, 1, and 3, the most and the least significant parameters were downtime and cumulative density function, respectively. For the Taguchi-Pareto method, the most and the least significant parameters were downtime and probability density function, respectively, at β = 0.5. At β = 1, the most and the least significant parameters were downtime and cumulative density function, respectively. However, at β = 3, the most and the least significant parameters were probability density function and downtime, respectively. Finally, using the Taguchi-ABC method, at β = 0.5, the most and the least significant parameters were probability density function and downtime, respectively. Nonetheless, at β = 1 and 3, the most and the least significant parameters were downtime and probability density function, respectively. The proposed model would assist seaport maintenance managers in the effective control of downtime]]>
