Enhanced efficiency and quality in wind turbine gearbox assembly: a new parallel assembly sequence planning (PASP) model

Abstract

This paper presents two major advances in parallel assembly sequence planning (PASP) for complex systems, specifically wind turbine gearboxes. The proposed time-cost-quality PASP hybrid model (PASP-TCQ) aims to enhance efficiency, reduce costs, and improve quality by aligning optimisation parameters with real-world demands. This model is designed to optimise complex assembly processes by addressing constraints on time, cost, and quality effectively. Additionally, we introduce a particle swarm-bacteria foraging optimisation (PSBFO) algorithm that integrates the global search capability of particle swarm optimisation (PSO) with the local optimisation strengths of bacteria foraging optimisation (BFO). Integrating PSBFO into PASP-TCQ achieves significant improvements: a 17% reduction in assembly time to 100 hours, a 10% cost reduction to $94,500, and a quality index improvement to 0.93. Statistical tests, including analysis of variance (ANOVA) and tukey’s honest significant difference (HSD), confirmed the PSBFO’s superiority, with significant gains of 8.44 units over BFO and 13.02 units over PSO in objective function values (p < 0.05). Extensive simulations on a 10 MW wind turbine gearbox validate the effectiveness of the PASP-TCQ and PSBFO, demonstrating their potential to enhance efficiency and productivity in industrial assembly operations.

Keywords

• Parallel assembly sequence planning
• time-cost-quality hybrid model
• particle swarm-bacteria foraging optimisation
• optimization algorithms
• industrial assembly efficiency
• wind turbine gearboxes