Abstract The growing demand for lightweight, durable, and environmentally friendly materials has positioned High-Density Polyethylene (HDPE) as a viable alternative in small boat production. Despite its advantages-including recyclability, UV resistance, and low maintenance-HDPE boat production involves a labour-intensive process with significant uncertainty in workforce needs. Existing studies have primarily focused on material performance and production techniques, leaving a gap in workforce optimisation under uncertainty. This study addresses this gap by proposing a two-stage stochastic programming model to forecast and optimise workforce requirements in HDPE boat hull production. The model captures variability in the amount of work and working performance, providing a structured approach to workforce planning. To solve the problem, the Sample Average Approximation (SAA) method is employed, and multiple replications are performed to ensure solution stability and robustness. Computational results indicate that workforce requirements remain relatively consistent across different scenarios, confirming the model’s robustness. Moreover, alternative solutions achieve lower total labour costs without compromising production efficiency. For the case study, the optimised total cost was 38,212 currency units, with workforce needs estimated at 24 man∙days for alignment, 10 man∙days for welding preparation, 10 man∙days for welding, and 29 man∙days for cosmetic ‘touch-up’. The findings provide practical insights into managing labour-related uncertainties in HDPE boat manufacturing, offering both economic and operational benefits. By integrating stochastic optimisation with sustainable material use, the proposed framework contributes to enhancing cost efficiency and production planning in the small boat industry.
Kafali et al. (Sat,) studied this question.