Optimizing Wind Turbine Blade Manufacturing Using Single-Minute Exchange of Die and Resource-Constrained Project Scheduling


Tunçel Memiş G., Yıldız G., Akcal N., Korkmaz G.

PROCESSES, cilt.13, sa.7, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 7
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/pr13072208
  • Dergi Adı: PROCESSES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex
  • Anahtar Kelimeler: lean manufacturing, setup time reduction, resource-constrained scheduling, workforce optimization, cycle time improvement, renewable energy manufacturing
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

This paper aims to enhance operational efficiency in the labor-intensive production of composite wind turbine blades, which are critical components of renewable energy systems. The study was conducted at a wind energy facility in T & uuml;rkiye, integrating the Single-Minute Exchange of Die (SMED) methodology with a Multi-Mode Resource-Constrained Project Scheduling Problem (MRCPSP) model to reduce production cycle time and optimize labor utilization. An operational time analysis was used to identify and classify non-value-adding activities. SMED principles were then adapted to the fixed-position manufacturing environment, enabling the conversion of internal setup activities into external ones and facilitating task parallelization. These improvements significantly increased productivity and labor efficiency. Subsequently, a scheduling model was developed to optimize the sequence of operations while accounting for activity precedence and resource constraints. As a result, the proposed approach reduced cycle time by 28.6% and increased average labor utilization from 68% to 87%. Scenario analyses confirmed the robustness of the model under varying levels of workforce availability. The findings demonstrate that integrating lean manufacturing techniques with optimization-based scheduling can yield substantial efficiency gains without requiring major capital investment. Moreover, the proposed approach offers practical insights into workforce planning and production scheduling in renewable energy manufacturing environments.