Toward resilient and adaptive warehousing with fuzzy-based selection of automated storage systems for industry 5.0


AYYILDIZ E., KESİCİ ÖĞRETMENOĞLU B., Erdogan M.

Applied Soft Computing, cilt.197, 2026 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 197
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.asoc.2026.115202
  • Dergi Adı: Applied Soft Computing
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Anahtar Kelimeler: Fuzzy, Industry 5.0, Multi criteria, Warehousing systems
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

The advent of Industry 5.0 (I5.0) marks a new era for manufacturing and warehousing, emphasizing the synergy between advanced automation and human-centric values. This evolution has brought renewed attention to the integration of human-robot collaboration within automated storage systems, a critical component of modern manufacturing logistics. This study presents a comprehensive multi-criteria decision-making (MCDM) framework for selecting automated storage systems, aligned with the principles of I5.0 and intelligent manufacturing. Relevant evaluation criteria were identified through a literature review and validated by expert insights from the fields of industrial engineering, automation, and supply chain management. The importance of these criteria was determined using the Picture Fuzzy Analytic Hierarchy Process (PiF-AHP) method, which effectively captures uncertainty in expert judgments. Subsequently, alternative automated storage solutions were ranked using the Picture Fuzzy Combinative Distance-based Assessment (PiF-CODAS) approach. This work advances the literature by introducing a novel fuzzy MCDM methodology tailored to the challenges of intelligent and human-centered warehouse design. A real-world case study is presented to demonstrate how manufacturers can leverage I5.0 concepts, such as human-machine integration, digital transformation, and sustainability, in their selection of automated storage systems. The findings highlight key priorities for future-ready, resilient, and adaptive storage solutions in computer-integrated manufacturing environments.