Assembly Line Balancing Using Fuzzy Mathematical Modeling

Tusan Derya; Kumru Didem Atalay; Irem Ucal Sari

doi:10.1007/978-3-031-98304-7_38

Assembly Line Balancing Using Fuzzy Mathematical Modeling

Tusan Derya
, Kumru Didem Atalay
, Irem Ucal Sari^*

^*Bu çalışma için yazışmadan sorumlu yazar

Baskent University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

Özet

This study investigates Assembly Line Balancing problem using fuzzy mathematical modeling. The proposed approach incorporates fuzzy parameters to model imprecise task times and resource constraints, enabling a more realistic representation of variability in the assembly process. A mathematical model is developed using fuzzy sets and solved to minimize cycle time and balance workload across stations. A case study is presented to demonstrate the application of the method, comparing the results with traditional crisp approaches. The findings highlight the advantages of using fuzzy modeling in achieving robust and efficient solutions in uncertain production environments.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
Editörler	Cengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	333-341
Sayfa sayısı	9
ISBN (Basılı)	9783031983030
DOI'lar	https://doi.org/10.1007/978-3-031-98304-7_38
Yayın durumu	Yayınlandı - 2025
Harici olarak yayınlandı	Evet
Etkinlik	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Türkiye Süre: 29 Tem 2025 → 31 Tem 2025

Yayın serisi

Adı	Lecture Notes in Networks and Systems
Hacim	1531 LNNS
ISSN (Basılı)	2367-3370
ISSN (Elektronik)	2367-3389

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Ülke/Bölge	Türkiye
Şehir	Istanbul
Periyot	29/07/25 → 31/07/25

Bibliyografik not

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

10.1007/978-3-031-98304-7_38

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Derya, T., Atalay, K. D., & Ucal Sari, I. (2025). Assembly Line Balancing Using Fuzzy Mathematical Modeling. In C. Kahraman, B. Oztaysi, S. Cebi, S. Cevik Onar, C. Tolga, I. Ucal Sari, & I. Otay (Eds.), Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference (pp. 333-341). (Lecture Notes in Networks and Systems; Hac. 1531 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-98304-7_38

Derya, Tusan ; Atalay, Kumru Didem ; Ucal Sari, Irem. / Assembly Line Balancing Using Fuzzy Mathematical Modeling. Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. editör / Cengiz Kahraman ; Basar Oztaysi ; Selcuk Cebi ; Sezi Cevik Onar ; Cagri Tolga ; Irem Ucal Sari ; Irem Otay. Springer Science and Business Media Deutschland GmbH, 2025. pp. 333-341 (Lecture Notes in Networks and Systems).

@inproceedings{b69af4a0d1c54161aabcb481fff7560d,

title = "Assembly Line Balancing Using Fuzzy Mathematical Modeling",

abstract = "This study investigates Assembly Line Balancing problem using fuzzy mathematical modeling. The proposed approach incorporates fuzzy parameters to model imprecise task times and resource constraints, enabling a more realistic representation of variability in the assembly process. A mathematical model is developed using fuzzy sets and solved to minimize cycle time and balance workload across stations. A case study is presented to demonstrate the application of the method, comparing the results with traditional crisp approaches. The findings highlight the advantages of using fuzzy modeling in achieving robust and efficient solutions in uncertain production environments.",

keywords = "Assembly Line Balancing, Fuzzy Mathematical Modeling, Intelligent Manufacturing",

author = "Tusan Derya and Atalay, \{Kumru Didem\} and \{Ucal Sari\}, Irem",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 ; Conference date: 29-07-2025 Through 31-07-2025",

year = "2025",

doi = "10.1007/978-3-031-98304-7\_38",

language = "English",

isbn = "9783031983030",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "333--341",

editor = "Cengiz Kahraman and Basar Oztaysi and Selcuk Cebi and \{Cevik Onar\}, Sezi and Cagri Tolga and \{Ucal Sari\}, Irem and Irem Otay",

booktitle = "Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference",

address = "Germany",

}

Derya, T, Atalay, KD & Ucal Sari, I 2025, Assembly Line Balancing Using Fuzzy Mathematical Modeling. in C Kahraman, B Oztaysi, S Cebi, S Cevik Onar, C Tolga, I Ucal Sari & I Otay (eds), Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. Lecture Notes in Networks and Systems, hac. 1531 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 333-341, 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, Istanbul, Türkiye, 29/07/25. https://doi.org/10.1007/978-3-031-98304-7_38

Assembly Line Balancing Using Fuzzy Mathematical Modeling. / Derya, Tusan; Atalay, Kumru Didem; Ucal Sari, Irem.
Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. ed. / Cengiz Kahraman; Basar Oztaysi; Selcuk Cebi; Sezi Cevik Onar; Cagri Tolga; Irem Ucal Sari; Irem Otay. Springer Science and Business Media Deutschland GmbH, 2025. p. 333-341 (Lecture Notes in Networks and Systems; Hac. 1531 LNNS).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Assembly Line Balancing Using Fuzzy Mathematical Modeling

AU - Derya, Tusan

AU - Atalay, Kumru Didem

AU - Ucal Sari, Irem

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - This study investigates Assembly Line Balancing problem using fuzzy mathematical modeling. The proposed approach incorporates fuzzy parameters to model imprecise task times and resource constraints, enabling a more realistic representation of variability in the assembly process. A mathematical model is developed using fuzzy sets and solved to minimize cycle time and balance workload across stations. A case study is presented to demonstrate the application of the method, comparing the results with traditional crisp approaches. The findings highlight the advantages of using fuzzy modeling in achieving robust and efficient solutions in uncertain production environments.

AB - This study investigates Assembly Line Balancing problem using fuzzy mathematical modeling. The proposed approach incorporates fuzzy parameters to model imprecise task times and resource constraints, enabling a more realistic representation of variability in the assembly process. A mathematical model is developed using fuzzy sets and solved to minimize cycle time and balance workload across stations. A case study is presented to demonstrate the application of the method, comparing the results with traditional crisp approaches. The findings highlight the advantages of using fuzzy modeling in achieving robust and efficient solutions in uncertain production environments.

KW - Assembly Line Balancing

KW - Fuzzy Mathematical Modeling

KW - Intelligent Manufacturing

UR - https://www.scopus.com/pages/publications/105013082663

U2 - 10.1007/978-3-031-98304-7_38

DO - 10.1007/978-3-031-98304-7_38

M3 - Conference contribution

AN - SCOPUS:105013082663

SN - 9783031983030

T3 - Lecture Notes in Networks and Systems

SP - 333

EP - 341

BT - Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference

A2 - Kahraman, Cengiz

A2 - Oztaysi, Basar

A2 - Cebi, Selcuk

A2 - Cevik Onar, Sezi

A2 - Tolga, Cagri

A2 - Ucal Sari, Irem

A2 - Otay, Irem

PB - Springer Science and Business Media Deutschland GmbH

T2 - 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025

Y2 - 29 July 2025 through 31 July 2025

ER -

Derya T, Atalay KD, Ucal Sari I. Assembly Line Balancing Using Fuzzy Mathematical Modeling. In Kahraman C, Oztaysi B, Cebi S, Cevik Onar S, Tolga C, Ucal Sari I, Otay I, editörler, Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. Springer Science and Business Media Deutschland GmbH. 2025. p. 333-341. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-98304-7_38

Assembly Line Balancing Using Fuzzy Mathematical Modeling

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap