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^*

^*Corresponding author for this work

Baskent University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
Editors	Cengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	333-341
Number of pages	9
ISBN (Print)	9783031983030
DOIs	https://doi.org/10.1007/978-3-031-98304-7_38
Publication status	Published - 2025
Externally published	Yes
Event	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Turkey Duration: 29 Jul 2025 → 31 Jul 2025

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1531 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Country/Territory	Turkey
City	Istanbul
Period	29/07/25 → 31/07/25

Bibliographical note

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Assembly Line Balancing
Fuzzy Mathematical Modeling
Intelligent Manufacturing

Access to Document

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

Cite this

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; Vol. 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. editor / 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).

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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",

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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, vol. 1531 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 333-341, 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, Istanbul, Turkey, 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; Vol. 1531 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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

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AN - SCOPUS:105013082663

SN - 9783031983030

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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, editors, 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

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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