Date of Award

2-5-2025

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Industrial and Manufacturing Systems Engineering

Keywords

Fuzzy Demand; Fuzzy Set Theory; Hybrid Manufacturing; Product Platform; Variant Substitution

Supervisor

A. Azab

Supervisor

F. Baki

Rights

info:eu-repo/semantics/embargoedAccess

Abstract

This study develops an integrated mathematical formulation for hybrid manufacturing, incorporating product platforms, multi-period lot-sizing, and fuzzy demand to address demand uncertainty and product variation challenges. Applying the fuzzy set theory, demand is modeled as fuzzy demand, providing a more effective approach to handling uncertainty than deterministic methods. The model includes a substitution strategy to accommodate dynamic changes in variant requirements, enhancing production flexibility. This model incorporates safety stock to have better handling features in terms of demand uncertainty. Additionally, based on the developed fuzzy optimization model, the fuzzy model is employed to train a regression model that predicts costs as a function of anticipated confidence levels. The proposed model is validated through two case studies, demonstrating its effectiveness in minimizing total production costs and efficiently managing multiple product variants across different planning periods. The findings offer adaptive production planning strategies for manufacturers facing fluctuating demand and high product variety.

Available for download on Wednesday, February 04, 2026

Included in

Engineering Commons

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