03276ntm a2200337 i 4500 MY-KuUP 20260219143744.0 t||||fr|||| 000 0 ta 260219t20252025my a|||fr|||| 000 0 eng d THE0010348 (Local) Hardback UMPSA eng UMPSA rda FIM .N39 2025 r Thesis Ahmad Nazif Bin Noor Kamar, author. Evaluating production process improvement strategies: utilizing discrete event simulation and system dynamics approaches in a manufacturing sme / Ahmad Nazif Bin Noor Kamar Kuantan, Pahang : UMPSA, 2025 © 2025 xii, 182 pages : illustrations ; 30 cm. + 1 CD-ROM rdacontent text rdamedia unmediated rdacarrier volume rda text file PDF Faculty of Industrial Management Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025 Includes bibliographical references Global manufacturing continues to evolve under the pressures of intensified competition, rapid technological advancement, and evolving customer expectations. While large firms have re-evaluated and transformed their operations using advanced technologies to improve production efficiency and maintain competitiveness, small and medium-sized enterprises (SMEs) often face difficulties due to constrained resources. The current work focuses on an SME specializing in aluminium casting products that struggle to meet monthly production targets. A hybrid simulation approach was adopted, combining discrete-event simulation (DES) and system dynamics (SD), to examine both operational inefficiencies and strategic capacity decisions. The DES model replicated the current production process and revealed that a 71% reduction in total production time was necessary to meet existing demand. While, the SD model assessed the long-term impacts of combining improvement strategies, which enabled the SME to potentially expand its capacity to 8,000 units per month. Combining DES and SD provided a comprehensive decision-support framework that addresses both short-term operational issues and long-term strategic planning. The novelty of this study lies in applying a sequential interaction mode of hybrid simulation within a real-world SME manufacturing context, where the output of one simulation model serves as the input for another. This approach allowed for a holistic evaluation of multiple improvement strategies across different decision levels, facilitating scenario-based planning and supporting data-driven decision-making with minimal investment. Future research could apply the proposed hybrid simulation approach across diverse industrial contexts to validate its generalizability and effectiveness. Such efforts would contribute to a broader empirical foundation and strengthen the body of knowledge concerning the scalability, adaptability, and practical application of hybrid simulation methods in implement process improvement. Faculty of Industrial Management Dissertations Universities and colleges Dissertations Theses Dissertations lcc THESIS 0 0 lcc 0 1 0 10000 10000 2026-02-19 0 FIM .N39 2025 r Thesis T000004102 2026-02-19 14:38:17 2026-02-19 RESTRICT 0 0 lcc 0 1 6 10000 10000 2026-02-19 0 CD13963 T000004103 2026-02-19 14:38:50 2026-02-19 RESTRICT 104202 104208