Logforum | 2026
Authors: Phongthiya T.; Jaroon K.; Pinnaratip R.; Mongkolkittaveepol P.
DOI: 10.17270/J.LOG.001346
Journal: Logforum
Year: 2026
Publisher: Poznan School of Logistics
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Background: Limited production capacity within existing factory layouts poses a significant challenge for manufacturers striving to meet rising demand. In the case of a factory producing automotive sensor circuit boards, three product types, Products A, B, and C, are manufactured to serve different automotive sensor applications. The projected demand indicated substantial growth across all three product categories, necessitating an optimized layout to enhance production capacity and operational efficiency. Previous studies have rarely integrated Multi-Criteria Decision-Making (MCDM) methods, such as the Order Preference by Similarity to Ideal Solution (TOPSIS), with Systematic Layout Planning (SLP), despite the potential benefits of incorporating weighted criteria into the layout design process. However, some studies have now examined how such an integrated approach can be applied to improve layout adaptability and capacity expansion under dynamic demand conditions in the automotive electronics industry. Methods: This study applied SLP methodology to develop three alternative factory layout designs. Alternative 1 prioritizes minimizing material movement distances. Alternative 2 prioritizes lower operation costs and faster implementation and Alternative 3 focuses on material movement distance together with the allocation of preparatory workstation close to the Surface Mount Technology product line, which can potentially help improving workflow. The TOPSIS was then applied to evaluate the alternatives, using weighted criteria to determine the most suitable layout. Results: Through the integration of SLP and TOPSIS, Layout Alternative 2 was identified as the optimal solution, achieving the best trade-off among operating cost, installation lead time, and material flow efficiency. Implementation of this layout led to significant capacity improvements, with monthly output increasing by +67% for Product A, +21% for Product B, and +50% for Product C, thereby enabling the factory to meet the forecasted demand. Conclusions: The integration of SLP and TOPSIS provides a robust decision-support framework for plant layout optimization under dynamic demand conditions. The study contributes to theory by extending SLP with weighted MCDM evaluation, and to practice by demonstrating significant capacity gains in a real manufacturing setting. © Wyższa Szkoła Logistyki, Poznań, Polska.
automotive sensors; circuit boards; layout optimization; systematic layout planning; TOPSIS