Simulation-based approach to the optimization of material flows and workstation layout in a manufacturing company

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Authors: Zdenka Bulková, Rudolf Kampf, Jozef Gašparík, Florin Codruţ Nemţanu
Cited by: 1
References: 30

Abstract

• Digital twin–based layout optimization using Tecnomatix Plant Simulation. • Throughput increased by 23% and material travel time reduced by 31%. • Workstation idle time decreased by 17% through layout reconfiguration. • One operator efficiently manages three CNC machines instead of two. • Personnel demand reduced by 40% and capacity created for an additional machine. In the context of increasing production complexity and pressure on operational efficiency, optimizing material flows and workstation layout has become a critical challenge for manufacturing companies. This paper presents a simulation-based optimization approach using a digital twin developed in Tecnomatix Plant Simulation to improve internal logistics and workstation layout in a CNC machining environment. A detailed simulation model of the current production system was created based on real operational data and subsequently used to evaluate alternative layout scenarios. The optimization focused on reducing transport distances, eliminating collision points, and improving labour utilization without additional investment in machinery. Simulation results demonstrate a 23% increase in system throughput, a 31% reduction in material travel time, and a 17% decrease in workstation idle time. Furthermore, the optimized layout enabled one operator to efficiently manage three CNC machines instead of two, resulting in a 40% reduction in required personnel and creating capacity for the installation of an additional production machine. The proposed methodology provides a practical and replicable framework for simulation-driven layout optimization and supports managerial decision-making in small and medium-sized manufacturing enterprises pursuing Industry 4.0 principles.

Fields of Study & Subjects

Digital Transformation in Industry Advanced Manufacturing and Logistics Optimization Flexible and Reconfigurable Manufacturing Systems

Publication details

Journal / source
Results in Engineering
Publisher
Elsevier BV
Volume
30
Pages
110392–110392
Publication date
4 April 2026
Language
EN