Marwa El-Mahalawy, M. Samuel, N. Fouda, Sara El-Bahloul,
Volume 32, Issue 2 (IJIEPR 2021)
Abstract
Abstract: Wire Electrical Discharge Machining (WEDM) is a non-traditional thermal machining process used to manufacture irregularly profiled parts. Machining of ductile cast iron (ASTM A536) under several machining factors, which affect the WEDM process, is presented. The considered machining factors are pulse on time (Ton), pulse off (Toff), peak current (Ip), voltage (V), and wire speed (S). To optimize the machining factors, their setting is performed via an experimental design using the Taguchi method. The optimization objective is to achieve maximum Material Removal Rate (MRR) and minimum Surface Roughness (SR). Additionally, the analysis of variance (ANOVA) is used to identify the most significant factor. Also, a regression analysis is carried out to forecast the MRR and SR dependent on defined machining factors. Depending on consequences, the best regulation factors for reaching the maximum MRR are Ton = 32 μs, Toff = 8 μs, Ip = 4 A, S = 40 mm/min. and V = 70 volt. Whereas, the optimal control factors that achieve the minimum SR is Ton = 8 μs, Toff = 8 μs, Ip = 2 A, S = 20 mm/min, and V= 30 volt. It is hypothesized that the perfect combination of control factors that achieves minimum SR and maximum MRR is Ton = 8 μs, Toff = 8 μs, Ip=5 A, S=50 mm/min. The microstructure of the machined surface in the optimal machining conditions shows a very narrow recast layer at the top of the machined surface.
André Guimarães, Ana Carolina Silva, João Pedro Teixeira, Filipe Gomes, Samuel Martins,
Volume 37, Issue 3 (IJIEPR- In Progress 2026)
Abstract
In the evolving landscape of Industry 4.0, Autonomous Mobile Robots (AMRs) are emerging as key enablers of innovation in intralogistics, particularly in material transport operations. These systems operate within innovative production environments where a central controller oversees high-level planning, while AMRs act with autonomy, interacting directly with equipment and systems to support decentralized operations. This shift challenges traditional planning and control practices by introducing new dynamics in decision-making. The present study investigates the implementation potential of AMRs for supplying assembly lines at the XYZ factory through simulation-based analysis. Rather than solely benchmarking against existing methods, the research aims to validate the efficiency and practicality of AMRs in this context. Several simulation models were built and iteratively refined using the SIMIO platform to examine different logistics configurations and scenarios. The insights derived from these simulations offer valuable support for decision-makers, helping to identify optimal setups and assess how AMR deployment compares to conventional intralogistics approaches regarding performance and flexibility.
