A Reverse Logistics Inventory Model with Multiple Production and Remanufacturing Batches under Fuzzy Environment
Authors :- S Sharma, SR Singh, M Kumar
Publication :- RAIRO-Oper. Res., Volume 55, Number 2, March-April 2021
Ever-growing needs in pipeline welding relating to quality, frequent usage of advanced, heat-sensitive, and corrosion-resistant materials alongside high production costs encourage the evaluation of a welding process thoroughly. The only way to overcome those problems is the adaptation of technically evolved welding methods that combine the goodness of cutting-edge power supply sources and advanced software configuration. One such technique is Regulated Metal Deposition (RMDTM) welding. In this context, the current study explores the influence of the regulated metal deposition (RMDTM) welding variables on ASME SA387-11-2 steels. Current (A), voltage (V), and gas flow rate (GFR) are preferred regulated metal deposition (RMD™) welding variables, and at the same time the depth of penetration (DOP), heat-affected zone (HAZ), bead height (BH), and bead width (BW) are incorporated as performance evaluation attributes. Furthermore, the exploration of Rao algorithms is presented to evaluate the optimal welding settings. The obtained optimal welding settings is current = 92 A, voltage = 13 V, and gas flow rate = 21 litre/min. The results are also compared with the JAYA, and teaching learning-based optimization (TLBO) approaches to show the efficacy of the intended approach.