Prediction of Optimal Mild Steel Weld Parameters using the Adaptive Neuro Fuzzy Inference System (ANFIS) Technique.

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher

Abstract

Welding is one of the major operations in many industries as it provides a durable means of joining metals and ensuring that diverse equipments are created to meet the growing needs of the manufacturing industries. To enhance the production of these diverse equipments, studies are continually been performed to identify improved means of obtaining reliable joints. This study applies the Adaptive Neuro Fuzzy Inference System (ANFIS) technique, in improving the predictability of the optimal weld characteristics for a mild steel welded joints, with focus on tensile strength and hardness as responses. From the study, the variation in tensile strength and hardness as a result of the process parameters effects is illustrated, and it reveals the optimal tensile strength and hardness is obtained at the combined input parameters. 170Amp, 20volts, 24l/min, 2.2mm for the tensile strength and 220Amp, 20volts, 20l/min, 2.4mm for the hardness.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-4.0