Performance analysis in WEDM of titanium grade 6 through process capability index. (14th February 2020)

• Record Type: Journal Article
• Authors: Majumder, Himadri; Maity, Kalipada
• Is Part Of: World journal of engineering. Volume 17:Number 1(2020)
• Page Start: 144
• Page End: 151
• Publication Date: 2020-02-14
• Subjects: Surface roughness -- MRR -- Process capability analysis -- WEDM; Engineering -- Periodicals; 620
• DOI: 10.1108/WJE-04-2019-0126
• Languages: English
• ISSNs: 1708-5284

Abstract

Abstract : Purpose: The purpose of this study aims to obtain excellent products, consistent investigation and manufacturing process control which are the preconditions that organizations have to consider. Nowadays, manufacturing industry apprise process capability index (Cpi ) to evaluate the nature of their things with an expect to enhance quality and also to improve the productivity by cutting down the operating cost. In this paper, process capability analysis was applied during wire electrical discharge machining (WEDM) of titanium grade 6, to study the process performance within specific limits. Design/methodology/approach: Four machine input parameters, namely, pulse ON time, pulse OFF time, wire feed and wire tension, were chosen for process capability study. Experiments were carried out according to Taguchi's L27 orthogonal array. The value of Cpi was evaluated for two machining attributes, namely, average surface roughness and material removal rate (MRR). For these two machining qualities, single response optimization was executed to explore the input settings, which could optimize WEDM process ability. Findings: Optimum parameter settings for average surface roughness and MRR were found to be TON: 115 µs, TOFF: 55 µs, WF: 4 m/min and WT: 6 kg − F and TON: 105 µs, TOFF: 60 µs, WF: 4 m/min and WT: 5 kg − F. Originality/value: Process capability analysis constantly checks the process quality through the capability index keep in mind the end goal to guarantee that the items made are complying with the particulars, providing data for product plan and process quality enhancement for designer and engineers, giving the support to decrease the cost of item failures.