Yakub Mogul Dr

The 4th Industrial Revolution incorporates the digital revolution in several fields, including artificial intelligence, autonomous vehicles, IoT, manufacturing, etc. Due to the advancement in difficult-to-cut materials, technology like abrasive waterjet machine (AWJM) in non-traditional manufacturing has been a benefit to the industry, and it can almost cut any material and is also considered environmentally friendly. The machine uses water, abrasives and electricity which are natural resources, and the purpose of the study is to optimize these resources for the AWJM which are relatively very complex considering the different varying parameters and material properties. The methodology is discussed with a case study of NC 3015S AWJ machine for studying sustainability using different method/tools like SCLM, ABCD and TSPDs approach which will illustrate the combined technical and sustainability assessment. An approach for working with abrasive waterjet machine on reducing cost and machining time which focusses on the four pillars of sustainability (social, economic, environmental and technology) has been presented. The discussions are demonstrated by cost/hour calculations, i.e., 45$/h for machining Ti6AL4V material, and how different machine and cutting parameters affect the total process economy was understood with abrasives contributed almost 65% of the total cost. Furthermore, a cloud-based knowledge sharing model is proposed by linking the sustainability with technology and how it can benefit the current SMEs to improve their productivity with abrasive waterjet machines.

Abrasive water jet (AWJ) cutting has been widely used in industries because of its precise cutting tech- nique. However, the effectiveness of AWJ cutting is dependent on machine operating parameters and the material properties. In this research AWJ cutting was applied on Titanium Ti6AL4V Grade 5 material to investigate the effects on depth of cut (DoC) and roughness. Taguchi L 27 experiments were conducted at three levels with operating parameters such as water pressure, transverse speed, abrasive mass flow rate, abrasive orifice size; a novel approach of ratio 3:1 was adopted with nozzle and orifice diameter to accommodate more parameters for investigation and to inspect the variation of these parameters in real time. Minitab 2017 software was used to simulate the influencing parameters with ANOVA. (GRA) Grey relational analysis linked with Taguchi technique represents a novel approach to optimization. It is a normalization estimation technique extended to elucidate the complex multi -performance character- istics. GRA is used for optimizing the process parameter which helped in determining the optimal param- eters for roughness and depth of cut, ANOVA was used for analyzing the effect of independent variables on dependent variables, as per ANOVA the P values and the S/N ration rank indicated that water pressure was the most influencing parameter for surface roughness and transverse speed was the most influencing parameter for the depth of cut. The prediction of cutting depth through GRA optimization proved a valu- able tool for the controlled depth milling (CDM) in Ti6Al4V material. (c) 2019 Elsevier Ltd. All rights reserved. Selection and peer -review under responsibility of the scientific committee of the 2nd International Con- ference on Recent Advances in Materials & Manufacturing Technologies.