Artificial Intelligence Fuzzy Logic Modeling of Surface Roughness in Plasma Jet Cutting Process of Shipbuilding Aluminium Alloy 5083

Journal Title: Journal of Materials and Engineering - Year 2023, Vol 1, Issue 2

Abstract

In this paper the influence of different process parameters on surface roughness responses in plasma jet cutting process was investigated. Experimentations were conducted on shipbuilding aluminium 5083 sheet thickness 8 mm. Experimental work was performed according to Taguchi L27 orthogonal array by varying four parameters such as gas pressure, cutting speed, arc current and cutting height. Due to complexity of manufacturing process and aim to cover wide experimental space few constraints regarding cutting area were defined. Surface roughness parameters Ra and Rz were analysed as cut quality responses. In order to define mathematical model that will be able to describe effects of process parameters on surface roughness artificial intelligence (AI) fuzzy logic (FL) technique was applied. After functional relations between input parameters and surface roughness responses were defined prediction accuracy of developed fuzzy logic model was checked by comparison between experimental and predicted data. Mean absolute percentage error (MAPE) as well as coefficient of determination (R2) were used as validation measures. Finally, optimal process conditions that lead to minimal surface roughness were defined by creating response surface plots.

Authors and Affiliations

Ivan Peko, Bogdan Nedić, Dejan Marić, Dragan Džunić, Tomislav Šolić, Mario Dragičević, Boris Crnokić, Matej Kljajo

Keywords

Related Articles

Lubricant Droplets Can Bounce on Wetted Cylinders

In this work, the droplet bounce phenomenon of polyalphaolefin, olive oil, silicone oil, and paraffin oil on wetted cylinders was reported. With a uniform oil film with a thickness of 0.06 mm formed on the cylinder, typi...

FOOD PRODUCTS DEFILEMENT ANALYZER USING IOT

In order to make additional, quick profits, shopkeepers frequently adulterate food today. Foods are adulterated by adding things like ripening mangoes, chalk powder to turmeric, starch to curry powder, papaya seeds to bl...

Working Out the Processes of Deposition “MetalMetal“ Multi-Layer Coatings (Cu-Mo, Cu-MoN, Cu-C) and Studying the Tribological Characteristics of Friction Pairs

As part of the program to search for new materials with high characteristics according to Avinit vacuum-plasma technologies, based on the complex use of coating methods (CVD + PVD), stimulated by nonequilibrium low-tempe...

Effect of Shaft Speed, Crack Depth and L/D Ratio in Rotor Bearing System: Using Taguchi Method and ANOVA

Vibration is produced by imbalance, positioning, mechanical softness, shaft cracking, and various defects in spinning machinery. In recent years, rotor defect diagnostics have become more important. This study looks at t...

Tribological Behavior of Cast Aluminum Matrix Composites After Multiple Remelting

One of the limiting factors for expanding the applications of aluminum alloy castings in many high-tech industries is the insufficient level of tribological properties, especially under conditions of dry and abrasive wea...

Download PDF file
  • EP ID EP727412
  • DOI 10.61552/JME.2023.02.005
  • Views 24
  • Downloads 0

How To Cite

Ivan Peko, Bogdan Nedić, Dejan Marić, Dragan Džunić, Tomislav Šolić, Mario Dragičević, Boris Crnokić, Matej Kljajo (2023). Artificial Intelligence Fuzzy Logic Modeling of Surface Roughness in Plasma Jet Cutting Process of Shipbuilding Aluminium Alloy 5083. Journal of Materials and Engineering, 1(2), -. https://europub.co.uk/articles/-A-727412