Experimental Investigation and Performance Optimization during Machining of Hastelloy C-276 Using Green Lubricants

Area of Science:

• Materials Science and Engineering
• Manufacturing Engineering
• Sustainable Manufacturing

Background:

• Industry 4.0 emphasizes smart manufacturing, requiring efficient processing of difficult-to-cut materials like superalloys.
• Hastelloy C-276 is a critical superalloy with limited machining data, posing challenges for sustainable production.
• Sustainable machining aligns with Sustainable Development Goal 12 (SDG-12).

Purpose of the Study:

• To investigate the machining performance of Hastelloy C-276 under minimum quantity lubrication (MQL).
• To analyze the effects of MQL on surface quality, thermal aspects, and chip reduction coefficient.
• To optimize machining parameters for sustainable production of Hastelloy C-276.

Main Methods:

• Experimental examination of Hastelloy C-276 turning using various oils under MQL.
• Optimization of output responses using Response Surface Methodology (RSM) and Analysis of Variance (ANOVA).
• Scanning Electron Microscopy (SEM) for tool wear analysis.

Main Results:

• Cutting speed (24.26%) and feed rate (60%) were dominant factors influencing machining performance.
• Depth of cut and lubricant type had a moderate influence (10-12%).
• Minimal temperature variation was observed, but significant differences in surface roughness and chip reduction coefficient were noted. Tool wear (coating, nose, flank) occurred across all conditions.

Conclusions:

• The developed RSM model is effective for optimizing Hastelloy C-276 machining, achieving high desirability (0.88) with low error (<5%).
• Feed rate and cutting speed are critical parameters for controlling surface quality and chip morphology in MQL.
• Implementing circular economy principles can mitigate the economic, ecological, and environmental impact of machining processes.