Concurrent multi-response optimization of austenitic stainless steel surface roughness driven by embedded lean and green indicators

• Lean and green profiling of four controlling factors for surface roughness.
• Responses include surface roughness, energy and coolant consumption and drilling time.
• Non-linear multi-factorial multi-response fractional factorials are used.
• Concurrent optimization is effected through nonparametric aggregation methods.
• Lean and green solution promotes the feed rate (at 70 mm/min) and the spindle speed (at 350 rpm).

International ecodesign initiatives encourage drilling process improvements that are also attentive to energy and peripheral materials consumption. A stainless-steel heat-exchanger component is optimized for surface quality during drilling while taking into account lean-and-green improvements. A non-linear four-factor fractional factorial scheme has been utilized to investigate the surface roughness performance due to: 1) the feed rate, 2) the spindle speed, 3) the twist drill type and 4) the coolant concentration. We address simultaneously the cumulative effect of multiple consecutive drillings on the surface quality of the last machined hole of a tube-sheet test plate. The concurrent optimization effort regulated the weighted surface quality performance of the drilling process by suppressing consumptions for: 1) energy – monitored at the final drilling and 2) coolant fluid. The weighted distribution-free optimization scheme was repeated to compound information from a key lean process indicator, the drilling processing time. It was found that the feed rate (at 70 mm/min) and the spindle speed (at 350 rpm) commonly influence non-linearly the surface roughness response (predicted at 1.05 μm) in both multi-response scenarios. The drill type (Guhring No. 8520) was also a statistically important effect when excluding optimality with respect to improved lean and green process performance. In such a case, the spindle speed needed to be decreased to 300 rpm for a predicted surface roughness of 0.86 μm (confirmed within 3%).