An Optimized Design of New XYθ Mobile Positioning Microrobotic Platform for Polishing Robot Application Using Artificial Neural Network and Teaching-Learning Based Optimization

Table 8

Optimum results for three case studies.

TLBO for single-objective problems	Cases	Optimal solutions (mm)	y-stroke (μm)	x-stroke (μm)	Safety factor	Stress (MPa)	Rotation angle (degree)
	Case 1	A = 0.9, B = 0.8, C = 0.6, D = 0.6, E = 50	1558.6763	266.4	1.58	318.35	1.85
	Case 2	A = 0.87, B = 0.7, C = 0.6, D = 0.55, E = 49	1300.6	735.55	2.33	215.87	1.97
TLBO for multi-objective problems	Cases	Optimal solutions (mm)	Stroke (μm)	x-stroke (μm)	Safety factor	Stress (MPa)	Rotation angle (degree)
	Case 3	A = 0.89, B = 7.97, C = 0.6, D = 0.55, E = 45	1568.1	714	2.04	246.56	2.26