DIRECTIONAL EFFECTS IN ROBOTIC MILLING OF UHMWPE: AN EMPIRICAL STUDY ON SURFACE ROUGHNESS
Abstract
Industrial robots offer large workspaces and flexibility for machining, but their compliance-dominated dynamics can compromise surface quality. While vibration control in robotic machining is well studied for metals and fibre-reinforced composites, empirical guidance for soft-polymer finishing remains limited. As one of the first empirical studies on robotic finishing of UHMWPE, this work investigates the direction–compliance–roughness interaction by framing feed direction as a controllable parameter. This study explicitly demonstrates how feed direction interacts with pose-dependent compliance to systematically influence surface roughness in robotic milling of UHMWPE. This feasibility study investigates how feed direction affects surface roughness (Ra, Rq, Rz) in robotic milling of UHMWPE. Experiments were performed using a KUKA KR120 R2700 six-axis robot with fixed parameters: 9500 rpm spindle speed, 1080 mm/min feed rate, and dry finishing cuts at depths of 0.1, 0.2, and 0.3mm. Surface roughness metrics were measured via contact profilometry using a standardized evaluation length. Due to kinematic constraints, X–Y toolpaths require different joint configurations; therefore, observed differences reflect the combination of feed-direction and pose-dependent stiffness anisotropy. Y-direction feeding produced lower Ra (1.64–1.87 µm) than X-direction feeding (1.66–1.94 µm). In contrast, X-direction feeding yielded lower Rq (2.0–2.5 µm) with strong linear predictability (R² > 0.99), compared with Y-direction Rq (2.35–2.40 µm). Rz exhibited depth-dependent behavior, with X performing better at shallow depth (0.2 mm) and Y at 0.3 mm, while tool adhesion showed little directional dependence. Overall, the findings provide evidence of direction-dependent roughness trade-offs: Y-direction may be preferred for average smoothness (Ra), whereas X-direction may be preferred when peak-sensitive control (Rq/Rz) is critical.
Fields of Study & Subjects
Advanced Surface Polishing Techniques
Robot Manipulation and Learning
Advanced machining processes and optimization
Publication details
- Journal / source
- International Journal of Innovation and Industrial Revolution
- Publisher
- Global Academic Excellence (M) Sdn Bhd
- Volume
- 8
- Issue
- 24
- Pages
- 357–357
- Publication date
- 18 March 2026