Octavian Bologa
Papers
12
Total Citations
113
H-Index
5
About
Octavian Bologa is a researcher whose work sits at the intersection of robotics, advanced manufacturing, and intelligent systems. His research spans two interconnected domains: the kinematics of redundant robotic manipulators and the application of industrial robots in non-traditional machining and forming processes. Bologa has made notable contributions to solving the complex inverse kinematics problem of 7-degree-of-freedom robotic arms, employing sophisticated computational approaches including Fuzzy Logic, Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Simulink-based modeling — work that has collectively garnered over 30 citations. His most impactful contribution, "Selecting Industrial Robots for Milling Applications Using AHP" (2017, 41 citations), introduced a structured decision-making framework that helps engineers identify suitable robots for continuous-path machining tasks — a significant advance as industrial robots increasingly challenge traditional CNC equipment. Further extending this work, he explored multi-process selection combining AHP and fuzzy logic to compare CNC milling, robot milling, and additive manufacturing. Bologa has also investigated incremental sheet metal forming using robotic platforms, demonstrating a versatile interest in expanding the functional boundaries of industrial robots. His body of work offers valuable practical guidance for engineers navigating today's rapidly diversifying manufacturing landscape.
Research Focus
Key Achievements
Top Papers
- 1Selecting industrial robots for milling applications using AHP41 citations · 2017
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- 4The inverse kinematics solutions of a 7 DOF robotic arm using Fuzzy Logic13 citations · 2012
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- 7FEM RESEARCHES REGARDING INCREMENTAL FORMING PROCESS3 citations · 2013
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- 9Another Approach for Redundancy Resolution of a 7 DOF Robotic Arm2 citations · 2015
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