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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Research on the influence of robotic manipulation on the uncertainty of product dimension measurements</dc:title><dc:creator>Zore,	Aleš	(Avtor)
	</dc:creator><dc:creator>Munih,	Marko	(Mentor)
	</dc:creator><dc:subject>robot</dc:subject><dc:subject>process measurement</dc:subject><dc:subject>measurement uncertainty</dc:subject><dc:subject>dimensional mea- surement</dc:subject><dc:subject>comparative measurement</dc:subject><dc:subject>robot manipulation</dc:subject><dc:subject>measurement robotization</dc:subject><dc:description>In this doctoral thesis, we present research on the influence of robotic manipulation
on the uncertainty of product dimension measurements. We have been studying a
robotic measurement cell dedicated to statistical process measurements. By robotizing
process measurements, the robot becomes part of the measurement system, and the
properties of the robot directly influence the measurement process. As part of the PhD
thesis, the robot and robot manipulation were considered influential elements in the
uncertainty of object dimension measurements.
The first chapter provides insight into statistical process measurements currently
used in the process industry. Performance criteria for measurement and process control
systems are presented. The introductory chapter concludes with the current state of
the art of robotic process measurement and the fundamental issues of the thesis.
Chapter 2 presents the experimental system used – a robotic cell for statistical
process control. It highlights the key features of the UR5e collaborative robot and
the Renishaw Equator 300 comparative principle based measurement robot (PME).
The chapter describes the two geometrically and dimensionally different types of serial
products considered. The six most critical dimensional characteristics in the daily
statistical process control are followed by a description of the implementation and
evaluation of the measurement system analysis (MSA) procedures. The most common
MSA outputs are the capability parameter Cg, the standard deviation  and the range
of measurements R in the case of the evaluation of the capability of a gauge, and the
repeatability and reproducibility parameter GRR in the case of the verification of the
capability of a measurement process. This is followed by a theoretical demonstration
of measurement uncertainty and metrological traceability in practice.
Chapter 3 of the thesis addresses the initial question of whether robot manipula-
tion impacts dimensional measurements. Nine different manipulation scenarios, ran-
ging from zero manipulation to full manipulation, used the robot as a manipulator to
carry and insert measurement objects into the PME. Each robot manipulation scena-
rio consists of three measurement runs with 25 repetitions, each of which is a robot
manipulation and PME dimensional measurement. The effect of robot manipulation
is discussed based on procedure 1 MSA statistical analysis. In addition to addressing
the complexities of robotic manipulation, the mode of operation (discrete touch and
scan) and PME sampling were addressed separately. As the complexity of the robotic
manipulation increases (adding longer movements, larger changes in orientation, and
multiple grasps), the scatter of the measurements increases. However, no difference
in scatter was detectable for the two modes of operation and for different numbers of
PME sampling points.
In Chapter 4, special attention is paid to the trajectory of the robot’s end-effector.
The way of interpolating the robot’s motion (linear or joint motion), the different ve-
locities of the motion, the length of the motion, and the number of active joints to
perform the robot’s motion are highlighted. The influence on the accuracy and preci-
sion of the robot tip is identified. The error in the accuracy and precision of the robot
tip is detected indirectly through the variability of the dimension measurements. The
more significant variability of the dimension measurements is due to the variability of
the position of the inserted measurement object in the fixture. The captured dimensio-
nal data were analysed using the MSA procedure 1, and the statistical independencies
of the individual influential trajectory parameters are further addressed using the ana-
lysis of variance (ANOVA) method. Each exposed parameter has at least a minimal
influence on the robot’s accuracy and precision or on the uncertainty of the dimensional
measurements.
The last chapter focuses on the robotic grasping operation. An optical measurement
system with two line laser sensors is designed to observe the change of orientation of
an object. In addition to the dimensional measurements, the differences in all three
orientation angles are observed when the robot is only touched and released. The
rotation about the vertical axis of the axisymmetric object is more pronounced in
the self-touch comparison. The rotation about the other two axes is not pronounced.
Considering the variation between touch and release, the differences in the perceived
twist between the different applied gripping forces are practically negligible.</dc:description><dc:date>2024</dc:date><dc:date>2024-09-24 08:30:02</dc:date><dc:type>Doktorsko delo/naloga</dc:type><dc:identifier>162465</dc:identifier><dc:identifier>VisID: 62244</dc:identifier><dc:identifier>COBISS_ID: 219409155</dc:identifier><dc:language>sl</dc:language></metadata>
