Digital Twin Implementation for Turntable Systems
in Automated Bottle Production
Thiri Thitsar Khaing
Klab Myanmar
University of Information Technology
Yangon, Myanmar
thirithitsarkhaing@uit.edu.mm
Su Su Naing
Klab Myanmar
University of Information Technology
Yangon, Myanmar
susunaing41@uit.edu.mm
Abstract— This paper explores the design and
implementation of a digital twin for a bottle production line,
focusing on the turntable system used in feeding operations.
Turntables play a critical role in dispatching products one by
one from bulk, and are widely used in bottle filling and capping
machines. We developed a simplified 3D model of the turntable,
which interacts with bottles in a simulated environment based
on real-world physics. The goal was to enhance industrial
automation by simulating physical interactions using advanced
techniques, including C# scripting, and providing a foundation
for integrating digital twins in manufacturing systems. Key
experiments demonstrated the model’s ability to evaluate bottle
stability under varying gravity, rotational speeds, and
controlled spawning conditions, offering insights for optimizing
turntable operations.
demonstrate how digital twins can improve the performance
of turntable systems, reducing costs associated with machine
wear, product wastage, and system downtime.
Keywords— Digital Twin, Turntable, 3D Model, Physics,
Simulation.
I. INTRODUCTION
In today's advanced manufacturing landscape, digital
twin technology has become an integral part of optimizing
and enhancing production processes. A digital twin is a
highly detailed virtual model of a physical system, enabling
engineers to monitor, simulate, and test various aspects of
operations in real-time. By using digital twins, manufacturers
can analyze system performance, predict potential failures,
and make adjustments without causing any disruption to
actual production. This reduces downtime and enhances the
overall efficiency of manufacturing lines.
Originally proposed by Grieves, the digital twin concept
involves continuous synchronization between the physical
asset and its digital counterpart, providing significant benefits
across the entire lifecycle of a product or system [1]. In
manufacturing, digital twins facilitate production planning,
process control, and predictive maintenance, becoming key
enablers of Industry 4.0 and Smart Manufacturing [2].
Despite these
advantages,
challenges
remain
in
implementing digital twins, particularly in modeling and
synchronizing complex processes.
This paper focuses on the design and development of a
digital twin for a turntable system within a bottle production
line. Turntables, critical components of feeding systems in
automated manufacturing, manage product flow and ensure
the orderly dispatch of bottles. These systems are responsible
for aligning, rotating, and directing bottles with precision to
minimize downtime and improve throughput. In this study,
the turntable system was modeled to simulate and optimize
these operations. The integration of a digital twin enables
detailed simulation of turntable dynamics, allowing engineers
to optimize settings, troubleshoot potential issues, and
enhance operational efficiency. The study aims to
979-8-3315-3459-2/25/$31.00 ©2025 IEEE
In recent years, the concept of digital twins has gained
significant traction across various industries, especially in
manufacturing and industrial automation. Digital twins serve
as virtual replicas of physical systems, enabling real-time
monitoring, simulation, and optimization of processes
without interfering with the actual production. This
innovative approach has been particularly impactful in
sectors such as automotive, aerospace, and consumer goods,
where precision and efficiency are crucial. Despite the
growing interest in digital twin technology, significant
challenges remain in its implementation, particularly within
the process industry, due to the complexity of accurately
representing and modeling the underlying production
processes. Some studies have highlighted the enabling factors
and barriers to successful digital twin implantation in
industries, offering conceptual models to address there
challenges and guide future applications [3].
The need for a reliable digital twin to simulate turntable
processes has become increasingly important for optimizing
machine performance, reducing downtime, and increasing
overall productivity. The turntable digital twin is built upon
the principles of Digital Virtualization, which serves as the
foundational layer for digital twin implementation [4]. In this
layer, information about target objects in the real world is
collected, transferred to a digitalized virtual world, and
processed for analysis and visualization. Leveraging this
concept, the design focuses on simplifying the simulation to
concentrate on core functionalities.
II. BACKGROUND
The concept of Digital Twin (DT) emerged as a
transformative technology bridging the physical and digital
worlds. First proposed by Grieves in 2002 and formally
conceptualized in 2014, a digital twin is defined as a highly
accurate virtual representation of a physical system, designed
to mirror its real-time state and behavior [1].
A. Evolution of Core Principles of Digital Twin
Digital twins originated in the aerospace sector for
simulating and monitoring complex systems, such as aircraft
engines. Over time, this technology has evolved into a
general-purpose tool applicable across industries, including
manufacturing, healthcare, city planning, and automotive
design [5].
A DT consists of three key components:
Physical Entity: The real-world system or object being
mirrored.
Digital Model: The virtual counterpart created using advanced
modeling techniques and real-time data.
Data Connection: The bi-directional flow of data between the
physical and digital entities.
The continuous synchronization of data ensures that the
digital twin accurately reflects the operational state of the
physical system, enabling users to perform what-if scenarios,
optimize processes, and predict failures [6].
B. Applications across the Product Lifecycle
Design Phase: Engineers use DTs for virtual prototyping and
simulation to test product concepts, minimizing development
time and cost [7].
Manufacturing Phase: DTs support production planning,
process optimizing, and predictive maintenance to improve
efficiency and reduce downtime [8].
Operation and Maintenance: Real-time monitoring and
analysis using DTs enable condition-based maintenance,
reducing unexpected failures and extending asset lifespan
[9].
C. Challenges in Digital Twin Implementation
Despite the benefits, implementing digital twins in
practical settings remains a challenge:
Data Integration: Combining data from diverse sources (e.g.,
Internet of Thing sensors, SCADA systems) into a unified
model requires robust frameworks and interoperability
standards [10].
Scalability: Scaling DTs for large and complex systems, such
as smart cities or industrial plants, requires high
computational power and efficient data management systems
[11].
Modeling Accuracy: Developing precise virtual models for
dynamic, non-linear processes can be computationally
intensive and requires domain expertise [7].
D. Digital Twin and Industry 4.0
The integration of digital twin technology with Industry
4.0 has led to the development of Smart Manufacturing
systems. These systems leverage Internet of Thing, big data
analytics, and artificial intelligence to enable predictive
maintenance, resource optimization, and adaptive
manufacturing processes. For example, in a bottle production
line, digital twins can simulate the behavior of systems such
as turntable, optimizing the movement and dispatching of
bottles in real-time [8].
E. Future Trends
The next generation of digital twins aims to incorporate
advanced technologies such as edge computing, block chain
for data integrity, and AI-driven decision-making. These
advancements will enable more autonomous and resilient
systems capable of self-optimization and real-time adaptation
to dynamic environments [9].
III. RELATED WORKS
Some studies have highlighted the enabling factors and
barriers to successful digital twin implementation in
industries, offering conceptual models to address these
challenges and guide future applications.
In recent years, the physically based simulation has been
developed and applied to various engineering processes. So
far, the use of this simulation method was limited to
calculating the behavior of objects with large dimensions, as
the calculation of small objects leads to severe inaccuracies.
However, technical systems often consist of a variety of small
functional components and work pieces. A method proposed
by Hofmann and Reinhart [12] addresses these challenges by
introducing scaling equations that improve the accuracy of
physically based simulations for small objects. Their
approach enables more precise testing and optimization of
small components, significantly reducing time and costconsuming experiments.
Motivated by the growing need for comprehensive digital
twin models in design and production engineering, Schleich
et al. [13] propose a reference model that serves as a digital
twin of the physical product. This model incorporates
important properties such as scalability, interoperability,
expansibility, and fidelity. Additionally, it addresses various
operations throughout the product life-cycle, including
composition, decomposition, conversion, and evaluation. The
application of this model to geometrical variations
management further highlights its relevance to the
manufacturing process.
The concept of digital twins has been successfully
applied to simulate industrial production lines within the
framework of Industry 4.0. Vachálek et al. [14] presented a
digital twin for the manufacturing process of pneumatic
cylinders, encompassing stations for material handling,
drilling, quality control, sorting, manual assembly, and
packaging. Their work demonstrated the versatility of digital
twins in modeling diverse production processes, including
variations in material types, component sizes, and color
coding for enhanced recognition. This study serves as a
foundational reference for leveraging digital twin technology
in replicating physical systems.
IV. DESIGN AND SET UP OF THE TURNTABLE DIGITAL TWIN
In the digital twin of the turntable configuration, the round
table is rotated solely through a C# script, eliminating the
need for a motorized model in the simulation. The design
integrates a frame and barrier system to control the flow of
bottles toward a conveyor path. At the center of the table, a
curved barrier, designed with two opposing curves, ensures
bottles are guided in the rotational direction. This directs
them effectively, toward the output path of the feeding
system, maintaining smooth and controlled bottle movement.
The model is intentionally simplified to concentrate on its
primary functions, particularly rotation and bottle
interactions.
In a full-scale industrial production line, turntables often
feature additional components designed to optimize
efficiency and accuracy in handling bottles. One common
addition is a central barrier, which plays a crucial role in
directing the bottles outward, ensuring smooth and controlled
movement through the system. These barriers, along with
other specialized mechanisms, are essential for managing
high speed operations and preventing bottlenecks or
misalignments as bottles transition between different stages
of production.
However, for the purpose of this project, a simplified
version of the turntable has been implemented, focusing on
the foundational concepts of digital twin design. It should be
pointed out that a digital twin does not necessarily require a
full smart product; even for simple products, such as
individual components, digital twins can be implemented [8].
Despite the absence of more advanced components, this
simplified model still provides valuable insights into key
design principles. These include the physical interactions
between the turntable, barrier, and the bottles, which are
central to replicating real-world dynamics. Additionally, the
model highlights the importance of animation in simulating
the movement of objects within the system, making it
possible to visualize the rotational movements and how they
affect the flow of bottles.
Furthermore, the use of C# scripting to control the
rotational movement is a critical aspect of this digital twin.
The script not only allows for precise control over the
turntable's behavior but also enables the simulation of realtime adjustments to factors like speed and direction. This
scripting component is fundamental in demonstrating how
digital twins can bridge the gap between the physical and
digital realms, providing a virtual environment to test and
optimize industrial processes without the need for costly
physical prototypes. Overall, this simplified turntable model
serves as an effective teaching tool, introducing essential
concepts of digital twin technology that can be scaled and
applied to more complex production systems.
As a result, the system was capable of producing realistic
bottle interactions, where bottles moved in response to the
disk’s rotation and reacted to physical barriers, providing a
close approximation to how the system would behave in an
actual production environment.
B. Scripting and Simulation Workflow Explanation
The flowchart for the turntable digital twin simulation
outlines the sequential steps involved in creating and
managing the virtual simulation environment. The workflow
begins with the initialization of the turntable and bottle
spawning system, setting up the foundation for the
simulation. C# Script Integration: The C# script plays a
crucial role in the workflow by controlling the rotation of the
turntable disk and spawning bottles. Specifically, the script
applies continuous rotational force to the disk, simulating
real-world spinning, and creates new bottles at designated
positions. This automation of bottle spawning and disk
rotation is central to the flowchart’s simulation process.
Spawn Bottle: New bottles are generated at designated
positions on the turntable using the C# script.
Rotate Turntable Disk: The C# script applies rotational force
to the turntable disk, simulating spinning around the z-axis.
Bottle Interaction: Physics interactions, including colliders
and rigid bodies, are managed within Unity, ensuring realistic
behavior as defined by the flowchart.
Gravity Check: Gravity settings are adjusted to reflect
realistic bottle movement and falling behavior.
A. 3D Model and Physical Environment Setup
The 3D model of the turntable system was developed
using CAD files, which were then imported into the
simulation environment. Once the model was in place, the
physical environment had to be configured to allow for
accurate physics-based interactions.
This involved assigning mesh colliders to define the
physical boundaries of the objects and rigid bodies to ensure
that the system adhered to the laws of physics, such as mass,
gravity, and collision behavior.
To simulate the turntable disk's rotation, a custom script
was written to drive its movement around the z-axis. This
script utilized pure physics principles, ensuring that the
rotational motion of the disk would interact naturally with the
bottles, replicating real world dynamics.
Fig. 2. Flowchart for turntable digital twin simulation
Fig. 1. Simplified 3D model of the turntable
Collision with Barrier: The simulation detects bottle
collisions with barriers, guiding bottles out of the system
when necessary. This detection is facilitated by the physical
properties set in the simulation environment.
End Simulation Cycle: Following each cycle, the system
waits for a set interval before repeating the bottle spawning
and rotation steps, as outlined in the flowchart.
The first experiment investigates the influence of varying
gravity levels on bottle stability under a fixed rotational
speed, the second evaluates the effect of rotational speed on
bottle stability across different speeds, and the third examines
the impact of controlled bottle spawning on tilt angles
distribution. These experiments aim to assess the model’s
performance and provide insights into its behavior under
varying operational conditions.
The workflow concludes with the stopping of the
simulation and a review of the results. By linking the C#
script functionalities to the flowchart’s steps, the simulation
accurately reflects the operational dynamics of the physical
turntable system, providing valuable insights for optimizing
bottle production processes.
The factors of gravity, and bottle spawning were selected
due to their significant impact on the system’s dynamics.
Gravity affects the stability of bottles on the turntable,
rotational speed dictates the throughput and efficiency, and
bottle spawning frequency influences the overall production
flow and synchronization.
C. Description in the Abstract Terms for the Paper
The bottle spawning and disk rotation process was
implemented using a simple event-driven loop that
continuously spawns bottles at regular intervals and applies
rotational movement to the turntable disk. Using physics
based properties such as colliders and rigid bodies, the bottles
interact naturally with the rotating disk and barrier,
simulating a real-world production environment. Bottles are
released from the system when they collide with the barrier,
mimicking how actual turntables guide products out of
feeding systems.
The relationship between tilt angle and rotational speed
(RPM) is a critical aspect of system dynamics, as tilt angles
can significantly influence performance and stability.
Theoretically, as the tilt angle increases, the balance of the
rotating system may be affected due to the shifting distribution
of forces, potentially leading to increased stress on
components. This could result in vibrations or oscillations that
affect efficiency and rotational stability. Furthermore, higher
tilt angles might introduce additional gravitational or inertial
forces that could either enhance or hinder rotational speed,
depending on the system's design and operational parameters.
Understanding this interaction is crucial for optimizing
performance and ensuring structural integrity during
operation.
The development and testing of the digital twin for the
turntable system were conducted using the following
software and hardware setup:
Software
Unity Hub 3.8.0— Utilized for creating and simulating the
digital twin model, providing a platform to visualize and test
the turntable system’s interactions.
Microsoft C#— Employed for scripting the rotational
movements and physical interactions of the turntable,
enabling realistic simulation based on pure physics.
Blender 4.3— Used for designing and modeling the 3D
turntable system, allowing for detailed and accurate
representation of the physical components.
Hardware
The setup in TABLE I. provided the necessary
computational resources and software tools required to
accurately develop, simulate, and test the digital twin model
of the turntable system. By combining Unity for simulation,
Microsoft C# for scripting, and Blender for 3D modeling,
along with the specified hardware, ensured effective execution
of the project tasks and analysis.
A. Effect of Gravity on Bottle Stability
This first experiment investigates how varying
gravitational forces, ranging from Earth’s standard gravity of
-9.81 m/s2to an extreme value of -90.81 m/s2, affect the tilt
angle of a bottle placed on a rotational turntable operating at
a constant speed of 10 RPM. The goal was to evaluate the
stability of the bottle by analyzing deviations in its tilt angle
under different conditions.
The results, as depicted in Figure 3, show that for most
gravity values, the tilt angle remains close to 90 degrees. This
indicates that the bottle maintains an upright position with
minimal deviation. This consistency demonstrates the
robustness of the model and its capability to preserve stability
despite increased gravitational forces.
However, under the extreme gravity of -90.81 m/s2, the
tilt angle decreases to approximately 83.65 degrees,
suggesting a slight compromise in the bottle’s upright
stability. This reduction could be attributed to increased
downward force influencing the interaction between the
V. RESULT AND DISCUSSION
This section presents the findings of three critical
experiments conducted on the turntable simulation model.
TABLE I.
Component
Device
Processor
Installed RAM
System Type
HARDWARE DETAILS
Specification
Laptop
11th Gen Intel® Core™ i7-1165G7 @ 2.80GHz
8GB
64-bit Operating System
Fig. 3. Effect of gravity on bottle tilt angles
bottle and the turntable possibly due to heightened friction or
structural stress.
Overall, the bottle displays consistent stability across the
gravity spectrum, with only minor deviations under extreme
conditions, validating the model’s reliability under varying
gravitational forces.
B. Effect of Rotational Speed on Bottle Stability
The second experiment evaluates the impact of rotational
speed on bottle stability by analyzing tilt angles under
different speeds.
The height at which the bottle is released will impact its
falling time, given the equation of motion for gravity:
1
d = 𝑔𝑡
2
2
(1)
Where:
d is the distance the bottle falls
g is the gravitational acceleration,
t is the time it takes to fall.
The tests were conducted at standard Earth gravity which is 9.81 m/s2, and a fixed rotational speed ranging from 10 RPM
to 60 RPM, as depicted in Figure 4.
For each speed, tilt angle data for three bottles were
collected and analyzed. At low speeds, the tile angles are
relatively small, indicating higher stability. As the speed
increases, the tilt angles rise significantly, with the highest tilt
angle reaching 20.08 degrees at 60 RPM. This demonstrates a
clear positive correlation between rotational speed and tilt
angle, indicating that higher speeds lead to reduced stability
due to increased centrifugal forces. The results indicate that
while moderate tilt angles may optimize performance,
exceeding critical values in combination with high RPMs
poses risks to both efficiency and structural integrity. Further
analysis is required to determine the precise tile angle and
RPM combination that maintain system stability without
sacrificing performance.
Additionally, slight variations in tilt angles across bottles
at the same speed were observed, likely caused by minor
inconsistencies in bottle placement or the turntable
mechanism. Despite these variations, the time for each test
remained consistent, suggesting the system is stable and
performs reliably under different speed conditions.
Fig. 4. Effect of rotational speed on bottle tilt angles
C. Controlled Bottle Spawning and Distribution of Tile
Angles
The third experiment focuses on controlling the bottle
spawning process to ensure that 10 bottles are consistently
placed in the same location on the turntable at the start of each
experiment, as shown in Figure 5. This controlled spawning
eliminates variability due to inconsistent placement, allowing
for a more accurate analysis of tilt angles under varying
rotational speeds.
The histogram in Figure 6 illustrates the distribution of tilt
angles after the bottles were uniformly placed in the same
location. This setup ensures that each bottle starts with the
same initial conditions, subjecting all bottles to identical
rotational forces and minimizing position-related variations.
As shown in the histogram, the tilt angles cluster around
specific values, with most tilt angles grouped at the lower end
and a few higher values.
This reduced spread in tilt angles indicates that the
controlled spawning process has effectively minimized
variability, making the data more consistent compared to
randomly placed bottles. The improved consistency allows
for a clearly understanding of how rotational speed and
gravity influence bottle stability.
By eliminating the effect of positional variation, the
controlled spawning process provides more reliable data and
enables better assessment of the relationship between speed
and tilt angle. This approach is critical for ensuring the future
experiments yield accurate, reproducible results, facilitating
the optimization of turntable systems for industrial
applications.
These findings highlight the trade-off between speed and
stability. While increasing rotational speed can enhance
production efficiency, it also introduces the risk of bottle
tipping, particularly at higher speeds. These insights are
essential for optimizing turntable operations and designing
stable, high-performance production systems.
The digital twin model of the turntable system
successfully simulated bottle behavior under varying gravity
and rotational speed conditions. Adjustments to physical
properties enhanced the simulation’s realism, showcasing the
potential of digital twins in industrial automation. The
findings offer a virtual platform for testing and refining bottle
production processes, ensuring efficiency and reliability in
real-world applications.
Fig. 5. Controlled spawning of 10 bottles
industries. Specifically, the turntable system is explored as a
case study to demonstrate how digital twins can improve
operational efficiency and serve as a stepping stone toward
more advanced automation solutions in Myanmar’s industrial
sector.
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[1]
Fig. 6. Distribution of bottle tilt angles
VI. CONCLUSIONS
The digital twin created for the turntable in a bottle
production line offers valuable insights into the integration of
physical and virtual environments. By simulating real-world
physics, the digital twin allowed for testing and refining
bottle handling mechanisms without the need for physical
prototypes.
The results from this work demonstrate the
turntable simulation model’s ability to accurately simulate
bottle behavior under varying operational conditions. The
experiments reveal that the model can maintain bottle
stability across different gravity levels, but hat increased
rotational speed reduces stability due to higher centrifugal
forces. Additionally, the controlled spawning process proves
essential for obtaining consistent tilt angle data which is
critical for optimizing turntable operations.
The insight gained from these findings not only validate
the robustness and reliability of the digital twin model but
also offer valuable guidance for improving real-world bottle
production processes. The controlled experiments, combined
with the ability to simulate these conditions in a virtual
environment, lay the groundwork for more efficient and
stable industrial automation systems. The potential of digital
twin technology to enhance operational performance in
production environments is clear, offering a powerful tool for
process optimizing and innovation.
This publication stems from the implementation of the
National Export Strategies project, which focuses on the
application of digital twin technology to bottle production
lines, a key initiative carried out in KLab Myanmar. This
project aims to address Myanmar's growing demand for
technological innovation and export competitiveness by
advancing digital solutions that can be scaled across various