Semi-Automated Pottery Making Machine Design
and Control
1. Introduction to Semi-Automated Pottery Making
1.1 Background and Motivation
Pottery production, an ancient craft, faces challenges with traditional manual methods:
Low Production Rates: Manual labor limits output.
Inconsistent Product Quality: Reliance on artisan skill leads to variations in dimensions and
thickness.
Physical Effort: Repetitive motions can cause musculoskeletal injuries.
High Cost of Full Automation: Industrial automation is expensive and unsuitable for small-scale
artisans.
This thesis addresses these issues by designing and simulating a semi-automated pottery making
machine. The goal is to enhance efficiency and consistency while preserving artisan involvement and
affordability.
1.2 Problem Statement
The traditional pottery industry is hindered by:
High physical strain on artisans, leading to injuries.
Inconsistent product quality due to manual skill dependence.
Unsuitability of expensive, complex industrial automation for small workshops.
There's a need for intermediate, affordable technology that balances manual craftsmanship with
automation, reducing physical effort and improving precision.
1.3 Objectives of the Study
1.3.1 General Objective
To design, model, and simulate a semi-automated pottery assistance machine that improves precision,
repeatability, and efficiency by integrating a stable rotating wheel, a programmable guiding mechanism, and
a controlled shaping unit. The system aims to reduce manual effort while allowing artisan creativity. A PIDbased control system will ensure stable operation.
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1.3.2 Specific Objectives
Design a detailed mechanical model using CAD (SolidWorks).
Implement an Arduino Uno-based control system for precise guiding arm motion.
Develop a mathematical model using Euler-Lagrange for system dynamics and stability analysis.
Design and simulate a PID controller using MATLAB/Simulink for wheel speed and guiding arm
motion.
Evaluate system performance through experimental testing.
Fabricate and validate a working prototype.
1.4 Scope of the Thesis
The project focuses on:
Mechanical Design: Structural frame, rotating wheel, guiding arm, shaping mechanism using
SolidWorks.
Control System: Arduino Uno integration with DC motor, stepper motor, sensors for wheel rotation
and guiding mechanism control.
Control Design: PID controller design and simulation in MATLAB/Simulink for speed stability and
motion accuracy.
Dynamic Modeling: Euler-Lagrange method for analyzing drive and motion system performance.
Functionality: Assisting artisans by reducing effort, minimizing errors, and improving consistency,
while allowing manual finishing.
1.5 Significance of the Study
Practical Application: Demonstrates mechatronic systems in traditional manufacturing.
Industrial Impact: Enhances production consistency, reduces labor, and increases productivity for
small-scale producers.
Economic Benefit: Utilizes affordable, locally available components for cost-effectiveness.
Academic Value: Serves as a case study in CAD, embedded systems, PID control, dynamic modeling,
and prototyping.
Technological Advancement: Contributes to accessible automation for traditional crafts.
1.6 Methodology Overview
The research integrates mechanical design, modeling, simulation, control development, and prototype
evaluation. Key areas include:
PID Control Development: For stable wheel rotation and guiding arm movement.
Mechanical Design and Load Analysis: Using SolidWorks and FEA for structural integrity.
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Dynamic Modeling: Euler-Lagrange for guiding arm and other subsystems.
Stability and Precision Analysis: Using simulations to evaluate performance metrics.
Trajectory Tracking Control: For accurate guiding arm path following.
Control Strategy Implementation: Arduino Uno for actuator control.
Component Selection: Sensors, motors, and microcontroller.
Simulation: MATLAB/Simulink for performance evaluation.
Prototype Development: Fabrication and integration of all components.
2. Literature Review Highlights
2.1 Guiding Arms and Shaping Arms in Pottery Automation
Function: Mechanical arms that follow predefined profiles to assist in shaping.
Benefits: Improve geometric accuracy and reduce physical effort.
Limitations: High cost, mechanical complexity, maintenance issues, and reduced tactile feedback.
2.2 Control Systems and PID in Pottery Automation
PID Controller: Widely used for stable wheel rotation and shaping arm movement.
Wheel Control: Maintains constant speed despite load variations for symmetry.
Shaping Arm Control: Ensures accurate path following and consistent shaping.
Advantages: Offers a balance of simplicity, stability, and adaptability compared to other control
methods.
2.3 Structural Design Simplicity and Stability
Importance: Crucial for performance, usability, and reliability.
Requirements: Balance simplicity with rigidity to absorb vibrations.
Materials: Steel, reinforced aluminum are preferred for strength and deformation resistance.
Design Considerations: Stable base, symmetrical frames, direct load paths, modularity for ease of
maintenance.
2.4 Overall Literature Summary
A gap exists between traditional (high creativity, low efficiency) and fully automated (high efficiency, low
creativity) systems. Semi-automated systems aim to bridge this but face challenges in cost, complexity, and
maintenance. PID control is a robust solution for stability. Structural simplicity and stability are paramount
for practical implementation.
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3. System Design
3.1 Mechanical Design Overview
Purpose: Assist pottery forming with controlled, repeatable shaping.
Capacity: Handles 1 kg to 2 kg of clay.
Key Components: Rotating wheel, guiding arm, shaping profiles (PBT plastic), supporting frame,
power transmission (silicone pulley).
Materials: Malleable cast iron (frame, guiding arm) for strength and durability, marine plywood
(machine bed) for moisture resistance, PBT plastic (shaping profiles) for wear resistance.
3.2 Load Analysis (FEA)
Finite Element Analysis (FEA) was performed to assess structural integrity under operational loads.
Machine Base: High factor of safety (FOS) indicates sufficient strength, even with balsa wood
simulation (marine plywood recommended for actual build).
Guiding Arm: Minimum FOS of 6.8 × 105 , well within malleable cast iron limits.
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Supporting Arm: Minimum FOS of 4.9 × 10 , confirming structural adequacy.
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Stand: Maximum stress 458 N/m is significantly lower than malleable cast iron yield strength.
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Wheel: Minimum FOS of 1.2 × 10 for carbon sheet material, indicating ample strength.
Wheel Connector: Minimum FOS of 2.2 × 107 , ensuring reliable load transfer.
3.3 Design of Machine Elements
3.3.1 Wheel Drive System Design
Function: Provides continuous, stable rotational motion for the wheel.
Components: DC motor, belt-pulley transmission, rotating wheel.
Key Parameters:
Clay Mass: 2 kg
Wheel Radius: 0.15 m
Required Torque: 4.41 Nm
Power Requirement: 81.5 W
Motor Speed: 3000 RPM
Wheel Speed: 150 RPM
Speed Reduction Ratio: 20 : 1
3.3.2 Rack and Pinion System Design
Function: Converts stepper motor rotation to precise vertical linear motion for the guiding arm.
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Components: Stepper motor, pinion, rack, guide rail.
Key Parameters:
Vertical Travel: 0.30 m
Pinion Diameter: 30 mm
Shaping Force: 30 N
Required Torque: 0.45 Nm
Stepper Step Angle: 1.8∘
Total Steps: 637 steps
3.3.3 End Effector and Servo Angle Control Design
Function: Shapes the internal profile of pottery using adaptive angular adjustment.
Components: Servo motor, end effector tool.
Key Parameters:
Angular Range: ±60∘
Resolution: 1∘
Shaping Force: 25 N
Arm Length (effective): 0.12 m
Required Torque: 3.0 Nm
Design Torque (with SF): 4.5 Nm
Servo Range: 180∘
3.3.4 Fixed Shaping Stand Design
Function: Forms the external profile of pottery with a fixed reference surface.
Components: Rigid stand structure.
Key Parameters:
Maximum Pottery Radius: 0.15 m
Shaping Force: 30 N
Bending Moment: 7.5 Nm
Maximum Stress (calculated): 0.6 MPa
Allowable Stress (malleable cast iron): 220 MPa
Deflection: 0.12 mm
3.4 Fabrication and Assembly
Approach: Modular fabrication for ease of assembly, maintenance, and testing.
Structural Frame: Malleable cast iron and marine plywood for rigidity and durability.
Wheel System: Carbon steel wheel, bearings, DC motor with adjustable bracket for belt tensioning.
Rack and Pinion: Steel rack, guide rail, stepper motor for precise linear motion.
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Guiding Arm & End Effector: Malleable cast iron arm, servo motor for angular control,
interchangeable tools.
Shaping Stand: Rigidly fixed to the base, precisely aligned.
Electrical Integration: Arduino Uno, motor drivers, sensors, power supplies, with proper wiring and
grounding.
Alignment: Critical for ensuring geometric accuracy between components.
Testing: Subsystems tested individually, then the integrated system under simulated loads.
3.5 Mathematical Modelling of the System
3.5.1 Rotational Dynamics of the Wheel (DC Motor Model)
di(t)
Electrical Equation: V (t) = L dt
+ Ri(t) + Kb ω (t)
dω(t)
Mechanical Equation: J dt + bω(t) = Tm (t) − TL (t)
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Motor Torque: Tm (t) = Kt i(t)
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Load Torque: TL (t) represents resistance from clay and friction.
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Ω(s)
Kt
Simplified Transfer Function (neglecting L): V (s) = Js2 +(bL+JR)s+(bR+K
K ) . A further
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t
Ω(s)
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b
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K
simplification often used for control is: V (s) = Js+b
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3.5.2 Mathematical Modelling of the Rack and Pinion System
Kinematic Relation: Linear displacement y(t) related to pinion angular displacement θ(t) by
y(t) = rp θ(t).
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Stepper Motor Dynamics: Jp θ̈ (t) + bp θ̇ (t) = Tm (t) − TL (t)
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Linear Force: FL = mÿ (t) + Ff (mass m, friction Ff )
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Torque-Force Relation: TL = FL rp
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Equivalent Linear Model: Meq ÿ (t) + Beq ẏ (t) = Fmotor (t) − FL (t)
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3.5.3 Mathematical Modelling of the Servo Motor and End Effector
Rotational Dynamics: Js θ̈ (t) + bs θ̇ (t) = Tm (t) − TL (t)
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Motor Torque: Tm (t) = Ku u(t) (where u(t) is control input)
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Load Torque: TL (t) = ke θ (t) + d(t) (clay resistance)
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Θ(s)
Ku
Transfer Function: U (s) = J s2 +(b +
s
s d)s+ke
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Coupling with Vertical Motion: θ(t) = k1 y (t)
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3.5.4 Overall Mathematical Model of the Semi-Automated Pottery System
The system is a multi-input, multi-output (MIMO) system combining the dynamics of the wheel, rack and
pinion, and servo.
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State Variables: Define states for angular velocity, angular position, linear position, linear velocity,
end effector angle, and end effector angular velocity.
State-Space Representation: Ẋ = AX + BU and Y = CX where X is the state vector, U is the
input vector (motor current, actuator force, servo control signal), and Y is the output vector (wheel
speed, linear position, end effector angle).
3.6 Control System Design
Strategy: Multi-loop PID control for each subsystem.
de(t)
General PID Law: u(t) = Kp e(t) + Ki ∫ e(t)dt + Kd dt
Wheel Speed Control: PID controller for the DC motor to maintain desired angular velocity ωref
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despite load disturbances.
Vertical Motion Control: PID controller for the rack and pinion system to track the desired vertical
position xref (t).
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Angular Control of End Effector: PID controller for the servo motor to track the desired angle
θref (t), adapting to internal pottery geometry.
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System-Level Architecture: Decentralized multi-loop control managed by Arduino Uno. Sensors
provide feedback for each loop.
Stability: Ensured by designing controllers such that closed-loop poles have negative real parts.
Example: PID Controller for Wheel Speed
Let the desired wheel speed be ωref and the measured speed be ω(t). The error is eω (t) = ωref − ω(t).
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The control voltage V (t) applied to the DC motor is:
V (t) = Kp,ω eω (t) + Ki,ω ∫ eω (t)dt + Kd,ω
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deω (t)
dt
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This voltage is fed into the DC motor model to regulate its speed. The gains Kp,ω , Ki,ω , and Kd,ω are tuned
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(e.g., using MATLAB/Simulink) to achieve desired performance characteristics like fast response, minimal
overshoot, and zero steady-state error.
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