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Development of a Low-Cost Automated Injection Molding Device for Sustainable Plastic Recycling and Circular Economy Applications

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In response to the critical demand for innovative solutions to tackle plastic pollution, this research presents a low-cost, fully automated plastic injection molding system designed to convert waste into sustainable products. Constructed entirely from repurposed materials, the apparatus focuses on processing high-density polyethylene (HDPE) efficiently without hydraulic components, thereby enhancing eco-friendliness and accessibility. Performance evaluations identified an optimal molding temperature of 200 °C, yielding consistent products with a minimal weight deviation of 4.17%. The key operational parameters included a motor speed of 525 RPM, a gear ratio of 1:30, and an inverter frequency of 105 Hz. Further tests showed that processing temperatures of 210 °C and 220 °C, with injection times of 15 to 35 s, yielded optimal surface finish and complete filling. The surface finish, assessed through image intensity variation, had a low coefficient of variation (≤ 5%), while computer vision evaluation confirmed the full filling of all specimens in this range. A laser-based overflow detection system has minimized material waste, proving effective in small-scale, community recycling. This study underscores the potential of low-cost automated systems to advance the practices of circular economies and enhance localized plastic waste management. Future research will focus on automation, temperature precision, material adaptability, and emissions management.
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Inventions 2024, 9, 124. https://doi.org/10.3390/inventions9060124 www.mdpi.com/journal/inventions
Article
Development of a Low-Cost Automated Injection Molding
Device for Sustainable Plastic Recycling and Circular
Economy Applications
Ananta Sinchai *, Kunthorn Boonyang
and Thanakorn Simmala
College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang,
Bangkok 10520, Thailand; 64125005@kmitl.ac.th (K.B.); 64125024@kmitl.ac.th (T.S.)
* Correspondence: author: ananta.sin@kmitl.ac.th
These authors contributed equally to this work.
Abstract: In response to the critical demand for innovative solutions to tackle plastic pollution, this
research presents a low-cost, fully automated plastic injection molding system designed to convert
waste into sustainable products. Constructed entirely from repurposed materials, the apparatus fo-
cuses on processing high-density polyethylene (HDPE) eciently without hydraulic components,
thereby enhancing eco-friendliness and accessibility. Performance evaluations identied an optimal
molding temperature of 200 °C, yielding consistent products with a minimal weight deviation of
4.17%. The key operational parameters included a motor speed of 525 RPM, a gear ratio of 1:30, and
an inverter frequency of 105 Hz. Further tests showed that processing temperatures of 210 °C and
220 °C, with injection times of 15 to 35 s, yielded optimal surface nish and complete lling. The
surface nish, assessed through image intensity variation, had a low coecient of variation ( 5%),
while computer vision evaluation conrmed the full lling of all specimens in this range. A laser-
based overow detection system has minimized material waste, proving eective in small-scale,
community recycling. This study underscores the potential of low-cost automated systems to ad-
vance the practices of circular economies and enhance localized plastic waste management. Future
research will focus on automation, temperature precision, material adaptability, and emissions
management.
Keywords: plastic recycling; injection molding; circular economy; resource recovery; sustainable
production; HDPE recycling; eco-friendly
1. Introduction
Plastic has become an integral part of modern life, nding applications in various
sectors, from packaging to furniture. However, the widespread use of plastic has led to
signicant environmental challenges, particularly in waste management and pollution
control [1]. The diculty in decomposing plastic waste and its increasing volume poses
serious threats to ecosystems and human health [2]. In response to these challenges, there
is a growing interest in developing cost-eective and ecient methods for plastic recy-
cling. One promising approach is the use of automatic plastic injection molding machines
for recycling plastic waste into new products. This research work aims to address the
plastic waste problem by designing and constructing a low-cost, fully automated plastic
injection molding machine using second-hand materials.
The oered device is designed specically for small-scale applications and localized
recycling initiatives. While the device may not currently compete economically with
large-scale industrial systems, its design prioritizes aordability, accessibility, and versa-
tility, making it well suited for small-scale applications such as educational use,
Citation: Sinchai, A.; Boonyang, K.;
Simmala, T. Development of a
Low-Cost Automated Injection
Molding Device for Sustainable
Plastic Recycling and Circular
Economy Applications. Inventions
2024, 9, 124. hps://doi.org/10.3390/
inventions9060124
Academic Editor: Theocharis
Tso ut sos
Received: 16 November 2024
Revised: 5 December 2024
Accepted: 9 December 2024
Published: 17 December 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Swierland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Aribution (CC BY) license
(hps://creativecommons.org/license
s/by/4.0/).
Inventions 2024, 9, 124 2 of 24
prototyping, or community recycling programs. It demonstrates a practical and accessible
solution for promoting sustainability in resource management.
The proposed machine operates on the principles of injection molding, a manufac-
turing process widely used in the production of plastic parts. By applying this technology
to recycling, we aim to transform plastic waste into various useful products such as ow-
erpots, vase blocks, and other household items. This approach not only reduces the vol-
ume of plastic waste but emphasizes the potential of decentralized recycling eorts and
the creation of value from waste materials.
In the context of HDPE recycling, the thermal processing and melting stages may
lead to the release of toxic gases. In addition to commonly discussed emissions, such as
carbon dioxide (CO2), other potentially harmful gases, including carbon monoxide (CO)
and volatile organic compounds (VOCs), may also be produced during the degradation
of HDPE. The exact composition of these emissions depends on factors such as tempera-
ture, oxygen availability, and material composition, including any additives present in the
HDPE. While this study focuses on estimating the possible emissions based on known
data, experimental validation is required to determine their presence and concentration
in the developed system. Addressing these emissions is critical for ensuring the sustaina-
bility and safety of small-scale injection molding systems, as outlined in later sections of
this paper. In addition, the recycling of plastics like HDPE through injection molding has
the potential to reduce waste and minimize greenhouse gas emissions when compared
with the production of virgin materials, contributing to global sustainability eorts [3,4].
This research oers several novel contributions:
1. Frugal innovation: we developed a low-cost automated recycling machine using re-
claimed materials.
2. Industrial-grade safety: we integrated advanced safety features in a compact recy-
cling device.
3. Circular economy: we transformed waste plastic into valuable products for sustaina-
ble management.
4. Innovative design: we operated without hydraulics, focusing on ecient thermo-
plastic processing.
5. Performance evaluation: we established key operational parameters for small-scale
recycling technologies, highlighting the potential usage in localized and educational
applications.
The structure of this article is as follows: Section 2 reviews the literature, followed by
Section 3, which outlines the methodology. Section 4 presents the performance evaluation
along with the experimental results. Section 5 discusses optimization insights, implica-
tions, and future directions, while Section 6 summarizes the key conclusions of the re-
search work.
2. Literature Review
Global production and plastic disposal continue to pose signicant environmental
challenges. Borrelle et al. projected that plastic waste inputs to aquatic ecosystems could
reach up to 53 million metric tons per year by 2030, highlighting the urgency of addressing
this issue [5]. Microplastics, formed from the degradation of larger plastic items, have be-
come a growing concern in particular. They have been found in marine organisms, poten-
tially entering the food chain and posing risks to human health [6]. Brahney et al. found
evidence of microplastic pollution in remote areas, demonstrating the pervasive nature of
plastic contamination [7].
The eects of plastic pollution on marine ecosystems have been well documented.
Shen et al. reviewed the impacts of microplastics on marine organisms, revealing potential
threats to biodiversity and ecosystem functioning [8]. Furthermore, Yong et al. discussed
the implications of plastic pollution on human health, emphasizing the need for compre-
hensive waste management strategies [9].
Inventions 2024, 9, 124 3 of 24
Recent advancements in recycling technologies have shown promise in addressing
the plastic waste crisis. Ragaert et al. provided an overview of mechanical recycling pro-
cesses for thermoplastics, highlighting the potential of injection molding in recycling ap-
plications [10]. The authors emphasized the importance of understanding material prop-
erties and processing conditions to ensure the quality of recycled products.
Injection molding involves melting plastic material and injecting it into a mold cavity,
where it cools and solidies into the desired shape. The process is versatile and can be
used with various thermoplastic materials, making it suitable for recycling applications
[11].
Conformal cooling channels (CCCs) have also emerged as a critical innovation in im-
proving injection molding eciency. These channels can achieve up to 62.9% beer cool-
ing performance compared with traditional systems, signicantly reducing cycle times
and improving thermal uniformity [12,13]. Despite these advancements, CCCs are typi-
cally complex and expensive, limiting their use in small-scale or low-cost applications.
In the context of injection molding, Zhao et al. investigated the use of recycled plastics
in the process, focusing on the challenges and opportunities associated with using mixed
plastic waste [14]. Their study demonstrated the feasibility of producing high-quality
products from recycled materials through optimized processing parameters.
While industrial-scale recycling facilities leverage advanced automation technolo-
gies, smaller, low-cost systems remain underexplored. Automation systems, such as Lab-
VIEW-based pneumatic injectors [15] and adaptive in-mold pressure controls [16], have
improved process reliability and part quality in industrial applications. However, such
systems often require signicant investment and technical expertise, highlighting the need
for simplied and cost-eective solutions tailored to localized recycling eorts.
While large-scale industrial recycling facilities exist, there is growing interest in de-
veloping small-scale, low-cost recycling solutions. These systems can be particularly ben-
ecial in areas with limited access to centralized recycling facilities or for small businesses
and educational institutions [17].
Zander et al. demonstrated the feasibility of constructing a low-cost plastic extruder
for recycling purposes, using readily available components and open-source designs [18].
Similarly, Chong et al. developed a small-scale injection molding machine for educational
purposes, highlighting the potential for such systems in promoting hands-on learning
about plastic recycling and manufacturing processes [19].
Material and process innovations in hybrid composites have shown promise in im-
proving the mechanical properties of recycled products. For example, wood ber compo-
sites reinforced with glass and carbon bers achieved tensile strength increases of 30–38%
[20]. Rapid tooling technologies have further demonstrated up to 89% reductions in cool-
ing times [21], paving the way for more ecient production cycles. However, these ad-
vances often target large-scale systems, leaving opportunities to adapt similar principles
for small-scale recycling technologies. In addition, low-cost epoxy resin molds with en-
hanced cooling eciencies have reduced cooling times by approximately 22%, showcas-
ing practical innovations for cost-eective production [22].
The development of small-scale, low-cost recycling solutions has gained traction in
recent years. Dertinger et al. presented an open-source design for a small-scale plastic re-
cycling system, which included an injection molding component [23]. Their work show-
cased the potential for distributed recycling and additive manufacturing (DRAM) in pro-
moting circular economy principles.
Likewise, Cruz Sanchez et al. explored the technical and economic feasibility of dis-
tributed recycling via additive manufacturing (DRAM) in rural areas [24]. Their ndings
suggested that such systems could provide both environmental and economic benets to
communities with limited access to centralized recycling facilities.
Despite the progress in recycling technologies, several challenges remain. Eriksen et
al. identied key barriers to plastic recycling, including contamination of waste streams,
degradation of material properties during recycling, and lack of standardized quality
Inventions 2024, 9, 124 4 of 24
assessment methods for recycled plastics [25]. The authors emphasized the need for im-
proved sorting technologies and design-for-recycling approaches to enhance the quality
and value of recycled materials.
Advancements in compatibilization techniques for biopolymers from renewable re-
sources show promise in overcoming challenges like brileness and cost [26]. The review
highlights strategies such as reactive methods and nanoparticle incorporation to enhance
compatibility and performance in biopolymer blends. These developments enable signif-
icant improvements in properties like strength and elongation, making biopolymers more
viable alternatives to traditional plastics.
In the realm of quality assessment, Vollmer et al. proposed a standardized method-
ology for evaluating the quality of recycled plastics, addressing a critical gap in the recy-
cling value chain [27]. Their work contributes to eorts in establishing reliable quality
standards for recycled materials, which is essential for increasing market acceptance and
value.
Furthermore, while optimization techniques like grey-based Taguchi methods have
improved product quality by reducing warpage (16.42%) and birefringence (74.74%) [28],
their application in low-cost, small-scale systems is limited. This highlights the need for
simplied optimization frameworks for non-specialist users. Taguchi-based optimiza-
tions in injection molding have improved material properties and processing eciency.
For talc-lled polypropylene (TFPP), tensile strength increased by 10.5% and shrinkage
reduced by 0.97% [29]. In non-pneumatic tire molds, a semi-annular conformal cooling
channel design reduced pressure loss by 77%, cycle time by 9.6%, and shrinkage by
0.012%, enhancing cooling eciency and tire quality [30].
Summary of Gaps and Opportunities
The literature reveals several opportunities for improvement:
1. Accessibility and cost: advanced technologies like CCCs and automated controls are
prohibitively expensive for small-scale applications.
2. Localized recycling needs: there is a lack of systems designed for decentralized, com-
munity-based recycling eorts.
3. Simplied automation: most automation methods require technical expertise, creat-
ing barriers for non-specialist users.
4. Tailored optimization: existing optimization techniques for molding processes are
not adapted for low-cost, small-scale setups.
This work therefore addresses these gaps by developing a cost-eective, fully auto-
mated injection molding system that utilizes reclaimed materials, eliminates hydraulic
components, and integrates user-friendly automation and performance optimization tai-
lored to localized recycling needs.
3. Methods
This outlines the conceptual framework, design principles, and implementation pro-
cedures for the automatic plastic injection molding machine. The methodology encom-
passes the structural design of the machine, component selection, control system architec-
ture, and software development.
3.1. Structural Design of the Automatic Plastic Injection Molding Machine
The structural design of the low-cost automatic plastic injection molding machine
comprises four primary components (see Figure 1) [31]. These components are the ma-
chine base, the control system unit, the plastic injection unit, and the heater control unit.
The base is constructed from galvanized steel, with dimensions of 2 × 2 inches for the main
structure and 1.50 × 1.50 inches for the four legs, each 84 cm in length. The legs are de-
signed to be foldable for enhanced portability. The tabletop consists of a 1 cm thick hard-
wood board measuring 80 × 50 cm.
Inventions 2024, 9, 124 5 of 24
Figure 1. Structure and view of the automatic injection molding machine: (a) three-dimensional
model of the machine; (b) front view—machine base; (c) top view—control unit; and (d) actual con-
structed machine.
3.2. Materials and Components
The research work utilizes a diverse array of components, including:
1. Inverter (220 V-3 phase 0.75/1 phase);
2. Gear motor (1/30 220 V 3 phase);
3. Stainless steel enclosures;
4. Push buon switches (22 mm, 1NO 1NC);
5. Emergency switch (22 mm);
6. Temperature controller (“Primus” TMP-48-P-N-A);
7. Single-phase solid-state relay (“Primus” PS-01N-40);
8. Heatsink (“Primus” HP-03);
9. Cooling fan for electrical cabinet (“Primus” PMV115NP220);
10. K-type thermocouple (“Primus” TSK-13);
11. Band heater (Primus 5 W/cm
2
450 °C);
12. Wire duct;
13. Switching power supply (5 V/5 A);
14. Custom-made injection cylinder;
15. Drilling press machine vise (6 inches);
16. Terminal block (6 × 6 slots, 600 V/15 A);
17. Four-channel 5 V relay module;
18. Arduino mega 2560 R3;
19. IR infrared obstacle avoidance module (3–5 V DC);
20. Laser head sensor module (KY-008, 5 V);
21. Laser receiver module (5 V);
22. Custom-designed CNC mold;
23. LCD with I2C module (LCD2 2 × 16 V);
Inventions 2024, 9, 124 6 of 24
Input Material Preparation
The exact origin of the input material is unknown. However, the HDPE used in this
work was sourced from post-consumer plastic products, such as boles and containers.
The material generally underwent the following preparation steps:
1. Shredding: the collected HDPE was shredded into uniform pellets to facilitate han-
dling and further processing.
2. Cleaning: the shredded material was thoroughly cleaned to remove any contami-
nants, such as dirt, labels, and adhesive residues, ensuring the purity of the material.
3. Drying: after cleaning, the material was dried at 70 °C for 2 h to eliminate any re-
maining moisture, preparing it for subsequent use (see Figure 2).
Figure 2. Final prepared material.
To save time, it is also possible to purchase the nal prepared material (shredded,
cleaned, and dried) directly from a recycling operator, which can streamline the material
acquisition process.
3.3. Control Circuit and Heat Generation Circuit Design
This section describes the control circuit and heat generation circuit, both illustrated
in Figure 3 to clarify their roles in the automatic plastic injection molding machine.
Inventions 2024, 9, 124 7 of 24
Figure 3. Overview of the device connections for the control circuit and heating circuit.
3.3.1. Control Circuit Design
The control circuit employs a switching power supply to convert 220 V AC (high
voltage) to 5 V DC (low voltage) for use with control circuit components. The MEGA Ar-
duino board serves as a power source for 5 V DC devices and controls the 5 V relay, which
in turn activates the inverter. This conguration enables the three-phase motor to rotate,
facilitating the transfer of plastic from the hopper into the injection cylinder.
3.3.2. Heat Generation Circuit Design
The heat generation circuit utilizes a temperature controller to manage the operation
of a single-phase solid-state relay, which supplies power to the band heater [32]. Temper-
ature regulation is achieved through feedback from a K-Type thermocouple sensor, en-
suring stable and precise heating of the injection cylinder [33].
3.4. Mold Design
The mold is composed of two aluminum plates, as shown in Figure 4, with the front
plate at the top and the back plate at the boom [34]. Neither of the piecework images in
the subgures are to scale, nor are they perfectly aligned. To replicate this designed mold,
each detail is explained. While this explanation applies to the current design, modica-
tions can be performed to meet the specic requirements of each individual design pref-
erence. Each plate has the dimensions 140 mm × 90 mm × 11 mm. Each section is initially
milled to a depth of 1.5 mm, forming a rounded rectangle with a length of 100 mm, a
width of 45 mm, and an arc radius of 22.5 mm. The rounded rectangle is centered on each
plate. During the formation of the rounded rectangle, a small 5 mm diameter cylinder bar,
1.5 mm in length, is formed on the right side of each plate, 11.25 mm from the edge and
aligned with the horizontal centerline of the rounded rectangle. An inow channel, 1–2
Inventions 2024, 9, 124 8 of 24
mm deep and wide, is milled as a straight line on each plate, approximately aligned with
the vertical centerline of the rounded rectangle. On the front plate, the channel is at the
lower horizontal edge, while on the back plate, it is at the upper horizontal edge (see Fig-
ure 4a,b). This inow channel serves to feed melted plastic into the rounded rectangle
inside the mold. In addition, two overow channels are milled on both sides of the
rounded rectangle along the horizontal centerline of both plates. The AMI alphabets are
then milled to a depth of approximately 0.1 to 0.2 mm (see Figure 4b). A hole with a di-
ameter of 5 to 5.5 mm is drilled at each corner, located 10 mm from both the horizontal
and vertical edges of each plate. However, the drilling distance from each edge depends
on the individual design of the hole size. These holes are used to secure the mold plates
together with bolts at all four corners during injection.
(a)
(b)
Figure 4. Designed mold: (a) front plate and (b) back plate.
3.5. Software Development and Operational Workow
The software architecture for the automatic plastic injection molding machine con-
sists of two primary components: an Arduino-based control program and a web-based
monitoring and control interface, as depicted in Figure 5. These components work in tan-
dem to execute the operational workow of the machine.
Inventions 2024, 9, 124 9 of 24
(a)
(b)
Figure 5. Workow diagram of the program and control interface displayed via the web application:
(a) workow diagram and (b) control and display interface.
Inventions 2024, 9, 124 10 of 24
3.5.1. Arduino Control Program
The Arduino program, wrien in C++, manages the core functionality of the machine
(see Figure 5a). Key features include:
Real-time temperature monitoring and control using a PID algorithm;
Injection cycle management with a congurable countdown timer;
Sensor input processing for safety and operational feedback;
LCD interface control for local status display.
The program implements a state machine architecture to manage dierent opera-
tional modes (e.g., idle, heating, injection, cooling). Error handling and safety checks are
integrated throughout the control ow to ensure safe operation.
3.5.2. Web-Based Monitoring and Control Interface
A Flask-based web application provides a user-friendly interface for remote moni-
toring and control (see Figure 5b) [35,36]. The application features:
Real-time data visualization of machine status and temperature;
Remote control capabilities for start, stop, and parameter adjustment;
A responsive design for access from various devices;
A secure communication protocol for machine-to-interface data transfer.
The web interface is designed with a focus on intuitive operation and clear data
presentation, enhancing the overall usability of the machine.
3.5.3. Operational Workow
The operational workow of the machine, as illustrated in Figure 5a, follows a sys-
tematic process to ensure ecient and safe plastic injection molding. The workow is as
follows:
1. System initialization: upon powering on, the machine performs a self-check of all
components and sensors.
2. Temperatur e seing: the operator sets the desired temperature for the injection pro-
cess through the interface.
3. Heating phase: the machine initiates the heating process, continuously monitoring
the temperature until it reaches the set point.
4. Material loading: once the target temperature is achieved, the system is ready for
material loading.
5. Mold closure: the mold is closed and secured, with safety checks to ensure proper
closure.
6. Injection process: the machine initiates the injection process, moving the screw for-
ward to inject molten plastic into the mold.
7. Cooling phase: after injection, the mold is cooled for a predetermined time.
8. Mold opening: once cooled, the mold is still opened manually.
9. Part ejection: the molded part is pulled out from the mold.
10. Cycle completion check: the system checks if the required number of cycles has been
completed. (A). If yes, the process ends. (B). If no, the system returns to step 4 for the
next cycle.
11. Emergency stop: at any point in the process, an emergency stop can be triggered,
immediately halting all operations and requiring a manual reset.
This operational workow ensures a systematic approach to plastic injection mold-
ing, maximizing eciency while maintaining strict quality control and safety standards.
The integration of automated processes with manual oversight capabilities allows for ex-
ible operation adaptable to various production requirements.
Inventions 2024, 9, 124 11 of 24
3.6. Maintenance Protocols
Eective maintenance is essential to ensure the longevity and optimal performance
of equipment, particularly in plastic injection molding processes as follows.
Temperature regulation: After concluding operations, it is critical to set the tempera-
ture of the device to 0 degrees Celsius and allow it to cool to below 100 degrees Cel-
sius. This practice not only preserves the heating system but also prevents thermal
stress that could lead to component degradation or failure. Proper temperature man-
agement is vital as it minimizes the risk of thermal expansion and contraction, which
can compromise the integrity of the machinery over time.
Inspection of components: Regular checks of the material feeding hopper and laser
sensor are imperative before and after use. Ensuring that these components are func-
tioning properly helps to avoid production inconsistencies and potential safety haz-
ards. Additionally, securely closing the material feeding hopper prevents foreign ob-
jects from entering the system, which could disrupt the injection process and damage
equipment.
3.7. Safety Precautions
Avoiding burns: During operation, it is crucial to avoid direct contact with the heated
injection barrel and to refrain from handling the mold with bare hands due to accu-
mulated heat. Always wearing gloves when interacting with these components is es-
sential to prevent burns and ensure personal safety. This practice not only protects
operators but also promotes a safer working environment by minimizing the risk of
accidents related to thermal exposure.
Troubleshooting procedures: In the event of a malfunction or operational failure, it
is important to rst press the reset buon before investigating the root cause of the
issue. This initial step helps to clear any temporary errors and may restore function-
ality. Following this, a thorough analysis should be conducted to identify and ad-
dress the underlying problem. Understanding the reasons for equipment failure is
vital for preventing future incidents and maintaining operational eciency.
Emission Mitigation Strategies
Given the potential release of toxic gases (e.g., CO, VOCs such as aldehydes, benzene,
and toluene) during HDPE melting, measures are necessary to ensure operator safety and
environmental compliance [37,38]:
Closed-system containment: install a gas containment hood to capture emissions at
the source, preventing them from dispersing into the surrounding environment.
Filtration and neutralization: equip the containment hood with activated carbon l-
ters to absorb VOCs and catalytic converters to neutralize CO and aldehydes.
Real-time monitoring: integrate gas sensors to detect concentrations of CO, VOCs,
and other harmful gases, ensuring immediate alerts if thresholds are exceeded.
Emergency response protocols: establish emergency protocols, such as immediate
evacuation and ventilation shuto, if high levels of toxic gases are detected.
3.8. Plastic Injection Experimental Setup
The plastic injection experiments were designed to evaluate the performance of the
automatic injection molding machine using HDPE material. Three temperature seings
(190 °C, 200 °C, 210 °C) were tested, with 10 injection cycles conducted at each tempera-
ture. The injection time was xed at 60 s, and the motor frequency was set to 105 Hz. A
stabilization period of 3–5 min between each cycle ensured consistent temperature. Key
outcomes, such as weight consistency and deviations, were assessed for each experimental
condition.
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3.9. Mold Injection Experimental Setup
This section outlines the setup for the mold injection experiments, which aimed to
determine optimal conditions for producing high-quality molded parts. The experiments
varied temperature (190 °C, 200 °C, 210 °C, 220 °C, and 230 °C) and injection time (15, 20,
25, 30, and 35 s), resulting in ve samples for each temperature condition.
The motor frequency was kept constant at 105 Hz, and a laser sensor was used to
detect overow, halting the injection process if excess plastic was injected. The mold di-
mensions were designed to allow for the injection of a maximum volume of approximately
115 cm3 [34]. These parameters were adjusted to assess the impact of temperature and
injection time on mold lling, part quality, and the occurrence of overow.
The estimated maximum volume of 115 cm3 for the injection cylinder is calculated
based on a 32 mm diameter and 190 mm length. The cylinder contains a 4-turn rotary
auger drill bit with a shaft radius of 2.5 mm and 10.2 mm thick ights. The 190 mm total
length is divided into 7 turns, each with a 20 mm pitch. This ensures a consistent axial
distance between consecutive turns, with each twist and ute also covering 10 mm and 20
mm in length, respectively. The design maintains uniformity in material movement across
the 7 turns. The turns are conned within a 190 mm working section of the bit, and the
maximum volume is derived from the following calculations.
1. Injection cylinder volume (use V = π × r2 × h; r and h represent the radius and height
of an object, respectively):
Vcylinder = π × (16 mm)2 × 190 mm 152,807.07mm3.
2. Auger shaft volume (use V = π × r2 × h; r and h represent the radius and height of an
object, respectively):
Vshaft = π × (2.5 mm)2 × 190 mm 3730.64mm3.
3. Estimated auger ight volume based on the ring-like area, modied from [39]:
o Outer radius of ight = 2.5mm + 10.2mm = 12.7 mm
o Flight area (viewed from the top of the auger drill bit tip) (use A = π × (router2
rinner2); router and rinner represent the outer and inner radii of an object, respectively):
Aight = π × ((12.7 mm)2 (2.5 mm)2) = π × (161.29 mm2 6.25 mm2) = π ×
155.04 487.07mm2.
o Flight volume (Aight × twist length × turns):
Vights = 487.07 mm2 × 10 mm × 7 34,094.9mm3.
4. Total auger volume:
Vauger = Vshaft + Vights = 3730.64 mm3 + 34,094.9 mm3 37,825.54 mm3.
5. Maximum approximate feeding volume:
V
maximum =
V
cylinder
V
auger
= 152,807.07 mm3 37,825.54 mm3 114,987.53mm3(or 115 cm3).
3.10. Setup for Quality Inspection of Specimens
3.10.1. Inspection of Surface Finish in Molded Parts
To evaluate the surface nish, a prolometer is typically required to measure the
roughness of each molded part. However, due to the unavailability of the prolometer,
an alternative technique based on image processing—specically intensity variation and
standard deviation [40]—is adopted and modied for this work. The inspection is per-
formed using MATLAB under a student license for image processing. First, a at surface
Inventions 2024, 9, 124 13 of 24
of each molded part, obtained from the side where the AMI alphabets are not visible, is
selected. This surface is then captured using a digital camera and stored as an image le
on a computer. The digital camera is mounted on a ball-head tripod, with its lens directed
towards the workpiece, which is placed on a suitable inspection plate. The optimal dis-
tance between the camera and the workpiece is empirically determined to achieve the best
resolution. The acquired image is cropped to dene the region of interest, which is then
converted into an 8-bit grayscale image. The region of interest covers only the right-angled
rectangular part of the specimen, as it appears to be the aest area (see Figure 4a). Finally,
the average intensity and the coecient of variation are calculated using the cropped
grayscale image as the input. It is noted that the 8-bit grayscale has an intensity range from
0 to 255, where this range transitions from black (0) to white (255).
3.10.2. Inspection of Complete Filling in Molded Parts
For the quality inspection of the molded parts concerning complete lling to com-
plete lling, Zebra AuroraTM Vision Studio v5.2.10.93510 Professional was employed to
dierentiate between fully formed and incomplete parts. The inspection involved evalu-
ating the clarity of paerns on the mold. These paerns were then compared with a refer-
ence to assess part completeness, using an 80–20 training–test ratio derived from 35 work-
piece images. The inspection criteria included a percent of area 60%, indicating a fully
formed part.
The inspection process involved:
Assessing the integrity of the samples.
Cropping images to focus on specic areas of interest.
Detecting characters through area-specic recognition.
Consolidating outputs into a single channel to determine the completeness of the
parts.
The results of these inspections were analyzed in relation to the injection parameters
(temperature and time) to determine the most eective seings for part quality.
It is important to note that the Aurora Vision software used in this study was obtained
under a student license and is intended exclusively for academic and research purposes.
It is not authorized for commercial use.
4. Performance Evaluation and Experimental Results
The study focused on evaluating the performance of a low-budget automatic plastic
injection molding machine using high-density polyethylene (HDPE) as the raw material.
The experiments were conducted to assess the eciency of the machine, identify factors
aecting its performance, and determine optimal parameters for dierent types of raw
materials. In addition, a repeatability and reproducibility (R&R) aspect was considered to
assess the precision and reliability of the measurement system involved in the process
[41]. The results and discussion are presented below.
4.1. Plastic Injection Experiments
As described in Section 3.8, plastic injection experiments were conducted using
HDPE at three temperatures: 190 °C, 200 °C, and 210 °C. The results demonstrate the crit-
ical impact of temperature on the consistency and reliability of the injection process.
At 190 °C, the average sample weight was 36.7 g, with an absolute deviation of 6.85%.
This moderate variability indicates that the lower temperature was insucient for com-
plete material melting, leading to inconsistencies in ow and injection.
At 200 °C, the average sample weight improved to 44.9 g, with a signicantly reduced
absolute deviation of 4.17%. This suggests that 200 °C is near-optimal for processing
HDPE, achieving stable material ow and consistent results.
Inventions 2024, 9, 124 14 of 24
At 210 °C, the average sample weight increased further to 59.3 g; however, the abso-
lute deviation rose to 7.85%. The higher temperature enhanced material uidity but intro-
duced variability, likely due to overlling or excessive ow dynamics.
These results demonstrate that while 200 °C provided the most consistent and relia-
ble outcomes, deviations increased at both lower and higher temperatures due to insu-
cient or excessive melting. Maintaining precise temperature control around 200 °C is es-
sential for ensuring high-quality and consistent results in plastic injection molding.
4.2. Accuracy and Deviations in Plastic Injection
The results indicate that the experiment conducted at 200 °C demonstrated the high-
est accuracy and stability in plastic injection, with the lowest average absolute deviation
of 4.17% being observed from the mean weight. The experiments at 190 °C and 210 °C
exhibited higher absolute deviations, with values of 6.85% and 7.85%, respectively. This
suggests that 200 °C may be the optimal temperature for this specic process, yielding the
most consistent and uniform output.
4.3. Eect of Temperature on Plastic Weight Stability
The lower percentage of deviation observed at 200 °C indicates that this temperature
is the most optimal for the process, resulting in the most consistent and uniform output.
In contrast, the experiments at 190 °C and 210 °C may not be as suitable, leading to greater
variability in weight.
This deviation can be linked to the properties of the material at dierent tempera-
tures. At lower temperatures, the plastic may not fully melt, causing incomplete injection,
while higher temperatures increase uidity, leading to overlling and inconsistencies. Re-
search in materials science supports the notion that optimal processing conditions signif-
icantly impact the quality of the nal product. It is important to note that the optimal
temperature of 200 °C is specic to HDPE, and other materials, such as polypropylene
(PP) or polystyrene (PS), would require further testing to determine their ideal processing
temperatures.
4.4. Physical Characteristics of Injected Plastic
The investigation into the physical characteristics of plastic samples revealed signi-
cant variations across three temperature regimes. At 190 °C, a sample weighing 35 g dis-
played a pronounced brous texture (see Figure 6a), indicating incomplete melting due
to inadequate uidity, which compromised structural integrity. In contrast, the sample
produced at 200 °C, weighing 45 g, exhibited a notably smoother texture with reduced
lament thickness (see Figure 6b). This improvement reects beer melting and ow char-
acteristics, resulting in a more uniform distribution of plastic within the mold.
(a) (b) (c)
Figure 6. Physical characteristics of injected plastic: (a) sample at 190 °C, (b) sample at 200 °C, and
(c) sample at 210 °C.
Inventions 2024, 9, 124 15 of 24
At the highest temperature of 210 °C, the sample weighed 61 g and demonstrated a
much more liquid consistency, characterized by minimal lament presence (see Figure
6c). This outcome is aributed to enhanced uidity, enabling more complete melting and
ow of the plastic material. These ndings underscore the critical role of temperature in
shaping the physical properties of injection-molded plastics, with 200 °C emerging as the
optimal temperature for balancing uidity and structural integrity. Temperatures below
this threshold result in poor melting and ow, while those above may lead to excessive
uidity, compromising the structural properties of the nal product. The weight varia-
tions across the temperatures highlight the necessity of precise temperature control for
consistent product quality.
4.5. Mold Injection Experiments
As described in Section 3.9, mold injection experiments were conducted to determine
the optimal parameters for producing high-quality molded parts.
At lower temperatures (190 °C and 200 °C), incomplete mold lling was observed,
especially at shorter injection times (15 and 20 s). At these temperatures, the plastic strug-
gled to ow properly into the mold, leading to parts with voids and rough surfaces.
At higher temperatures (220 °C and 230 °C), the mold lling improved, but the risk
of overow increased, especially at longer injection times (30 and 35 s). The temperature
of 220 °C provided a good balance between complete mold lling and part quality, with
optimal injection times of 15–35 s.
The best results in terms of part quality, including surface nish and mold lling,
were observed at 210 °C to 220 °C. However, at 230 °C, some parts exhibited signs of over-
heating, such as slight discoloration or warping, indicating that temperatures beyond this
point could negatively aect part integrity.
These ndings demonstrate the importance of optimizing both temperature and in-
jection time. A balance must be struck to ensure complete mold lling while avoiding
overow or defects in the molded parts.
4.5.1. Analysis of Results
The results of the mold injection experiments revealed several important ndings:
(a) Temperature eects
Lower temperatures (190 °C and 200 °C) generally resulted in incomplete mold
lling, especially at shorter injection times.
Higher temperatures (220 °C and 230 °C) improved mold lling but increased
the risk of overow and potential part defects.
The middle temperature range (210 °C) appeared to oer a good balance be-
tween mold lling and part quality.
(b) Injection time eects
Shorter injection times (15 and 20 s) often resulted in incomplete parts, particu-
larly at lower temperatures.
Longer injection times (30 and 35 s) improved mold lling but increased the risk
of overow, especially at higher temperatures.
The optimal injection time varied depending on the temperature, with higher
temperatures generally requiring shorter injection times for complete mold ll-
ing.
(c) Part quality observation
Parts produced at 190 °C showed clear signs of incomplete lling, with visible
voids and rough surfaces (Figure 7a).
Parts produced at 200 °C showed improved lling but still exhibited some im-
perfections (Figure 7b).
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The best overall part quality was observed in the 210 °C to 220 °C range, with
good surface nish and complete mold lling (Figure 7c,d).
At 230 °C, some parts showed signs of overheating, such as slight discoloration
or warping (Figure 7e).
Figure 7. Characteristics of plastic samples injected at various temperatures and time intervals: (a)
190 °C for 15, 20, 25, 30, and 35 s (pieces 1–5); (b) 200 °C for 15, 20, 25, 30, and 35 s (pieces 1–5); (c)
210 °C for 15, 20, 25, 30, and 35 s (pieces 1–5); (d) 220 °C for 15, 20, 25, 30, and 35 s (pieces 1–5); (e)
230 °C for 15, 20, 25, 30, and 35 s (pieces 1–5).
To sum up, the experimental ndings underscore the intricate relationship between
temperature, injection time, and the resultant quality of molded parts. At lower tempera-
tures (190 °C and 200 °C), incomplete mold lling was prevalent, particularly during
shorter injection durations. This phenomenon can be aributed to the insucient uidity
of the material, which hampers its ability to ll the mold cavity eectively.
Conversely, the higher temperature range (220 °C and 230 °C) facilitated improved
mold lling; however, it introduced challenges related to overow and potential defects
in the nal product. This highlights the critical need for a careful balance between tem-
perature and injection duration to optimize manufacturing outcomes.
The analysis of injection times revealed that shorter durations (15 and 20 s) frequently
led to incomplete parts, particularly at lower temperatures. In contrast, extending the in-
jection time to 30 and 35 s generally enhanced lling but raised the risk of overow, espe-
cially at elevated temperatures. Notably, the optimal injection time was found to be tem-
perature-dependent, with higher temperatures necessitating shorter injection periods to
achieve complete mold lling.
Regarding the assessment of part quality through visual inspection and tactile exam-
ination, the parts produced at 190 °C displayed signicant defects, such as voids and
rough surfaces, while parts at 200 °C showed modest improvements yet still retained im-
perfections. The optimal quality was achieved within the 210 °C to 220 °C range, charac-
terized by a superior surface nish and complete lling. However, at 230 °C, signs of over-
heating—such as discoloration and warping—were evident, underscoring the importance
of precise temperature control in the injection molding process. The evaluation of part
quality in terms of quantity is discussed in Sections 4.6.1 and 4.6.2.
Inventions 2024, 9, 124 17 of 24
These insights contribute valuable knowledge to the optimization of mold injection
parameters, which is crucial for enhancing product quality and overall manufacturing ef-
ciency.
4.5.2. Gas Emission Analysis During HDPE Melting
The thermal degradation of HDPE during the injection molding process results in the
emission of various gases. For a continuous injection cycle using 108.1 g of HDPE (equiv-
alent to the maximum feeding volume of 115 cm3), the following emissions are estimated
[42,43]:
HDPE input data
Volume of molten HDPE: 115 cm3
Density of HDPE: 0.94 g/cm3
Mass of HDPE melted:
Mass = Volume × Density = 115cm3 × 0.94g/cm3
1. Carbon dioxide (CO2)
Emission factor: combustion of HDPE typically produces 3.14 g of CO2 per g of
HDPE.
Calculation based on stoichiometry [44]:
CO2 = Mass of HDPE × 3.14 = 108.1g × 3.14 = 339.43g
Emission factor of CO2 equivalent (CO2e): 6.71 kg of CO2e per kg of HDPE, as
adopted from [45].
Calculation:
CO2e = Mass of HDPE × 6.71 kg = 108.1 × 103kg × 6.71 = 0.73kg (730 g)
2. Carbon monoxide (CO)
Emission factor: partial combustion or thermal degradation of HDPE produces
0.0025 g of CO per g of HDPE, as derived from [46].
Calculation:
CO = Mass of HDPE × 0.0025 = 108.1g × 0.0025 = 0.27g
3. Volatile organic compounds (VOCs)
Emission factor: thermal degradation produces 0.00247 g of VOCs per g of HDPE,
as derived from [47].
Includes: acrolein, aldehydes (e.g., formaldehyde), benzene, toluene [48]
Calculation:
VOCs = Mass of HDPE × 0.00247 = 108.1g × 0.00247 = 0.267g
In a single injection cycle, the combustion and thermal degradation of HDPE release
approximately 730 g of CO2e, which represents the total greenhouse gas emissions, in-
cluding CO2, methane, and other gases. Additionally, approximately 0.27 g of CO and
0.267 g of VOCs (including acrolein, aldehydes, benzene, and toluene) are emied. While
these quantities may seem small, they contribute to global warming, respiratory issues,
carcinogenic risks, and air pollution. Eective emission control is crucial to mitigate these
environmental and health impacts.
The thermal degradation process, inuenced by the operating temperature (ranging
from 190 °C to 230 °C), determines the types and amounts of gases released. At lower
temperatures (190 °C to 200 °C), emissions are generally lower, but more toxic gases like
aldehydes, VOCs, and acrolein can form due to incomplete combustion. Higher tempera-
tures (220 °C to 230 °C) result in a broader range of emissions, including CO2, which con-
tributes signicantly to climate change; CO (which is toxic even at low concentrations);
Inventions 2024, 9, 124 18 of 24
and benzene. This variety of gases—ranging from CO2, a greenhouse gas, to VOCs, which
can be harmful or toxic—highlights the need for careful control of the thermal process and
appropriate safety measures.
Among these gases, CO2 is the most signicant contributor to greenhouse gas emis-
sions, exacerbating climate change concerns. Managing these emissions is crucial for
aligning injection molding processes with sustainability goals.
This analysis underscores the importance of managing emissions in continuous in-
jection operations. Successive cycles without the introduction of new nal prepared HDPE
can lead to cumulative emissions and increase the risks of harmful gas buildup, especially
in poorly ventilated environments. Eective containment and ltration solutions, as dis-
cussed in the Section Emission Mitigation Strategies and in Section 5.5, are essential for
mitigating these risks.
4.6. Quality Inspection of Specimens
As described in Section 3.10, quality inspections of the molded parts were conducted
using Aurora Vision software and image processing techniques. The inspections focused
on the part completeness, with a percent of area 60% indicating a fully formed part, and
surface nish, assessed through intensity variation and standard deviation.
The results were analyzed in relation to injection parameters (temperature and time)
to determine optimal seings for part quality.
4.6.1. Surface Finish in Quantity Measurement
At various temperatures, the surface nish of the specimens (see Figure 7) was eval-
uated based on the average intensity and coecient of variation. At 190 °C, only two spec-
imens were evaluated, with an average intensity of 165.44 and a coecient of variation of
8.54%. At 200 °C, three specimens showed an average intensity of 183.10 and a coecient
of variation of 9.65%. At 210 °C, all specimens were evaluated, yielding an average inten-
sity of 190.88 and a signicantly lower coecient of variation of 1.66%. At 220 °C, the av-
erage intensity of all specimens increased to 196.65, with a further reduction in the coe-
cient of variation to 0.88%. At 230 °C, the average intensity of four specimens was 179.60,
and the coecient of variation was 1.76%. The coecient of variation serves as an indica-
tor of surface roughness, with lower values corresponding to smoother surfaces. A coe-
cient of variation below 5% suggests low roughness, while values above 5% indicate
higher roughness [49]. Overall, the surface nishes at 210 °C, 220 °C, and 230 °C exhibited
beer quality compared with those at 190 °C and 200 °C, as evidenced by the lower coef-
cient of variation values at higher temperatures.
4.6.2. Temperature and Injection Time
At 230 °C with 30 s of injection time (Figure 8a): the part shows good quality, passing
the inspection criteria with a high percent of area value.
At 230 °C with 25 s of injection time (Figure 8b): the part shows good quality only in
the upper part, like the rst case, but the lower part is missing, so it fails the inspec-
tion criteria.
At 230 °C with 20 s of injection time (Figure 8c): the part still maintains good quality,
but there is a crack at the top, so it fails the inspection criteria.
At 200 °C with 20 s of injection time (Figure 8d): the part shows improved quality but
may not be as perfect as those injected at higher temperatures.
At 200 °C with 15 s of injection time (Figure 8e): the part fails the inspection criteria,
indicating incomplete injection.
Inventions 2024, 9, 124 19 of 24
Figure 8. Quality of plastic samples injected at 230 °C and 200 °C across various time intervals: (a)
sample at 230 °C for 30 s, (b) sample at 230 °C for 25 s, (c) sample at 230 °C for 20 s, (d) sample at
200 °C for 20 s, and (e) sample at 230 °C for 15 s.
4.6.3. Complete Filling in Quantity Measurement
The classication performance of Aurora Vision software demonstrates high accu-
racy, with most specimens being correctly identied (see Table 1). The results for unseen
specimens, which the software had not previously processed, reveal 15 true passes (true
positives), 9 true fails (true negatives), and 1 false pass (false positive), with no false fails
(false negatives) (see Figure 7).
Table 1. Confusion matrix of classication.
Predicted Pass Predicted Fail
Actual pass 15 (TP) 0 (FN)
Actual fail 1 (FP) 9 (TN)
The absence of false fails and the relatively low number of false positives suggest that
the system is eective at distinguishing between acceptable and defective parts. The single
false positive may be aributed to variations in the appearance of defects or inconsisten-
cies in defect presentation, such as lighting conditions, surface texture, or the type of de-
fect. In terms of classication metrics, the software achieved an accuracy of 96%, a preci-
sion of 93.75%, a recall of 100%, and an F1-score of 96.8%. These values indicate that the
software is highly eective, with no false negatives and a strong balance between preci-
sion and recall.
Regarding the assessment of part quality, the specimens produced within the optimal
temperature range of 210 °C and 220 °C demonstrated high-quality injection molds, char-
acterized by complete lling and superior surface nishes. This conrms that the injection
molding process was well controlled in this range, resulting in well-formed parts that met
the quality standards. These results align with the classication outcomes, as the software
Inventions 2024, 9, 124 20 of 24
correctly identied these parts as passes. In contrast, parts produced at 190 °C and 200 °C
exhibited incomplete lling and surface imperfections, such as voids and rough surfaces,
indicating that these temperatures were suboptimal for achieving complete lling and
quality molding. At 230 °C, although the lling was complete, the parts showed signs of
overheating, such as discoloration and warping, highlighting the need for precise temper-
ature control to avoid defects.
These ndings suggest that Aurora Vision software can reliably assess part quality,
conrming the successful correlation between temperature control, complete lling, and
injection mold quality in the optimal range.
While the system performed well with this dataset, further testing with a larger and
more diverse sample is needed to assess its robustness and reliability under varying con-
ditions.
4.6.4. Temperature Eects
The results indicate that 230 °C consistently produced beer-quality parts than 200
°C, particularly when paired with the appropriate injection time. This aligns with the char-
acteristics of HDPE HD2308J, which has a melting point of 131 °C, making higher temper-
atures more suitable for ensuring full material ow and mold lling.
4.6.5. Injection Time Eects
Injection time signicantly inuenced part quality. For 230 °C, 25–30 s of injection
time produced the best results, ensuring complete mold lling. Conversely, 15 s injection
times were insucient, leading to incomplete parts, especially at lower temperatures like
200 °C.
4.6.6. Quality Inspection System Eciency
Aurora Vision software eectively distinguished between fully formed and incom-
plete parts by analyzing image clarity and comparing the percent of area. The system
proved to be a reliable tool for assessing part completeness and provided valuable insights
into the injection molding process.
4.6.7. Relationship with Production Parameters
The results highlight the importance of ne-tuning production parameters such as
motor speed (525 RPM) and inverter frequency (105 Hz). These seings had a direct im-
pact on material ow, mold lling, and part quality, underscoring their role in achieving
consistent outcomes.
4.6.8. Material Properties
The performance of HDPE HD2308J material, with a melting point of 131 °C and a
density of 0.94 g/cm3, was key in determining the optimal processing conditions. The
properties of the material inuenced the ideal temperature and injection time required to
produce parts with minimal defects and consistent quality.
4.6.9. Equipment Specications
The specications of the gear motor (1 HP, 525 RPM), inverter (1 HP, 105 Hz), and
injection screw (1 inch diameter, 25 mm pitch) played a critical role in the injection process
and the resulting part quality. These components ensured the proper ow of material and
facilitated consistent molding under varying conditions.
Inventions 2024, 9, 124 21 of 24
4.6.10. Limitations and Development Opportunities
While the experiments demonstrated the ability to produce high-quality parts, sev-
eral areas for improvement remain:
Enhancing temperature control precision could reduce material degradation and im-
prove consistency across production runs.
Expanding the range of materials that can be processed by the machine would allow
for broader applications and more versatile production capabilities.
5. Optimization Insights, Implications, and Future Directions
This section delves into the broader implications of the study, focusing on the opti-
mization strategies identied, the observed machine performance, and the behavior of
HDPE under various processing conditions. It highlights the practical signicance of the
ndings in optimizing injection molding processes and explores the potential for further
advancements. Moreover, limitations and areas for future research are discussed with the
aim of enhancing the versatility and performance of the machine while contributing to
sustainable recycling practices.
5.1. Optimal Processing Parameters
The results suggest that for the HDPE material used in this study, a temperature
range of 200 °C to 210 °C provides the best balance between consistent weight, good mold
lling, and part quality. This temperature range allows for adequate material ow while
minimizing the risk of overheating and associated defects.
For the specic mold used in the later experiments, a temperature of 210 °C to 220 °C
with an injection time of 15 to 35 s appears to yield the best results. However, these pa-
rameters may need to be ne-tuned based on the specic geometry part and desired char-
acteristics.
5.2. Machine Performance
The low-budget automatic plastic injection molding machine demonstrated reasona-
ble performance, with the ability to produce consistent parts under optimal conditions.
The integration of a laser sensor for overow detection is a valuable feature that helps
prevent mold damage and material waste.
However, the variability observed in weight and part quality across dierent tem-
perature seings suggests that there is room for improvement in temperature control and
overall process stability. Enhancing the temperature regulation capabilities of the machine
could lead to more consistent results across a wider range of operating conditions.
5.3. Material Behavior
The experiments provided valuable insights into the behavior of HDPE under dier-
ent processing conditions. The clear dierences in material ow and part characteristics
across the temperature range tested highlight the importance of carefully selecting pro-
cessing parameters for this material.
The strand-like features observed at lower temperatures and the more homogeneous
texture at higher temperatures demonstrate how temperature aects the ow behavior of
the material and the nal part structure. This information can be crucial for optimizing
part design and mold-lling strategies.
5.4. Process Optimization
This study underscores the importance of systematic experimentation in optimizing
injection molding processes. By methodically varying temperature and injection time, it
was possible to identify the most suitable processing window for the given material and
mold design. This approach can be applied to other materials and part designs, allowing
Inventions 2024, 9, 124 22 of 24
for ecient process optimization without the need for expensive simulation software or
extensive trial-and-error testing.
5.5. Limitations and Future Work
This study presents a low-budget automatic plastic injection molding machine with
signicant potential but identies several limitations and areas for future inquiry. Key
considerations include the necessity to expand the material range beyond high-density
polyethylene (HDPE) to achieve a more comprehensive understanding, as well as the eval-
uation of more complex mold designs to assess machine performance. Preliminary tests
suggest that the machine could also process other thermoplastics such as polypropylene
(PP), polyethylene (PE), polystyrene (PS), polyethylene terephthalate (PET), and acryloni-
trile butadiene styrene (ABS), with estimated optimal processing temperatures for these
materials ranging from 200 °C to 250 °C. Additional detailed evaluations are planned to
conrm these capabilities.
Furthermore, conducting long-term stability tests would provide insights into con-
sistency over extended production runs. The eects of cooling rates on part quality require
further exploration, alongside opportunities for enhancing automation to improve overall
eciency. This study also raises concerns regarding the smoke and gas emissions gener-
ated during operation, highlighting the limitations of relying solely on ventilation and
personal protective equipment such as masks and gloves. Advanced strategies, including
closed-system gas containment and ltration systems, are essential for ensuring safety
and minimizing environmental impact.
Future research will prioritize emissions management. This includes conducting ex-
perimental studies to precisely quantify the types and concentrations of gases emied
during HDPE processing. A focus will also be placed on designing and testing a gas con-
tainment hood equipped with advanced ltration systems to neutralize toxic gases. More-
over, alternative thermoplastics with lower emission proles will be investigated as part
of the eort to improve the sustainability of this technology. In addition, specic aention
will be given to greenhouse gas (GHG) emissions, particularly carbon dioxide (CO2),
which signicantly contributes to climate change [3,4]. Strategies to minimize GHG emis-
sions during processing will include optimizing thermal degradation conditions and ex-
ploring materials with lower carbon footprints.
Overall, while the research demonstrates acceptable results under optimized condi-
tions, future eorts should focus on addressing these limitations to enhance machine ca-
pabilities and ensure user safety.
6. Conclusions
The research on a low-cost automatic plastic injection molding machine, developed
using second-hand materials, has shown promising results, particularly in addressing
plastic waste recycling. This machine successfully converted high-density polyethylene
(HDPE) into valuable products, with optimal operating temperatures being identied be-
tween 200 °C and 210 °C, which minimized weight variations and ensured consistent qual-
ity.
In experiments with a customized mold, a temperature range of 210 °C to 220 °C,
along with an injection time of 25 to 30 s, yielded the best results for mold lling and
product quality. In contrast, lower temperatures (190 °C and 200 °C) led to incomplete
lling, while higher temperatures (230 °C) caused defects such as warping and discolora-
tion. These results highlight the signicant impact of temperature and injection time on
the quality of molded parts.
The addition of a laser sensor for overow detection reduced material waste and
mold damage, improving overall eciency. Aurora Vision software eectively ensured
part quality during production. While the machine performed well under optimized con-
ditions, enhancements in temperature control, long-term stability, and automation are
Inventions 2024, 9, 124 23 of 24
needed. Future research should focus on testing additional materials and addressing
emission mitigation strategies and safety concerns for safe operation.
Author Contributions: Conceptualization, A.S., K.B., and T.S.; data curation, A.S., K.B., and T.S.;
methodology, A.S., K.B., and T.S.; formal analysis, A.S.; investigation, A.S.; software, K.B. and T.S.;
resources, K.B. and T.S.; validation, A.S.; visualization, K.B. and T.S., writing—original draft, A.S.,
K.B., and T.S.; writing—review and editing, A.S.; supervision, A.S. All authors have read and agreed
to the published version of the manuscript.
Funding: This research received no external funding.
Data Availability Statement: The datasets used and/or analyzed during the current study are avail-
able from the corresponding author on reasonable request.
Acknowledgments: The authors thank the College of Advance Manufacturing Innovation at King
Mongkut’s Institute of Technology Ladkrabang for partial nancial support.
Conicts of Interest: The authors declare no competing interests. The authors also declare that they
have no known competing nancial interests or personal relationships that could have appeared to
inuence the work reported in this paper.
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