INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 942
Prin Track_ Real-Time Workflow Monitoring Management and
Inventory using Predictive Analytics and Logistic Regression
Algorithm for Designers Print
Mel Shandlar R. Blando
1
, John Paul M. Mangana
2
, Sophia Lorrine P. Acebron
3
, Daniel M. Maure
4
,
Dina Cura
5
, Marisol De Guzman
6
123456
(SY 2025-2026) Arellano University, Pasig Campus
DOI: https://dx.doi.org/10.51584/IJRIAS.2025.1010000077
Received: 21 September 2025; Accepted: 26 September 2025; Published: 07 November 2025
ABSTRACT
The PrinTrack System is a web-based workflow monitoring and inventory management platform developed to
enhance the efficiency, accuracy, and transparency of customized printing operations. It enables administrators
and operators to monitor order progress, manage inventory, and track production status in real time. Developed
for Designer’s Print, a small-scale printing company specializing in customized shirts, mugs, and stickers, the
system addresses issues related to delayed tracking, miscommunication, and inefficiency in manual monitoring
processes. PrinTrack, a real-time workflow monitoring and inventory management system that utilizes predictive
analytics through the Logistic Regression algorithm to enhance operational efficiency for Designers Print. It
seeks to predict product demand and workflow status, enabling data-driven decisions for inventory control and
resource allocation. PrinTrack also offers administrative control, live notifications, and an organized database
structure for efficient record management.
The study employed a quantitative research design using structured surveys and system testing to collect
measurable data regarding the system’s functionality, reliability, and usability. Developed using PHP for
backend processes, JavaScript and CSS for user interface design, and MySQL for database management, the
system utilizes data visualization tools to monitor workflow and inventory in real time. The study utilized the
Iterative Methodology, allowing the system to be continuously developed, tested, and refined based on user and
expert feedback. This approach ensured that improvements were made in each cycle, enhancing the system’s
reliability, usability, and overall performance. In accordance with the ISO 25010 Software Quality Model, the
system was evaluated in terms of Reliability, Efficiency, Usability, Security, and Portability by 50 respondents
comprising 40 users and 10 technical experts. Their evaluation provided comprehensive insights into both user
experience and technical functionality, ensuring that the system met quality standards and operational
effectiveness.
PrinTrack is a web-based system that enhances workflow monitoring and inventory management for Designer’s
Print using predictive analytics through the Logistic Regression algorithm. The system effectively improved
operational efficiency, reliability, and usability based on ISO 25010 evaluations from users and technical experts.
It is recommended to integrate mobile accessibility and advanced analytics to further enhance system
functionality and decision-making efficiency.
Keywords: PrinTrack, Workflow Monitoring System, Real-Time Inventory, Logistic Regression Algorithm,
Customized Product Manufacturing, PHP, MySQL, Iterative Methodology, Predictive Analytics, ISO 25010
INTRODUCTION
Operational effectiveness and real-time production monitoring are essential elements of customer satisfaction
and business success in the customized product manufacturing industry, especially for companies making
personalized stickers, mugs, and hats. Due to the personalized nature of bespoke items, conventional manual
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 943
tracking techniques frequently result in inefficiencies including incomplete orders, misunderstandings between
departments, and opaque manufacturing processes.
For companies of all sizes, the Smart Inventory Management System is a complete solution that makes inventory
tracking, order management, and restocking easier. Through automation and real-time monitoring, it guarantees
that companies keep the proper stock levels, avoid shortages, and steer clear of overstocking. Enhancing retail
productivity and profitability requires careful inventory control and sales analysis. To find product linkages and
improve cross-selling prospects, this project offers a data-driven methodology that incorporates association
analysis. (K.R. Aswathy et al., 2025).
The company was officially established in January 2021. By April of the same year, 77 P. Visitacion, Brgy.
Kalawaan, Pasig City the business began hiring its initial team members to support its growing operations.
According to the company's co-founder, the idea to start the business came from a shared vision between him
and a former colleague and close friend, both of whom previously worked as engineers in a construction firm.
The company currently faces challenges in efficiently tracking and managing customized product orders,
especially when the owner is away from the physical location. Without a centralized and accessible system,
monitoring the progress of each order and maintaining accurate inventory records becomes difficult, leading to
delays, miscommunication, and potential errors in fulfilling customer requests. As the business grows and the
volume of online orders increases, manual tracking methods become less practical and more prone to mistakes.
Therefore, there is a critical need for an online system that provides real-time visibility into order statuses and
inventory levels. Such a system will enable the owner and staff to monitor operations remotely, ensure timely
production, and maintain sufficient stock, ultimately improving customer satisfaction and operational efficiency.
The specific objectives of the study are to:
1. To create a real-time monitoring system that uses Logistic Regression functions
2. To update the status of ongoing production automatically, eliminating the need for human refreshes.
3. To develop a dashboard for inventory tracking that displays restock levels and available supplies, along
with automated notifications when inventory hits a critical level.
4. To create a product monitoring tool that shows the estimated time of completion and manufacturing status
of each item, automatically updating when a stage is finished or delayed.
5. To create a workflow monitoring module that walks users through the printing process step-by-step and
advances to the next step automatically when tasks are completed.
6. To provide an assessment framework based on ISO/IEC 25010 in order to evaluate the system's security,
usability, efficiency, and functionality in real-time.
Scope
The main features and capabilities that facilitate the effective tracking of orders, inventory, and production
workflows are covered by PrinTrack: Real-Time Workflow Monitoring Management and Inventory. Each of the
system's five primary divisions is crucial to maintaining efficient operations and accurate reporting.
The key features integrated into the system include:
Orders
• Allows admins to monitor all ongoing jobs
• Displays key details like Order ID, workflow status, and priority level.
• Includes a search function and tools to move orders through different production stages.
• Helps manage production queues and prioritize tasks efficiently.
Finished Orders
• Logs all completed jobs for reference and reporting.
• Provides a summary table with order details and timestamps.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 944
• Includes visual reports such as monthly bar charts and product distribution pie carts.
• Supports post-production review and performance analysis.
Analytics
• Offers real-time insights through graphs and charts.
• Displays orders per day, workflow distribution, and priority breakdown.
• Tracks weekly order trends to help with planning and forecasting.
• Assists in identifying busy periods and balancing workloads.
Instructions
• Provides detailed, categorized printing instructions for different products.
• Ensures production consistency and quality control.
• Acts as a guide for staff during each step of the workflow.
Inventory
• Monitors stock levels of materials needed for production.
• Tracks usage history and remaining supplies.
• Sends alerts when items fall below the restock threshold.
• Helps prevent delays due to missing materials.
LIMITATION
The creation of a web-based, real-time production status display system tailored for print-on-demand companies
is the exclusive focus of this project. To simplify and automate the tracking of printing operations, inventory
levels, workflow procedures, and product status, the system makes use of a logistic regression algorithm. The
fact that this project will only run online and needs a steady internet connection to work properly is one of its
main limitations. This system's primary functionality depends on real-time data processing and cloud-based
monitoring, hence it cannot be used offline or deployed standalone. Although this restriction guarantees that data
is current and remotely available, it may also limit system usability in places with erratic or inadequate
connectivity. Furthermore, features pertaining to marketing or advertising are not supported by the system.
Features like sponsored content, banner ads, and product promotions are purposefully left out because the
system's main goal is to improve operational efficiency and visibility in the manufacturing setting, not to act as
a platform for commerce. Task automation, real-time reporting, and production management are given top
priority in this system, which is designed for internal corporate use. Therefore, tasks not directly associated with
manufacturing processes are outside the scope of this project's intended design and execution.
THEORETICAL FRAMEWORK
Figure 1: Process of Manufacturing A Customized Product
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 945
The following collection of ideas, theories, concepts, and presumptions aids in comprehending the study
question:
Predictive analytics
Involves using historical or observed data to forecast future outcomes or classify trends in a dataset. In this
study, logistic regression is applied as the primary predictive model to estimate the probability of a specific result
based on identified variables. By mapping input data into a sigmoid function, logistic regression converts linear
combinations of predictors into probability scores that determine class membership. This approach enables the
system to analyze existing patterns, evaluate critical relationships among variables, and generate outcome
predictions with measurable accuracy. Through predictive analysis, the research can provide data-driven insights
that support informed decision-making and improve system performance.
Logistic Regression
It is used in the PrinTrack system to predict whether a product or print design will fall into the lowest-selling or
highest-selling category by analyzing historical and real-time sales data. It takes different factors such as
customer demand, order frequency, and inventory levels, and converts them into probability values using the
sigmoid function. Based on these probabilities, PrinTrack can classify which products are likely to perform well
and which may underperform. This allows the system to support better inventory planning, avoid stock shortages
or excess supplies, and help designers focus on high-demand print items.
CONCEPTUAL FRAMEWORK
Figure 1: Process of Manufacturing A Customized Product
This conceptual framework explains how the proposed system functions using the Input–Process–Output (IPO)
model as its structure. It outlines how data flows and transforms throughout the system to deliver its intended
results
The PrintTrack system processes collected data through several automated operations:
1. Input Stage – The system collects sales data, inventory updates, order frequency, and timestamps to
monitor what products are being purchased and how often they are requested in real time.
2. Process Stage – PrinTrack uses Predictive Analytics and a Logistic Regression Algorithm to classify
products as highest-selling or lowest-selling based on changing demand and sales trends.
3. Output Stage – The system provides real-time insights on product performance, sends alerts for low-
demand inventory, and updates the dashboard to support faster and smarter decision-making for designers
and staff.
4. Feedback Loop – Continuous data input helps refine future predictions, ensuring that PrinTrack becomes
more accurate over time in managing workflow efficiency and material allocation.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 946
Significance of The Study
The following collection of ideas, theories, concepts, and presumptions aids in comprehending the study
question:
• Employee/Client: This study provides a practical and affordable tool for small to medium manufacturing
businesses to track production in real time. Using a logistic regression algorithm, the system automates
updates, reduces manual errors, and improves workflow visibility. Through a centralized dashboard, staff
and administrators can easily monitor orders, prioritize tasks, and coordinate better, leading to smoother
operations. Although customers don’t directly use the system, they benefit from faster processing, on-time
deliveries, and improved service quality.
• Customers: Customers can view the progress of their orders from design to delivery without editing access.
This promotes transparency, builds trust, and keeps them informed in real time, improving satisfaction and
confidence in the service.
• Students/Researchers: For students and researchers, this project can serve as a model for future studies in
smart manufacturing and real-time monitoring. It encourages further innovation, such as adding IoT
integration, customer notifications, or inventory tracking. Academically, it shows how logistic regression
programming and system design can solve real business challenges effectively.
REVIEW OF RELATED LITERATURE
The collected foreign and local literature and studies present a cohesive view of the growing relevance and
impact of logistic regression, real-time monitoring systems in the context of Industry 4.0. A common thread
among these works is the emphasis on intelligent automation, real-time responsiveness, and the reduction of
manual intervention in industrial and production settings all of which strongly align with the goals and design
of the capstone project, PrinTrack.
The foreign studies reviewed One of the most significant uses in the Industry 4.0 era is smart manufacturing
systems (SMS), which have many benefits over conventional production systems and are quickly being adopted
by manufacturing companies as a performance-enhancing tactic. SMS is a cutting-edge and well-liked
manufacturing setup that creates ever-more-intelligent production systems, but designers still need to adjust to
the needs and preferences of businesses. Functional and non-functional, technological, economic, social, and
performance assessment components that are critical to SMS evaluation are identified and evaluated in this study
using an analytical and descriptive research methodology. In order to evaluate business requirements and
prioritize and propose SMS services, a predictive analytics framework, a crucial part of many decision support
systems is employed.
Predictive and prescriptive maintenance permits various industries to analyze historical data in real time for the
purpose of optimization of industrial operations, such as production, manufacturing, etc. to increase productivity
and cumulative outcome. It considers three essential indicators of availability, quality, and performance. This
article presents the unique condition-monitoring-based predictive maintenance framework incorporated into the
modern world to create a machine-learning-based predictive maintenance approach for automotive industries.
The proposed framework has been validated by collecting the raw data from the water pump machine through
sensors to preprocess and analyze the performance indicators. The equipment's remaining useful lifetime was
calculated based on the data points acquired in real time by calculating the adjacent variation. The developed
dashboard has allowed the visible monitoring of all possible anomalies and the remaining useful life of
equipment while the machine runs in real time.
Synthesis
In summary, the reviewed materials validate the core design of PrinTrack and highlight areas for future
enhancement, including greater automation, predictive analytics, and advanced scheduling mechanisms. The
consistency of themes across local and international sources supports the conclusion that PrinTrack is a timely
and strategic response to the ongoing digital transformation in manufacturing, offering real-world value even as
it evolves toward full smart system integration.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 947
METHODOLOGY OF THE STUDY
This study uses a Quantitative Research Design, focusing on the development of a web-based platform called
PrinTrack, designed to improve production monitoring and inventory management for customizable product
manufacturers.
In PrinTrack: Real-Time Workflow Monitoring Management and Inventory using Predictive Analytics and
Logistic Regression Algorithm for Designers Print, logistic refers to the effective organization and movement
of materials, tasks, and inventory to ensure smooth and timely printing operations. By applying Logistic
Regression, the system can also predict workflow outcomes, helping optimize scheduling, reduce delays, and
improve overall production efficiency.
The research involves selected company staff and administrators who are directly engaged in daily production
activities. Using a purposive sampling method, only participants with relevant experience in managing or
monitoring production were included to ensure accurate and meaningful feedback for system development.
To gather data, the researchers used survey questionnaires and informal interviews to understand existing
workflows, common production issues, and user requirements. Additional information was collected from order
logs, inventory sheets, and production schedules to analyze current processes. This data served as the foundation
for designing the system’s features and functionality. Feedback from users during testing was used to enhance
system performance, reliability, and user experience. All data collection followed ethical standards, including
informed consent and data privacy compliance, to ensure the confidentiality and security of participant
information.
Figure 3: SDLC Iterative Model
The PrinTrack system follows the Iterative Model of the System Development Life Cycle (SDLC). This
approach allows the system to be developed in multiple stages, where each iteration includes planning, designing,
coding, and testing. Feedback from every cycle is used to make continuous improvements before moving to the
next stage. The iterative model is ideal for PrinTrack because it supports gradual refinement, early detection of
errors, and real-time adjustment of features.
The database design for PrinTrack is structured to store and manage data efficiently, including customer orders,
production status, inventory levels, and staff activities. Relationships between database tables ensure data
consistency and reliability across all modules. Below is a simplified context diagram illustrating the main data
flow and interaction within the PrinTrack system.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 948
Figure 4: Context Diagram
The PrinTrack Context Diagram shows how the system communicates with outside parties including
administrators, production workers, and e-commerce platforms. It acts as a high-level summary, illustrating the
data flow between users and the PrinTrack system. The system receives orders from sites such as Shopee and
TikTok Shop, and uses logistic regression updates to track and manage them in real time. Updates from
production workers are processed and displayed on real-time dashboards that administrators and the company
owner can view. Additionally, an internal inventory database that tracks material levels and sends out
notifications when supply is low is connected to the system. Overall, the graphic shows how PrinTrack facilitates
effective, real-time production monitoring and inventory control, centralizes processes, and improves
cooperation.
Respondents of the Study
The respondents of the study are divided into two groups:
• Users: The 40 users were customers or employees from small to medium-sized businesses that make
customized products. They used the system in their daily work to track orders and manage tasks. They
tested PrinTrack and gave feedback on its ease of use, clarity of updates, and usefulness in their jobs.
• Technical Experts: The 10 technical experts were IT professionals and developers with at least one year
of experience. They evaluated the system’s design, security, speed, and potential for future improvements.
The researchers used purposive sampling to ensure that all participants were relevant to the study. This means
participants were chosen based on their experience and role rather than at random. The goal was not to represent
a large population but to gather accurate and meaningful feedback from people directly involved in production
and system development.
In total, 50 respondents participated in the evaluation.
Development And Evaluation Procedure
The development of “PrinTrack_ Real-Time Workflow Monitoring Management and Inventory using Predictive
Analytics and Logistic Regression Algorithm for Designers Print ” is guided by the Agile methodology, allowing
the system to evolve through continuous feedback and testing. The researchers used several programming
languages and development tools to ensure that the system is functional, user-friendly, and efficient. Each tool
played an important role in building and testing both the frontend and backend components.
The main development tools include:
• HTML5: Structured the system’s web pages and interface layouts.
• CSS: Designed a responsive, modern, and user-friendly interface for both administrators and members.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 949
• JavaScript: Added interactivity, enabling form validation, dynamic content, and smooth navigation.
• PHP: Served as the main backend language responsible for handling logic, user authentication, and
database interaction.
• MySQL: Functioned as the database system for storing user records, attendance logs, and payment
transactions.
• XAMPP: Provided the local testing environment integrating Apache, MySQL, and PHP.
• Visual Studio Code: Used as the main programming editor for writing and managing code.
The evaluation procedure followed a structured approach to determine the system’s functionality, usability, and
reliability. The assessment is based on the ISO 25010 software quality standard, which evaluates the following
aspects:
Functionality
PrinTrack ensures long-term efficiency and flexibility through modular design and logistic regression
mechanisms. It uses real-time tracking and widely supported technologies like PHP, MySQL, and JavaScript for
scalability, easy maintenance, and sustainable performance.
Reliability
PrinTrack prioritizes stable performance and minimal downtime through early issue detection and continuous
testing. Regular updates and quality assurance maintain system reliability and address bugs based on user
feedback.
Efficiency
PrinTrack focuses on fast processing, responsive performance, and optimal resource use. The system evaluates
algorithm speed, platform responsiveness, and practical usefulness to ensure smooth operation and effective
results.
Usability
PrinTrack is designed to be simple, intuitive, and user-friendly for all types of users. Continuous user feedback
and testing ensure that the interface remains easy to navigate and aligned with user needs.
Security
PrinTrack protects user data through strong authentication, data encryption, and access control. It ensures
accountability and data integrity by tracking user actions and maintaining secure communication.
Portability
PrinTrack runs efficiently on different devices, browsers, and operating systems. Its cross-platform design allows
easy installation, updates, and scalability for businesses with multiple locations.
Data Analysis Plan
The evaluation of the system is guided by the ISO/IEC 25010 Software Quality Model. This model is chosen
because it aligns with the objectives of PrinTrack in ensuring functionality, security, and usability for both gym
administrators and members.
To interpret the responses gathered from the evaluation forms, the researchers utilized appropriate statistical
tools that helped analyze and validate the system’s performance. These methods provided a clear and structured
understanding of the overall user perception of the system’s effectiveness.
• Weighted Mean: This tool is used to determine the overall level of agreement among respondents for each
ISO 25010 criterion. It allowed the researchers to identify how strongly users and technical experts agreed
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 950
on the quality aspects of the system.
• Frequency Percentage: This statistical tool presented the distribution of responses in percentage form,
providing a visual understanding of how often a particular rating was chosen.
Figure 5: Likert Scale and Interpretation
A four-point Likert Scale is employed to evaluate respondents’ level of satisfaction with the system’s usability,
efficiency, and reliability. This scale provided a structured way for users to express their perception of system
quality.
• The scale ranged from 1 to 4, representing Strongly Disagree (1), Disagree (2), Agree (3), and Strongly
Agree (4).
• Each statement in the evaluation form corresponded to one of the ISO 25010 characteristics, enabling the
researchers to assess each software quality attribute objectively.
• Responses are then interpreted statistically to determine the overall level of satisfaction and system
acceptability.
This rating approach ensured that the evaluation results of the PrinTrack system were presented objectively and
could be analyzed to measure how effectively the system fulfilled its intended functions based on user and
technical feedback.
The System
The PrinTrack: A Real-Time Manufacturing Status Display with logistic regression is a web-based system
designed for print-on-demand businesses to efficiently track and manage production. It automates order updates
across all stages of design, printing, quality check, packaging, and delivery through a centralized dashboard and
notification system. This allows staff and admins to monitor real-time progress, reducing delays and human
errors while improving transparency. Developed using PHP, JavaScript, HTML, CSS, and MySQL, PrinTrack
ensures smooth workflow management and accurate order tracking. The system can also integrate with e-
commerce platforms like Shopee and TikTok Shop for automatic order syncing. Evaluated under ISO 25010
standards, PrinTrack demonstrates high reliability, usability, and efficiency, making it a practical and effective
solution for small to medium print-on-demand businesses. ISO 25010 standards, the system ensures reliability,
security, accuracy, efficiency, and portability.
Figure 5: Likert Scale and Interpretation
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 951
The Admin Dashboard serves as the central hub where administrators can oversee and control the entire system.
Its purpose is to manage users, monitor activities, and maintain smooth system operations.
Figure 6: User/Customer Dashboard
The Customer’s Dashboard serves as the main interface where customers can view and manage their personal
information, activities, or transactions. Its purpose is to give users quick access to important features and updates
in a centralized location.
Figure 7: Employee Dashboard
The Employee Dashboard serves as the main workspace where employees can access tools, tasks, and
information related to their role. Its purpose is to help staff manage operations efficiently and monitor their
responsibilities in one place.
Assessment: Summary of Respondents on The System
The table presents the distribution of respondents involved in the system evaluation, categorized into user and
technical groups. The assessment is conducted following the ISO 25010 Software Quality Model to ensure a fair
and reliable evaluation of the system’s usability and technical performance. This classification provides a clear
overview of the participants who contributed feedback based on their experience and expertise.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 952
Table 1: Distribution of the Respondents
Table 1 presents the total number and percentage of participants who took part in evaluating the system. Among
the 50 respondents, 40 individuals or 80% are users, and 10 persons or 20% are technical evaluators. This
indicates that the majority of the feedback is gathered from users, while the technical group contributed expert
assessments to ensure the system’s functionality and performance are properly reviewed.
Table 2. Summary of Respondents’ Assessment on the PrinTrack System Based on ISO 25010 Standards
Table 2 presents the overall summary and comparison of evaluations from both user and technical respondents
based on the ISO 25010 criteria. The user group obtained an overall average mean of 3.5, interpreted as Strongly
Agree, while the technical group achieved an average mean of 3.6, also interpreted as Strongly Agree. Among
all the criteria, Portability received the highest rating from users with a weighted mean of 3.6, whereas Accuracy
received the top score from technical respondents with a weighted mean of 3.7, showing strong confidence in
the system’s accessibility and stable performance. Meanwhile, Efficiency earned the lowest rating from users
with a weighted mean of 3.5, indicating slight areas for enhancement in system speed and responsiveness. In
general, both groups agreed that the system satisfies the ISO 25010 standards, reflecting overall confidence in
its functionality, reliability, and ease of use.
Ethical Considerations
The development of PrinTrack focuses on keeping data accurate, private, and secure. All information is used
only to monitor and improve production. The developers make sure the system is fair and that no company data
is shared or misused. Regular updates and maintenance are done to keep it safe, reliable, and ethical for
manufacturing use.
Summary
PrinTrack is a web-based system that helps print-on-demand businesses track orders in real time. It automates
updates for each production stage from design and printing to checking, packing, and delivery. The system has
a dashboard and notification feature so staff and admins can easily monitor progress. It helps prevent delays,
reduce errors, and improve transparency. PrinTrack can also connect with e-commerce sites like Shopee and
TikTok Shop to sync orders, making production faster, more accurate, and easier to manage.
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue X October 2025
www.rsisinternational.org
Page 953
CONCLUSION
The study had both users and technical respondents evaluate PrinTrack’s performance using the ISO 25010
quality model. Results showed that both groups gave high ratings in all six areas: functionality, reliability,
efficiency, usability, security, and portability, with average scores of 3.5 to 3.6 (Strongly Agree). This means
PrinTrack is reliable, efficient, and easy to use. Technical respondents focused on system performance, while
users valued its simplicity and navigation. Overall, both groups agreed that PrinTrack meets its goals and is
effective for monitoring production in print-on-demand businesses.
RECOMMENDATION
Future developers are encouraged to improve PrinTrack by adding offline features so it can still work without a
strong internet connection. They can also expand its connection to platforms like Shopee and TikTok Shop to
automatically sync orders. Adding features like inventory tracking, mobile access, and detailed reports can make
it more useful for managing production. Collecting feedback from users will also help keep PrinTrack easy to
use and effective for businesses.
REFERENCES
1. Cheng, C., Pourhejazy, P., Hung, C., & Yuangyai, C. (2021). Smart Monitoring of Manufacturing
Systems for Automated Decision-Making: a Multi-Method Framework. Sensors, 21(20), 6860.
https://doi.org/10.3390/s21206860
2. Yin, Y., Wan, M., Xu, P., Zhang, R., Liu, Y., & Song, Y. (2023). Industrial product quality analysis based
on online machine learning. Sensors, 23(19), 8167. https://doi.org/10.3390/s23198167
3. Sharma, R., & Villányi, B. (2022). Evaluation of corporate requirements for smart manufacturing systems
using predictive analytics. Internet of Things, 19, 100554. https://doi.org/10.1016/j.iot.2022.100554
4. Aswathy K.R., Shaji A.M, Athul M., Bhavya K., (2025) Smart Inventory Management System,
https://www.researchgate.net/publication/390684013_Smart_Inventory_Management_System
5. Yambao, J., Miranda, J. P., & Pelayo, E. L. (2023). Development of augmented reality application for
Made-to-Order furniture industry in Pampanga, Philippines. International Journal of Computing Sciences
Research, 7, 1487–1497. https://doi.org/10.25147/ijcsr.2017.001.1.112
6. Singh, S., Batheri, R., & Dias, J. (2023). Predictive Analytics: How to improve availability of
manufacturing equipment in automotive firms. IEEE Engineering Management Review, 1–14.
https://doi.org/10.1109/emr.2023.3288669
7. Gao, S., Yang, D., Zhang, X., & Dai, W. (2024). A Real-Time scheduling method for industrial edge
applications based on event types. A Real-Time Scheduling Method for Industrial Edge Applications
Based on Event Types, 1–6. https://doi.org/10.1109/isie54533.2024.10595785
8. Revilla-León, M., Meyer, M. J., Zandinejad, A., & Özcan, M. (2020). Additive manufacturing
technologies for processing zirconia in dental applications. International Journal of Computerized
Dentistry, 23(1), 27–37.https://pubmed.ncbi.nlm.nih.gov/32207459/
9. Luzon-German, C., & Evangelista, R. (2024). Real-time water level monitoring system in Oriental
Mindoro using neural networks. Journal of Innovative Technology Convergence., 6(2), 99–
108.https://innocon.innotcs.org/index.php/jitc/article/view/112
10. Haldos, R. R. C., Abu, P. A. R., Oppus, C. M., & Reyes, R. S. J. (2020). Real-time Monitoring of the
Semiconductor Wirebond Interconnection Process for Production Yield and Quality Improvement.
Ateneo de Manila University. Link: https://archium.ateneo.edu/ecce-faculty-pubs/71/
11. Barroga, K., & Wabina, V. E. R. (2022, March). Smart manufacturing: National implementation
framework (Philippines). In Smart Manufacturing: National Implementation Framework (pp. 72–100).
Asian Productivity Organization. https://www.apo-tokyo.org/publications/papers/smart-manufacturing-
national-implementation-framework/
