Page 17 - IMDR Journal 2025

Research Article
Systems that analyze data and learn from patterns to make ● Importance of IoT in Advanced Manufacturing
decisions.
IoT acts as the digital nervous system in a smart factory. It
● Big Data Analytics: Evaluation of large datasets to enables seamless integration between different systems,
improve production efficiency and predict issues. machines, and even supply chains.
● Cloud Computing: Remote data storage and analysis Key components include
capabilities for better scalability.
● Smart Sensors: These are the core of IoT, gathering real-
● Autonomous Robots: Robots that work independently or time data on machine status, production output,
alongside humans, adapting in real time. temperature, vibration, and more.
The Trans formative Effects of IoT in Smart Manufacturing ● Edge Devices: Allow data to be processed closer to the
The use of IoT in manufacturing operations has been a source rather than sending everything to the cloud. This
game-changer. Here are some of the main areas where IoT ensures faster responses and reduces bandwidth costs.
brings quantifiable value: ● AI Integration: Boosts decision-making by using machine
● Enhanced Production Efficiency learning models to analyse trends and predict outcomes.
IoT enables machines to talk to each other and to central ● IIoT Platforms: Provide centralized dashboards to monitor
systems. This enables real-time observation of operations everything from production lines to factory-wide
and process adjustment in real-time. In the event that a performance metrics.
machine is operating slower than it should, for example, the The Benefits of IoT Adoption in Manufacturing
system can reassign jobs or adjust the production schedule in
an instant. 1. Rapid Design-to-Delivery IoT enables in-process
evaluation in real-time and dynamic reorganization of
● Predictive Maintenance production lines, supporting faster ordering and fulfilment
Traditionally, maintenance is done on a scheduled interval within the design-to-delivery cycle.
or after the breakdown that has been set. IoT systems make 2. Operational Visibility Increased visibility improves
use of sensors that monitor machine performance management and control since each phase of the production
constantly. AI algorithms can predict failures before hand, process is monitored.
so intervention on schedule and minimizing downtime.
3. Improved Cost-Effectiveness Robotic equipment,
● Smart Inventory Management automated systems, and machine maintenance in optimal
IoT-enabled systems monitor inventory levels with RFID condition along with energy harvesting systems all allow for
tags and intelligent sensors. They update inventory records greater emphasis on operating costs.
automatically, order when inventory is low, and notify 4. Enhanced Safety Record IoT sensor-based safety alarm
managers of imbalances. This promotes lean inventory and emergency shutdown systems reduce the likelihood of
levels and prevents storage costs. accidents.
● Real-Time Supply Chain Visibility 5. Enhanced Customer Retention Quicker delivery of highly
IoT enhances supply chain management by providing real- customized products results increased customer satisfaction
time tracking of shipments, condition monitoring of and retention and encourages
products (e.g., temperature products), and route 6. Risks of IoT Adoption
optimization. This provides quicker, more accurate delivery
and enhanced customer satisfaction. 1. Cybersecurity Threats As more devices go online, there is
an even bigger attack surface. Vulnerable weak points in the
● Customization and Flexibility network are attacked by hackers for sensitive information
With IoT and AI-based systems, manufacturers can quickly extraction or control access seizure.
shift between production lines to produce customized 2. Challenge to Integrate New Technologies Challenges of
products without lengthy setup time or expense. This "mass adoption from still accumulating legacy infrastructure that
customization" strategy addresses contemporary can be incompatible with IoT paradigms occur holding up
marketplace needs for customized products. the companies that needs to be transferred to modern agile
● Quality Assurance and Inspection systems.
High-definition cameras paired with AI software and data 3. Information Collected and Stored Without Filtering:
from IoT devices can examine every item exiting the Failure to filter analytics and
production line. Anything defective is caught immediately, huge data may lead to flooded systems hence having to
eliminating waste and rework, and enhancing the overall curate frameworks for automated systems.
quality of products.
4. High Upfront Cost Sensors, implementation platforms
● Energy Optimization and training cost enormous funds hence making it losing
IoT systems can detect places where energy is being used high upfront returns on investment.
excessively by monitoring energy usage around the clock. 5. Niche Industry Skill Gaps Identified Recent shortages of
They can also recommend optimizations. This serves skilled labor have are noted. Employees need to be trained
sustainability efforts by lowering carbon footprints and and upskilled to work in such an environment.
energy expenditures.

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