Introduction
The Internet of Things (IoT) is transforming manufacturing operations around the world. By connecting machines, assets, and processes digitally, manufacturers gain unprecedented visibility into their operations. This allows them to optimize productivity, reduce downtime, and increase flexibility.
As per McKinsey, the global IoT market in manufacturing will grow to $153 billion in 2024, delivering over $500 billion in value. I believe the adoption of IoT will accelerate as costs decrease and as new applications emerge. In this article, I aim to provide an in-depth look at how IoT is impacting manufacturing today and share my vision for how it will evolve by 2024.
Current State of IoT in Manufacturing
IoT is already delivering major benefits across manufacturing operations. Here are some of the key applications:
Predictive Maintenance
By connecting sensors to equipment like motors and pumps, manufacturers can monitor machine health in real time. Advanced analytics can detect early warning signs of failure so maintenance can be scheduled proactively. This prevents unexpected downtime and optimizes maintenance costs.
- GE estimates that predictive maintenance can reduce unplanned downtime by 10-20% and maintenance costs by 5-10%.
Asset Tracking
Connecting RFID tags or GPS to parts and capital equipment allows manufacturers to track their location and status. This delivers a real-time view of inventory and assets, improving capital efficiency.
- Boeing is using IoT tracking to reduce the search time for airplane parts inventory by 60%.
Process Optimization
Sensors can monitor all types of manufacturing processes in real time (e.g. temperature, pressure, humidity). When combined with data analytics, manufacturers can identify process optimization opportunities to improve quality, throughput, and yields.
- Siemens estimates their IoT-enabled optimization systems can improve throughput by 5-10% in process industries.
Key IoT Technology Trends Driving Adoption
Several technology trends are accelerating the adoption of IoT in manufacturing:
Improved Sensors
Sensors are the “eyes and ears” of an IoT system. Cheaper, lower-power, and more capable sensors are enabling new use cases. MEMS technology has expanded sensor applications.
5G Connectivity
5G networks promise faster speeds, lower latency, and support for more devices. This will expand the potential for real-time control applications across manufacturing.
Edge Computing
Processing data closer to the source reduces latency and allows for real-time process adjustments. Gartner expects 50% of industrial data to be processed at the edge rather than the cloud by 2023.
Digital Twin Technology
Digital twins are virtual representations of physical assets and processes. They enable better insights and predictive capabilities from IoT data. Accenture estimates digital twins can reduce product development costs by up to 50%.
AI-Enabled Analytics
AI techniques like machine learning and computer vision are unlocking more value from sensor data. This enables predictive capabilities and improved automation.
The Manufacturing Plant of the Future
By 2024, these technology trends will enable a fully connected, intelligent manufacturing plant. Here is my vision for how IoT will transform operations:
Complete Visibility
The plant floor and supply chain will feature end-to-end visibility. Sensors will track the status of all assets and materials in real time. Operators will have a 360-degree view of plant operations.
Predictive Insights
AI will detect patterns in data to predict failures, maintenance needs, quality issues, and more. Operators will receive predictive alerts and be able to simulate different scenarios.
Modular Automation
Robots and machines will adapt flexibly to changes via modular automation and software-defined capabilities. Production lines can be reconfigured quickly based on demand.
Digital Twin Integration
The physical plant and processes will have a complete digital twin. Engineers can experiment and optimize the digital twin first before applying changes.
Closed-Loop Control
With edge computing, data is analyzed locally to enable real-time process adjustments and control. This creates a seamless feedback loop between physical and digital systems.
Human-Machine Collaboration
Operators, machines, robots, AI, and more will seamlessly collaborate via the IoT network. Humans focus on higher-level, creative tasks.
Key Challenges to Address
To fully realize this vision, there are some key challenges manufacturers need to address:
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Legacy equipment must be connected and retrofitted into the IoT environment. This requires hardware, software, and integration costs.
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Data security is paramount with more devices connected. Manufacturers need to ensure their data and operations are resilient to cyber threats.
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Data silos need to be broken down. Data must flow seamlessly from sensors to visualization to actuators via common architectures.
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In-house expertise must be developed to launch, scale, and maintain IoT systems over the long term. Personnel may need retraining or hiring.
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Open platforms and standards are needed to avoid vendor lock-in. Manufacturers need flexibility to source IoT components from different vendors.
Conclusion
The manufacturing industry will reap tremendous benefits as IoT adoption accelerates through 2024. With end-to-end connectivity, intelligent devices, and advanced analytics, manufacturers will achieve new levels of productivity, flexibility, and efficiency.
However, to fully realize this potential, companies need to invest strategically in IoT platforms, while addressing key challenges like legacy equipment, security, data integration, talent development, and standards. By proactively managing these areas, manufacturers can ensure their operations are “intelligence delivered” by IoT.
