by The Industrial Internet of Things (IIoT) refers to the interconnectivity of industrial machines and devices via the internet. With embedded sensors, actuators and networking capabilities, these devices are able to autonomously exchange data within an industrial network. By establishing real-time data connectivity in industrial operations, the IIoT enables predictive maintenance, remote monitoring and other applications that deliver efficiency, productivity and cost savings benefits.
Enabling Advanced Asset Management
One major industrial internet of things application is advanced asset management through condition-based monitoring of industrial equipment. By deploying sensors to continuously track operating parameters like vibration, temperature and pressure, manufacturers can gain real-time visibility into equipment health. This sensor data is transmitted over the network to analytics platforms that can detect early signs of failure or performance degradation. Predictive maintenance alerts allow issues to be addressed before costly downtime occurs. Remote monitoring also reduces the need for on-site inspections and diagnostics. With automated insights into asset performance, maintenance schedules can be optimized based on actual equipment usage and wear rather than predetermined cycles. This improves uptime while lowering service costs.
Facilitating Process Optimization
Beyond asset management, the industrial internet of things enables deeper process optimization across industrial operations. Embedded sensors provide a continuous stream of production data that reveals bottlenecks, inefficiencies and quality variances. Analytics tools help identify correlations to optimize settings like temperature, speed, flow rate and more. This process data combined with real-time production schedules allows for dynamic adjustments that maximize output. The IIoT also facilitates remote process monitoring and control. Engineers can remotely tweak processes from anywhere without needing to be physically present on the plant floor. Performance can be fine-tuned on an ongoing basis for consistently optimal output.
Enhancing Worker Safety and Productivity
Workflows and tasks on the production floor present inherent safety risks to employees. The IIoT enhances safety through automated process monitoring and alerts. Sensors integrated with safety systems can detect erratic machine movements or high-risk conditions. Real-time alerts allow remote shutdown commands to be issued if safety parameters are breached. Additionally, networked machinery provides usage metrics that helps optimize staff deployment. Operators are assigned to tasks based on current demand rather than predefined schedules. Self-guided vehicles reduce accident risks by automating material transport between areas. By improving both safety and workflow efficiency, the IIoT boosts overall workforce productivity.
Supporting Agile Supply Chain Management
Digitally transforming industrial operations through the IIoT also enables more agile supply chain management. Networked sensors track inventory levels and product movements in real-time across the supply chain. This end-to-end visibility of stock allows demand forecasts to continuously adjust replenishment based on current usage rates rather than estimates. Procurement and logistics are dynamically optimized to reduce overstocks and shortages. Distributed ledgers like blockchain facilitate transparent records of order fulfillment, shipments and invoicing across business partners. Streamlined data flows quicken response times and fulfillment accuracy. Overall, the IIoT enhances supply chain efficiency, resilience and customer satisfaction.
Overcoming Implementation Challenges
While the benefits of industrial internet of things implementations are compelling, manufacturing plants also face challenges to enable the necessary digital transformation. Upgrading legacy machinery with new sensor and networking capabilities requires significant capital budgets. Integrating disparate industrial systems from multiple vendors introduces interoperability complexities. Addressing cybersecurity vulnerabilities in perimeter defenses, authentication and authorization is also critical as industrial networks get connected to external cloud environments for analytics. Skill shortages in specialized roles like industrial IoT architects and data scientists limit the talent availability for IIoT projects as well. Finally, changing organizational culture and work processes is another hurdle as data-driven decision making replaces experiential judgment. Despite such hurdles, the payoffs of IIoT implementations continue incentivizing manufacturers to overcome barriers through prudent investment and planning.
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1.Source: Coherent Market Insights, Public sources, Desk research
2.We have leveraged AI tools to mine information and compile it
About Author - Ravina Pandya
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