Introducing Industrial IoT to Manufacturing - Challenges and Benefits

The march toward widespread adoption of the Internet of Things, or IoT, is on. Awareness and interest are increasing across markets, with manufacturing and robotics at the center of many industrial IoT conversations.

This is not a new phenomenon. Rather, it began over a century ago with roots in connecting sensors, equipment, and machinery. For example, Nikola Tesla had the idea of ubiquitous connectivity with his “world wireless system” in the early 1900s. A century later, Tesla’s vision for a connected — albeit often virtual — world has come to fruition with the Internet and Web.

As businesses and consumers come to expect the benefits of everyday connectivity, opportunities abound. Everything from kitchen appliances to home security or energy monitoring systems is delivering information in real time (or close to it) through the Internet.

But the underlying technologies of IoT are transferrable to business and industry solutions as well. Beyond commercial security, authentication, or HVAC systems, industrial IoT is being applied to vehicles, industrial automation, and even planning and scheduling systems.

The market for IoT and big data will experience a compound annual growth rate of 13.6%, from $24.46 billion last year to $46.19 billion by 2021, predicts RnRMarketResearch.com, and the robotics market is also benefiting from new investment.

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Business Takeaways:

Like robotics, the industrial Internet of Things is evolving faster than consumer-related applications, particularly in the manufacturing and supply chain markets.
User organizations need to understand which systems they want to connect, the level of security needed, and how they will analyze and act upon all the data generated.
Mobile sensors, cloud computing, and new applications are helping industrial IoT become essential to automated business.

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Industrial IoT challenges

Many manufacturers have used connected automation systems for decades. Most commonly, applications are seen in programmable logic controllers (PLCs), conditioning monitoring, and similar systems for maintaining efficiency.

As connected production and control applications become more widespread, many organizations must work around legacy systems. Such systems are not designed with wireless networks or Internet Protocol integration in mind, nor do they use multi-layer security protocols. These siloed systems present security, mobility, and adaptability issues.

Attributes of connected systems for manufacturing

As mobile sensors, robots and drones offer anywhere, anytime capabilities. In addition, connectivity to the cloud enables enterprises to aggregate, analyze, and act upon big data.

On the other hand, another hurdle for industrial IoT adoption is the need for robust data management, especially since inputs include both unstructured data (such as text) and the typical structured data found in relationship databases, data warehouses, and customer relationship management systems.

Also important are integration and analytics capabilities — the former to enable communication throughout networks, and the latter to aid in planning and prediction.

Increasingly powerful analytics and reporting applications can offer deep insights, such as forecasts of part and process status or consumer demand. These insights can establish benchmarks that automatically trigger action, such as predictive maintenance.

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More on Manufacturing, Robotics, and IIoT:

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Industrial IoT becomes a ‘must have’

IIoT is continuing to expand from manufacturing and smart homes to retail, food packaging, healthcare, and other use cases. For today’s manufacturers, industrial IoT is fast becoming a “must have” on production lines for reasons of efficacy and risk mitigation.

Monitoring sensors must integrate with production-line equipment, including robots. Data flows and monitoring/reporting modules can provide critical path information, trigger response protocols, and affect other activities being tracked on various industrial networks.

Industrial IoT can increase visibility into the conditions of robots in a factory, farm, warehouse, or hospital. Information about components and equipment can continually monitored to maximize productivity and to reduce line downtime.