How to Automate and Integrate IIoT Systems

As advances in technology make it more cost-effective to deploy Industrial Internet of Things (IIoT), industries will need to acquire a strategic approach to integrating new sensor data with pre-existing data environments.

Now more than ever, industries are seeking simple integrations with controls, automation, and data analytics visualization software to harness the power of IIoT and realize materialize operational and competitive benefits for their business. IIoT can unite people and systems on the plant floor with those at the enterprise level, enabling users to get the most value from their automated systems while reducing technological and economic limitations.

To ensure successful deployment of the IIoT, industrial organizations can benefit from embracing new network design infrastructures, including developing a reliable framework that supports collaborative work processes across functional lines, as well as between internal and external resources.

New Ways to Integrate IIoT Systems

Processes, digital devices, and business systems can support the implementation of the IIoT, from small companies new to IIoT's potential up to large industries that can benefit from adding new sensors into their present systems for internal and external business processes. From laying the foundations to help guide future technology investments to easing the integration of the current systems with new controls, automation, and data processing benefits, there are ways to help smooth the transition.

When looking at new systems for IIoT implementation, we recommend keeping the following seven factors top of mind.

Seven Considerations for Successful IIoT Implementations

1. Assess the Baseline

Look at assets, processes, data collection, analytics, and real-time visibility to assess the ability to predict and detect issues and opportunities. For example, which types of sensors, cameras and other instrumentation are available to make use of available data tracking potentialities?

2. Boost the Capabilities

Use machine learning and automation technologies to create an über-system that can accurately and consistently capture, analyze, and transmit data with visualized dashboards for operations management.

3. Integrate the Potential

Employing open integration and communications technologies can help connect data from varied sources on the way to extracting meaningful value for decision-making. This can include software that brings high fidelity data from disparate operational sources to people in all corners of a client's enterprise—wherever, whenever, and however it's needed.

4. Consolidate Data

Look to centralizing data in the cloud with new applications that connect multiple disparate systems, applying higher level analytics and leveraging expertise with the benefits of being physically remote from the operating site.

5. Make it Visual

Consider employing cloud-based applications that add value, such as advanced process control (APC) monitoring, condition-based monitoring (CBM), enterprise data historical databases, mobility solutions, and planning and scheduling tools. This new instrumentation can help facilitate real-time decision making plus allow long-term data tracking for precise adjustments.

6. Redefine Teamwork

With these new controls and automation tools, look to define how functional groups can work together and how to enable smart collaboration across the organization using IIoT advantages. This may include sharing data in operations, maintenance, system reliability, supply chain management, and other potential synergies.

7. Make Alliances with the Experts

Stay flexible with new updates and demographic changes using technology tools and collaborations with third-party experts that understand industrial automation, process data, and control-related issues across the enterprise. Traditional information technology (IT) providers may not offer that depth, and the potential for niche integration consultants is ripe for growth.

Potential Challenges and Hurdles

Integrating new technologies into existing environments can present unique challenges to overcome. While connecting legacy equipment and systems offers potential big benefits—it's an important step in the IoT initiatives at many industrial companies—the hurdles to implementation are nontrivial.

Having said that, many companies are making important strides in IIoT initiatives. How are they doing it?

One of the challenges they continue to face with legacy machines is the lack of connectivity built into legacy machines. Companies are now adding stand-alone sensors and cameras to existing environments and devices to monitor and collect data about performance and health in new ways, like attaching the sensors directly to the existing devices and connecting new gateways to securely collect and transmit the data, which is then analyzed and used to help boost various areas of the business while preventing failure and downtime.

One of the lingering questions is this: If legacy machines don’t have sensors and automation controls built into them today, how can they be attached in a cost-effective manner?

The answer would enable teams to begin measuring things like vibration, temperature, climate, dust in the air and other factors that are useful for quality environments where the machines are deployed. Cameras also can play a big role, enabling the monitoring ability of team members through a common platform to tap open a video and get a real-time sense for where a machine is and how the operation is functioning.

Platform Strategies

With the increased integration of global intelligent manufacturing, companies are turning to IIoT architecture as the core of their platform strategy to ease integration. Various companies are designing solutions as a three-layer architecture, offering neither an IIoT platform nor simply an industrial cloud platform, yet a fully connected system.

● Bottom Layer: this would include various hardware products with interconnectivity capacity, like gateways and more.
● Intermediate Layer: this would take care of edge point control.
● Upper Layer: this would comprise various applications, analytics, and services for decision-making abilities.

The system's layers works together. The reality is that IIoT only can be realized through intercommunication of these three layers that each refer to information, data, communications, and applications. Software platforms at the operating system level are needed to support and connect the three-layer architecture.

Conclusions and Next Steps

As more hardware devices go online, opportunities abound for embedded engineers to assist with the integration and novel use of controls, automation, and instrumentation across industries. Following the simple steps of assessing company assets and capabilities while reviewing potential ways to ease integration can benefit the whole enterprise.

Feel free to share your ideas in the comments section below. We look forward to hearing about your unique experiences and ideas for the integration of IIoT today.