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How to succeed at IIoT Implementations.

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Posted by Arthur Corallo - 12 November, 2019

In our last post, we discussed specific ways Industrial Internet of Things (IIoT) platforms can deliver business value and drive new levels of efficiency, productivity and performance. However, most organizations aren’t fully prepared for the challenges involved with implementing this technology.

Organizations frequently struggle to effectively integrate IIoT technologies with existing infrastructure and processes. Fully integrating machines, sensors, systems, processes and networks is a complex endeavor that can quickly get off track. According a Cisco report, only about 40 percent of such projects ever make it past the proof of concept stage.

Poor interoperability is a common issue. IIoT involves a complex interplay of many networking devices, connectivity technologies, applications and management platforms. It also requires the use of multiple protocols and data sources.

Acquiring Expertise

A lack of standardization in the marketplace contributes to interoperability problems. Amazon, IBM, Cisco, Microsoft, Oracle and dozens of other vendors have developed proprietary platforms and ecosystems. Integration is often possible, but it requires specific expertise with software development kits and application programming interfaces.

Few organizations have such expertise on staff. A lack of in-house skills was cited as the top barrier to IIoT deployment in a recent Vanson Bourne survey. Respondents cited the need for greater expertise in security (56 percent), data analysis (48 percent) and technical support (42 percent). Additionally, many said they lack the strategic vision to identify, develop, deploy and manage IIoT solutions that will deliver bottom-line benefits.

A lack of integration and development talent on staff doesn’t have to derail your IIoT initiatives, however. A trusted solutions provider with strong industry relationships can ease the process by providing expert guidance through all phases of a project, from component acquisition and front-end deployment to data acquisition and analytics.

RMM Solutions works closely with Tech Data to offer customers this type of holistic implementation. We understand how to aggregate components from multiple vendors and integrate them with existing infrastructure and processes in order to reduce costs while delivering rapid business benefits.

Ready to Go

Implementation is further streamlined with more than 30 market-ready and fully vetted solutions that comprise Tech Data’s Analytics and IoT Solution Catalog. Designed for specific use cases in manufacturing, operations, energy, healthcare, and transportation and logistics, these field-tested solutions lower your barriers to entry and speed time to production.

Through our relationship with Tech Data, RMM can deliver centralized monitoring, predictive maintenance and connected logistics that support specific use cases in industrial settings. For example, we can help you implement an industrial health monitoring solution that uses data from a combination of sensors and programmable logic controllers to monitor equipment and predict production cycle failures.

A predictive maintenance solution features pre-integrated data acquisition, analytics and reporting capabilities that can quickly provide manufacturers with insight into the health of their connected assets. By aggregating and analyzing real-time data from a variety of industrial sensors, this solution enables you to create customized predictive models that provide advanced warning of impending equipment failures.

The interconnectivity of machines, sensors, systems and networks is changing the way industries operate, creating the potential for process improvements and operational efficiency that drive growth and profitability. However, many organizations are finding that IIoT projects are more challenging than anticipated. Working with a solution provider with the right expertise and the right industry connections can simplify the process and improve time to market. Give us a call to learn more.

Topics: Industrial Internet of Things, IIoT


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