The impact of technology evolution encompasses advances in sensor technologies, connectivity, analytics and cloud environments that will expand the impact of data on enterprise performance management and pose challenges for system integrations for most companies.
As industries are transitioning from analog to digitalized PLCs and SCADA, they would have to leverage sensor-based data to optimize control and design their assets and processes – both in real time and over time for faster decision making as well as embedding software in traditional industrial equipment.
Developing and deploying these systems securely and reliably represents one of the biggest challenges.
Going far beyond the current definition of networks, the most complicated and powerful network yet is now being built. In it, devices embedded in power lines, waterlines, assembly-lines, household appliances, industrial equipment, and vehicles will increasingly communicate with one another without the need for any human involvement.
The reach of these integration capabilities will go far beyond infrastructure and manufacturing. Today, for example, clinicians diagnose health conditions through a lengthy assessment. But simply matching historical pathological patterns, lifestyle patterns and matching those to live diagnostics collections systems provides for a more accurate diagnostic approach to serious ailments or early-warning signal. To make the most of such opportunities, health-care companies must figure out how to integrate systems far beyond the hospital. Much like in-memory big data analyses, this presents a problem of data collection closer to the source of the data.
You may wonder collecting and transmitting data from several industrial machines and devices is not a new concept. Since the early 80s, data from industrial assets has been captured, stored, monitored and analysed to help improve key business impacts. In this era of digitization, as the industrial sensors and devices create hybrid data environments, systems integration will propagate more data from more locations, in more formats and from more systems than ever before. Data management and governance challenges that have pervaded operations for decades will now become a pressing reality. Strategies to manage the volume and variety of data, would need to be administered now to harness the opportunity IoT and BigData promises.
Despite of the above stated challenges, some strategies incorporated in core operations can help increase the odds to success:
- Multiple Protocols
As the number of sensors and devices grow, increase in the number of data acquisition ‘protocols’ are creating a greater need for new ‘interfaces’ for device networking and integration within the existing data ecosystems.
- Data Variety
As devices and sensors are deployed to fill the existing information gaps and operationalize assets outside the traditional enterprise boundaries, centralizing data management systems must be able to integrate disparate data types in order to create a unified view of operations and align them with the business objectives.
- New Data Silos
Systems built with a purpose produce data silos that create barriers to using data for multiple purposes, by multiple stakeholders. Without foresight connected devices solutions presents the new silo – undermining the intent to construct architectures that incorporate connected devices to build broader, interactive data ecosystems.
As discussed above, for more than 30 years industries across the globe have been leveraging sensor-based data to gain visibilities into operations, support continuous improvement as well as optimize overall enterprise performance. As advances in the technology make it cost-effective to deploy connected solutions, industries would need to develop a strategic approach for integrating sensor data with pre-existing data environments. These advancements would traverse towards creating a seamless, extensible data ecosystem with the need for cooperation between multiple vendors, partners and system integrators.