Leverage data to generate value

Originally published in issue of CTS March 2023
As organisations generate greater volumes of data from their operations it’s imperative that data is leveraged to generate more value.

Data can be leveraged to produce value and insight that helps operations and asset integrity managers ‘do more, better’, according to Vinod Ninan, product director at ABB Process Automation.

In a manufacturing environment, most of these systems are running in multiple networks / units. Even the ownership of this data differs varies from plant to plant and even in roles.

“In this context, you would need a centralised environment where you can integrate, validate, contextualise the cleaned data and make it accessible centrally – this is where the cloud presents great potential and can yield benefits.”

Consolidating data and deploying via the cloud opens up a plethora of solutions and applications possibilities, including business, asset and sustainability solutions, planning and logistics solutions, operation solutions, supply chain solutions, and advanced supervisory solutions. From an industrial point of view, it also empowers predictive, diagnostics and prescriptive analytics applications. This means that previously siloed information is now available across the entire enterprise.

Concerns about security are of course in front of mind when you increase the number of users across a system, more devices connected to the network, and more and more information being stored on the cloud.

There are also a number of data and integration challenges when considering the deployment of cloud solutions including proprietary controls, multiple data formats, lack of contextual information, quality issues, designed for operations, different across industrial verticals, directly coupled to applications and isolated networks.

“There are some powerful risk mitigation strategies however, for example, deploying edge solutions, whether there is ‘lite edge’, for secured communication from edge to cloud or ‘heavy edge’ for deploying application at the source of data and for enabling distributed computing, faster response time and cost optimisation,” Ninan adds.

There are a number of clear benefits to this approach including an SAAS based business model that enables customers to focus on operational efficiency; building of an integrated asset information model using operations, process control, assets and design systems using a contextulisation engine.

Empowering user personas via solution positioning with strong focus on controls or process engineer, manufacturing system engineer, data engineer, integration engineer or system architect.

Enabling hybrid deployment of containerised solutions thereby reducing data round trips and enabling faster responses; cost reduction through distribution of data processing b/w edge & cloud by filtering and aggregating high-volume data at the edge.

Operational resilience by making site operation resilient to unreliable network by enabling hosting of managed application at the edge and synchronising with the cloud when the connectivity returns.

“The good news is that huge amounts of value can be generated by integrating information from assets (IT systems), sensors (OT Systems) and design (Engineering) systems,” Ninan says.

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