Authored by: Ravi Gopinath at AVEVA explores why connectivity in complex industries will continue to expand
The Industrial Internet of Things (IIoT) is here to stay. Many heavy industry companies in fields such as engineering, mining, oil & gas, and manufacturing are accelerating their adoption of digital transformation journeys due to recent global events.
The barriers to adopting IIoT technology has also fallen dramatically in the past decade. Historical challenges to implementing IIoT solutions included expensive components to add network connectivity, difficulty aggregating data from disparate data streams, and lack of a centralised database or dashboard. Now businesses can have the opportunity to adapt and maintain operational excellence in volatile times through digital transformation. The current global crisis is accelerating cloud and the use of data in increasingly sophisticated ways to provide visibility and certainty into operations.
Smarter data-driven decisions
Adoption of analytics is said to be one of the greatest drivers of digital transformation, as businesses seek greater data-driven insights. Data acts as a source of truth that helps teams focus on the critical factors that determine business resilience. There has also been a fundamental shift in mindset. Businesses are acutely aware that they must become more resilient by using technology.
Companies are using IIoT to their advantage to securely connect, and collect data from diverse remote assets, channelling information to advanced operational applications, and closing the loop by feeding key business applications. This helps to enable optimisation, asset management, enhanced analytics, and modelling/simulation, thus providing and improving business efficiency.
This has been particularly true for the industrial sector, for instance, where IIoT has had a significant impact in five key areas including:
- Real-time operational information is used to understand what is happening in real-time and enables the condition management of asset and operations lifecycles. For example, a dashboard displaying vibration frequency of a rotating asset such as a turbine during operation provides real-time understanding of the asset operational behaviour and state.
- Historical operational information helps you to understand what has happened in the past to create intelligence around operational behaviour of assets. Through operational trends, display of KPIs and dashboards, you can create abstracted views of operational states. For example, a graph may be displayed on a dashboard showing the turbine’s past vibration frequency during operation. This can be compared to the real-time vibration frequency, creating intelligence on the asset’s long-term operational trends.
- Predictive analytics is used for what-if type modelling. Integrating up real-time and historical data enables your team to assess potential outcomes of operational states and behaviours, even accounting for tertiary variables. Deterministic or non-deterministic models can then be applied for open-loop simulation and predictive analytics. For example, you can now estimate how long a piece of equipment can run before it requires inspection or is predicted to fail.
- Prescriptive analytics describes what’s needed to optimise asset and operations lifecycles. Scenario-based guidance is created and delivered through learning elements and closed-loop algorithms to enable your team to calibrate planning and scheduling across the entire enterprise value chain. For example, using a unified supply chain model, scenario-based calculations can be used to optimise maintenance schedules and performance, minimising impact to your operations.
- Enhanced safety: A combination of connected IoT devices, augmented and virtual reality technology provide real-time operating procedures and key messages to operations personnel, reducing human error for performing specific tasks. Operators are also supplied with information about the location of existing hazards by superimposing them over the operator’s location.
IoT is evolving
Industrial organisations will continue to evolve how they handle and present data at the plant level, and those who make sensible choices to ensure flexibility and expansibility will unlock unlimited potential in existing and expanding data. If your organisation does not have a strategy in place for Digital Transformation, the all-important first step is to execute a pilot project and key steps include:
- Define an operational architecture (OA) – a key to success is think big and start small.
- Choose an initial underlying system to provide state-of-the-art user interface and data platform – What you choose today will undoubtedly evolve over time: in this case starting now and changing later is infinitely better than waiting for the next generation.
- Tackle small projects that prove the concept of key requirements — user interface, sharing plant and business data across the enterprise — real-world use cases. Keep in mind that it’s still early in the fourth industrial revolution and things will change faster than we can cope with. Consumer electronics will continue to drive and accelerate the pace of change in human machine interaction, and vendors will be making choices about which ones they’ll embrace or leave behind. Industrial organisations must work with their vendors to ensure they get technology to help them make the transitions needed as technology and the workforce continues to change.
Building resilience from within
Covid-19 has significantly curtailed global and local mobility, leaving the global economy to face the prospect of a sharp recession. This will put businesses under enormous strain in 2020. To help navigate the challenge, digital transformation can provide the data-driven insights needed to adapt and overcome.
IIoT offers organisations a powerful framework for operational continuity. Enabling users of all levels and experience to access the critical information they need to do their jobs successfully. IIoT devices also empower workforces with the digital services they need, such as equipment utilisation, condition management and more. IIoT offers innovative ways to monitor and manage objects in the physical world, particularly as huge streams of data offer companies’ better avenues for decision making. The results? More uptime, more efficiency and a more engaged and empowered workforce due to the access they have to a unified stream of insightful intelligence, at a time when it’s never been more important to contextualise data and information that drive actionable insights.
Digital transformation is enabling companies to enhance their capabilities, increase their reach and returns across their asset and operations value chains. The use of IIoT through real-time online monitoring and analytics has had a profound impact by improving response times to potential issues and minimising possible damage to the environment, which has ultimately resulted in the avoidance of costly unscheduled shutdowns, while improving profits. IIoT has made a vast difference to the efficiency of the industry and simply put, it is here to stay for the foreseeable future.
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