The Industrial Internet of Things, IIoT, is here to stay. Many heavy industry companies in fields such as engineering, mining, oil and 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.
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, channeling 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 or 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.
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 behavior 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 behaviors, 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 is 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 is 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.
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 defining an operational architecture, choosing an initial underlying system to provide state-of-the-art user interface and data platform and tackling small projects that prove the concept of key requirements.
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. 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.
- IIoT offers organisations a powerful framework for operational continuity.
- Adoption of analytics is said to be one of the greatest drivers of digital transformation.
- Predictive analytics is used for what-if type modelling.
- Prescriptive analytics describes what is needed to optimise asset and operations lifecycles.