The Industrial Internet-of-Things is here to stay. Recent global events have prompted many heavy industry companies to accelerate their digital transformation efforts.

Over the past decade, barriers to IIoT technology acceptance have fallen drastically. It was difficult to implement IIoT solutions. It was difficult to implement IIoT solutions because of the high cost of components that improve network connectivity and the difficulty in aggregating data from multiple streams. There was also a lack of a central dashboard/database.

Through digital transformation , businesses have the ability to adapt and keep their operations running smoothly in turbulent times. Global crisis: Data usage has become more sophisticated, and the cloud is expanding. This gives you greater control and visibility into your operations.

Smarter data-driven decisions

analytics adoption is a key driver for digital transform as companies look for more data-driven insight. Data can be a source for truth. This allows teams and individuals to focus on the factors that will impact the company’s resilience. This mindset shift is evident. Businesses can be more resilient through technology.

Companies can benefit from remote assets using IIoT. They can securely link and collect data, and channel it into advanced operational apps. They complete the loop by feeding business applications. This helps to enable optimization, asset management, enhanced analytics, and modelling/simulation, thereby providing and improving business efficiency.

This is especially true in the industrial sector, where IIoT has had an important impact on five key areas.

This real-time operational data is used to analyse what’s happening and allows for asset lifecycle management as well as condition management. A dashboard that shows the frequency of an operating turbine’s vibration can provide real-time information about its operational behavior.

Analyzing past operational data can help identify patterns in asset operations. Dashboards and Key Performance Indicators (KPIs) can be used to create abstract views of an operational state.

A graph showing the turbine’s vibration frequency in operation can be displayed on a dashboard. This graph can be compared with the current vibration frequency to gain insight into asset’s long-term operational trends.

Predictive Analytics is used to determine what-if scenarios. You can use historical and current data together to evaluate the potential outcomes of operational state or behavior. Tertiary variables may also be taken into account. Both predictive analytics and open loop simulations can be done with either deterministic or undeterministic models. It is possible to determine the maximum time that an equipment component can run before it is subject to inspection or declared unsafe.

Prescriptive analytics identifies key factors that will increase asset and operation lives. Closed loop algorithms and learning elements provide scenario-based guidance that will help your team plan and schedule across all enterprise value chain value chains.

Scenario-based calculations can be used, for example, to optimize maintenance programs. This will have a positive impact on your business.

Combining connected IoT devices with augmented and VR technologies can increase safety. Operators will be able to receive key messages in real-time and perform certain tasks more accurately. Operators will also be able to receive information about hazards located at their location.

IoT is rapidly growing

The industrial organizations will continue to improve how they present data at plant level. Smart decisions that allow flexibility and extensibility in data presentation will unlock the unlimited potential of existing and new data.

Your first step in implementing a digital transformation strategy for your company is the pilot project. These are the most important actions.

Create an operating environment (OA). is your key to success. Think big, start small.

Choose a state of the art user interface and data platform. Your choices today will evolve over time. It’s better to make changes today than wait for the next generation.

You can undertake small projects to demonstrate core requirements such as user interfaces, sharing tools, enterprise data between enterprises, and enterprise data. These things will change during the fourth industrial revolution.

The human-machine interface will be influenced by consumer electronics. Vendors will have to decide which technologies to adopt and which ones they should abandon.

To ensure the correct technology, industrial organizations need to work closely with vendors. This will allow them to adapt as technology changes.

Build resilience within

Covid-19 has severely limited global freedom and local liberty, putting the global economy at serious risk of collapse. In 2020, this will place businesses under severe pressure. Digital transformation is a great way to help. You can adapt and win with data-driven insights.

IIoT provides organizations with a solid foundation for operational continuity. Access to the information required to perform their job well is available to all skill levels. Digital services like equipment utilization or condition management can be accessed via the IIoT device.

IIoT allows objects to be monitored and managed in real-world settings. Large streams of data give companies more options for making decisions.

What are the results? What are the results? What are the results? This is where contextualization and data that provide actionable insights are crucial.

Digital Transformation enables companies to increase their capabilities, reach more people and increase their yields throughout all asset and operation value chains. Unscheduled shutdowns can be avoided by using IIoT via real-time online monitoring. It also reduces the risk of environmental damage.

The IIoT has had an impact on efficiency and will continue to be an important part of our lives for many more years.

About the Author

Santiago Picco

Partner @ 4i Platform - Data Driven Innovation Electronic Engineering specified in control automation. Master in Stategic Management of Techology. Data scientist. Industry 4.0. IIoT and Digital transformation.

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