Why Data is Important in Industry 4.0?

Post By: Harry Richardson On: 29-03-2024 - Industry 4.0 - Industry Trends - Manufacturing

Advanced Industry 4.0 technologies have created a marked change in business practice. Business intelligence now helps manufacturers achieve production excellence by collecting, analysing and managing the huge volumes of data generated by all aspects of the operation. This data supplies the Industry 4.0 technologies with continuous information, to create more data (Big Data) and keep growing. They leverage this data with Artificial Intelligence (AI) to boost automatic learning systems. This has expanded the Internet of Things (IoT) into the Industrial Internet of Things (IIoT) and the Internet of Systems (IoS).

Advent of Industry 4.0

In what we now call Industry 3.0, we started using computers to enhance existing processes. Connecting these computers into networked systems and discovering how to deal with large amounts of data led to the creation of intelligent machines. This means allowing your IIoT systems to make informed decisions on their own.

In Industry 4.0, we’re now creating entire manufacturing systems around the power of big data. 

Some manufacturers are still trying to get their heads around this and make the transition, but many others have already switched to data-driven manufacturing. To achieve this, some key steps are required, such as investing in advanced technology like 3D printing, augmented reality and robotics. You'll be using big data and analytics to reinvent your products, processes and services. Plus, you'll be leveraging enhanced system control and IoT networks to derive greater operational efficiencies.

Investing in Industry 4.0 technologies is a big decision. Adapting your existing manufacturing systems won’t be as effective as a complete re-evaluation of your production process. You’ll need to assess how to increase automation with cyber-physical systems and build in IoT core architecture to create and exchange data. It will need to be capable of managing the enormous volumes that big data represents. IIoT devices and sensors generate a stream of real-time data that allows constant and precise control of your whole manufacturing environment. A central management system must control and synchronise all elements of the production process in a time-critical manner.

Importance of Data in Industry 4.0

The central control system is the foundation of any advanced manufacturing operation. Time is its most critical factor, so the required precision should be provided by a time-series database. This can deliver two crucial services: minimising downtime and ensuring the efficient running of your production line. These may sound very similar, but they represent two very different aspects of the control structure. 

Reducing Downtime

Reducing downtime on the production line requires a system able to predict equipment failures and operational problems before they occur. This ability to predict failure is a function of big data analytics, which can assess a myriad of operational measurements in a nanosecond. It then determines what action is required to identify and eliminate potential problems so that you won’t risk any unscheduled downtime.

Maximising Efficiency

A control system can also maximise production line efficiency by fine-tuning the timing and sequence of events as they occur in the manufacturing process. Again, this means managing the vast amounts of continuously input sensory data, and responding in real time. All automated functions and cyber-physical systems can be precision-tuned to ensure the best possible efficiency.

A time-series database is capable of this kind of split-second precision monitoring. It can do this across many data sources, including sensors and other devices. It can also contextualise the various data according to their importance in the operation. This means it can prioritise between high and low precision data, and how long each type might need to be stored. The ideal time-series database will need to cope with extremely high data volume, while still maintaining the speed of its responses.

Big Data Use in Industrial Environments

Why Data Is Important In Undustry 4.0?

The value of all this information to modern manufacturing can be seen in various aspects of the industrial process. Centrally-controlled systems use big data analytics to classify it and determine how it can help to improve your business operations. Some key areas of automated decision-making include:  

Improving Operational Efficiency

Improving operational efficiency in warehouse processes by analysing data received from sensors and portable devices. They can detect human error, identify optimal production and assembly routes and carry out quality controls.  

Eliminating Bottlenecks

Eliminating bottlenecks by identifying potential factors affecting performance, so problem areas can be rectified.  

Predictive Maintenance

Analysing data from sensors helps identify breakdown patterns leading to potential machine failures. A central control system sends predictive maintenance alerts so that the equipment can react to problems before they happen. 

Predicting Consumer Demand

More accurately predicting consumer demand, by analysing internal activity such as customer preferences. Combining this with real-time external analysis such as current events and trends allows you to tailor your product portfolio to your customers’ needs.  

Improved Business Strategy

Big data is also important in industry because it can be applied to your business strategies too. You can establish and optimise systems directly involved in manufacturing, such as product lifecycle management, supplier relationship management and enterprise resource planning. You can also design your systems to leverage social media, be more environmentally responsible and improve security. 

Maximise Efficiency Using Data

The importance of data to today’s industry is that it’s not just historical. Big data analyses information from the past, present and future, offering a holistic picture of your business operations. This includes analysis of causalities as well as future projections, integrating supply chain management and enhancing customer satisfaction. You’ll be integrating previously isolated systems in your manufacturing processes and getting a complete visual of how everything works together. At the same time, you’ll be reducing your inventory and medium to long-term capital requirements.

Adopting Industry 4.0 technologies and big data management will help you maximise efficiency in your manufacturing processes and increase overall value. You’ll understand better how each system functions, both individually and in combination. Big data is the key strategy for any 21st-century manufacturer, before even considering such issues as supply chain, production floor layout and logistics. What data architecture you choose will be your central consideration to maintain optimum efficiency and maximise throughput.

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