Data as The Core of Industry 4.0
It’s been a decade since the beginning of an era, the era of Industry 4.0: the integration of traditional manufacturing practices with the latest smart technology (AI, the IoT, automation, virtual reality, etc). Synonymous with smart manufacturing, Industry 4.0 is the realization of the digital transformation in the production field, delivering enhanced productivity, quality, flexibility, and agility. According to Industry Today, the big difference between Industry 4.0 versus Industry 3.0 is that while in the former computers were introduced to support existing processes, the latter seeks to reinvent the entire process around the power of data. So, how does data play an important role in Industry 4.0?
The Role of Data in Industry 4.0
In general business operations, the analysis of data provides valuable information on key elements such as markets or business directions, identifying which ones will potentially generate the highest profits. It is vital for making strategic decisions such as expansion and development plans or financial analysis. However, data also plays an important role in connected, technology-driven manufacturing processes.
In the traditional practices, manufacturing technology is divided into two functions: operational technology (OT) and information technology (IT). OT focuses on the systems, softwares, and sensors that monitor and control manufacturing processes, while IT is in charge of data analytics. Industry 4.0 is where processes and analytics are interdependent and the two functions are merged into one whole function.
Data lies at the heart of this integration, a fundamental instrument that makes it possible for businesses to reinvent their manufacturing process. Connected devices collect a massive volume of data that can inform performance, maintenance, and other issues, and then analyze that data to identify patterns, anomalies , and insights that would be impossible for a human to do in a reasonable timeframe. That is why Industry 4.0 offers the opportunity for companies to optimize their operations quickly and efficiently by knowing what needs their attention and mitigating risks. In addition, data can also be used in predictive, forward-looking ways to boost not only production efficiency and improvement, but also customer services and product development.
Examples of Data Utilization
Data can be analyzed and translated into various applications: automation, real-time remote control, downtime prevention, predictive maintenance, etc. Below are some examples of how data can be utilized.
1. Improving production processes
Data collected by sensors and other devices can be used by companies to improve operational efficiency by detecting human errors, performing quality controls, and showing optimal production or assembly routes.
2. Optimizing logistics and supply chains
A supply chain that is connected to a system and real-time data can adjust and accommodate when new information is presented. For instance, if a shipment is delayed due to the weather, the system can proactively adjust to that situation and modify manufacturing priorities.
3. Eliminating problems
Big Data can help companies identify variables that can affect performance, at no extra cost, guiding them in identifying the problem, fixing it, and finding ways to avoid it in the future.
4. Predictive demand
More accurate and meaningful predictions can be made through internal analysis (customer experience, preference, and complaints) and external analysis (trends and external events) of historical data. This allows the company to modify and optimise its business actions and operations.
5. Predictive maintenance
Data fed sensors can identify possible failures in the operation of machinery before it becomes a breakdown, by identifying breakdowns in patterns. The system then sends an alert to the equipment so that it can react in time.
Taking those into account, as data is the key element of Industry 4.0, data centers and cloud computing are becoming critical factors that enable companies to reinvent their production processes and realize smart manufacturing. To be able to store and process large volumes of data, companies require reliable infrastructure which are specifically designed for such tasks. Thus, since Industry 4.0 is inevitable, it’s essential for companies to start by choosing a reliable data center and cloud services provider which can assist them in achieving their goals.