Industry 4.0 has brought digitisation and connectivity to the heart of the production process, transforming modern factories' operations. Based on physical controls and manual processes, traditional production methods are no longer sufficient to meet the increased demands for efficiency, quality, and flexibility. Today, the collection and analysis of data from machines is the key to:

✔ Improving production efficiency, with more precise control of each production stage.
✔ Cost reduction, by avoiding unnecessary downtime and failures.
✔Optimisation of quality, with real-time control and prevention of deviations.

Access to accurate, reliable, and real-time data enables industries to make informed decisions, prevent problems before they cost time and money, and ensure more efficient and sustainable production.

But why is data so important, and how can it fundamentally change the way a factory operates? In the following article, we discuss their importance, the benefits they offer and how they can be properly utilised by industries.

🔹 What is Data Collection and Analysis from Machines?

Data collection from machines refers to the recording and storage of information related to the operation of the machine in the production process. Then, the capture and analysis of this data includes indicators, graphs, reports, etc., on uptime, lost time, energy consumption, machine performance, machine health, quality losses, and other critical variables. By continuously monitoring and analyzing this information, companies gain full visibility of production, can identify efficiencies and problem areas, and make timely, informed decisions.

🔍 How is the data collected and analysed?

The main technologies used for data collection and analysis include:

✔ IoT (Internet of Things) sensors: Smart sensors are installed in machinery and equipment, recording critical variables in real time, such as temperature, vibration, pressure, energy consumption, production speed, etc. This data is sent to centralized systems for analysis and decision-making.

✔ SCADA & MES: SCADA (Supervisory Control and Data Acquisition) and MES (Manufacturing Execution Systems) systems collect data from different points of production, allowing continuous monitoring, automated control, and performance analysis.

✔ Cloud & Edge Computing: Large volumes of data are managed through Cloud Computing, allowing easier storage, analysis, and real-time access. At the same time, Edge Computing enables fast data processing directly on the production site, reducing the need to send all data to the cloud.

✔ Machine Learning & AI: Artificial intelligence and machine learning algorithms can identify patterns and trends in the data, enabling the prediction of potential failures, optimizing the production process and reducing waste.

🔹 The Benefits of Data Collection and Analysis in Industry

The collection and analysis of data from machines is based on advanced technologies that allow continuous monitoring and optimization of the production process. Businesses leverage various tools and systems to capture, manage, and analyze critical information in real-time.

Some indicative benefits are presented below:

Production Optimization & Efficiency Increase (OEE - Overall Equipment Effectiveness)

Using production data, companies can monitor and improve their OEE (Overall Equipment Effectiveness), which measures:

✔ Availability

• Calculates the actual running time of the machines in relation to the scheduled time.

• It is affected by unplanned outages, maintenance times and start-up delays.

• Aim: to reduce unplanned downtime and optimise uptime.

✔ Performance

• It measures how close the actual production is to the maximum potential of the machines.

• It is affected by factors such as low operating speeds and frequent micro-interruptions.

• Aim: Increase production rate without affecting quality.

✔ Quality

• It assesses the percentage of products that meet quality standards without defects.

• It is affected by the quality of raw materials, mechanical malfunctions, and human error.

• Aim: to reduce defective products and rejects

Based on the above that the business user can not only identify losses during the production process, but also what causes them and how to act in time.

Failure Prediction & Predictive Maintenance

Traditional maintenance is based on either planned operations or reactions after a failure. By collecting and analyzing data, businesses can:

✔Detect anomalies before they cause serious problems.
✔Intervene only when needed on the problematic parts, without unnecessary replacements and wear and tear on adjacent production parts.
✔Reduce unplanned downtime and increase the life of machinery.

Improve Product Quality & Reduce Discards

With real-time monitoring of critical production parameters (such as temperature, pressure, and humidity), companies can:

✔ Identify deviations and intervene immediately.
✔ Reduce raw material wastage.
✔ Ensure consistent quality in the finished products.

🔹 How to Get Started with Data Collection and Analysis

Moving to a data-driven environment can seem challenging, but with the right approach, any industry can leverage data to its advantage. If your business hasn't yet adopted a data collection and analysis strategy, you can follow these basic steps:

1. Define your goals: Identify the critical parts of the production process that need improvement.

2. Select the appropriate technologies: Look for solutions such as IoT sensors, Cloud Computing, Edge Computing and AI Analytics that will allow you to capture and analyze your production data.

3. Use specialized platforms: Incorporate solutions that provide combined insights into your production and allow you to make informed decisions instantly. Get to know the SEEMS platform.

4. Get started with pilot projects: While proper planning is a key pillar of successful data collection and analysis, piloting on a specific process/machine before overall adoption can be beneficial. This allows companies to evaluate the results, identify any challenges, and adjust their strategy before full integration.

📌 Conclusion

Collecting and analysing data from machines is not just a new trend - it is an essential pillar for the industry of the future. Digitizing production through data collection is not just a technological investment, but a strategic move that leads to greater efficiency, lower costs, and competitive advantage.

📊 The future of the industry belongs to data!

📢 Do you want to harness the power of data to improve your production?🚀

📩 Contact SEEMS PC and find out how we can help you turn your data into a real competitive advantage!