Introduction

In today’s competitive manufacturing landscape, leveraging technology to gain a leg up is no longer optional. Among many technological advancements, real-time data stands out as a pivotal asset in driving operational excellence. 

In this blog post, we delve into various ways real-time data can be harnessed to bolster manufacturing processes, spotlighting our project Concrete Manufacturer Digitalization, as a testament to the transformative power of real-time data.


Use cases of real-time data in manufacturing

1. Quality Control & Compliance Monitoring

Real-time data plays a pivotal role in both Quality Control and Compliance Monitoring within manufacturing operations.

It enables the immediate identification and correction of quality issues, ensuring that the products meet the required standards. Concurrently, it facilitates real-time monitoring of compliance parameters to ensure adherence to industry regulations and standards. 

This integration reduces risks associated with sub-standard products and non-compliance, fostering excellence, and integrity in manufacturing operations

Use case example:

In pharmaceutical manufacturing, real-time data is utilized to monitor drug quality while ensuring compliance with health authority regulations.

2. Predictive Maintenance

Predictive maintenance is a proactive approach that utilizes real-time data to monitor the condition and performance of equipment to predict when maintenance will be required, thus preventing unexpected equipment failures and associated downtime​​.

Use case examples: 
  • Industries ranging from automotive manufacturing to consumer goods production employ predictive maintenance to prevent material waste and ensure on-time delivery of products.
  • High-speed train lines in Europe are transitioning to predictive maintenance models to monitor equipment on board trains and in stations, anticipating cost reductions and efficiency improvements​​.

3. Digital Twins

As discussed in a previous blog: How To Boost Operational Efficiency With a Digital Twin, Digital Twins are digital replicas of physical systems updated in real-time with data from the manufacturing process. 

Real-time data is the backbone of Digital Twins, enabling monitoring, control, and optimization of production performance in real-time.

4. Enhancing Production Potential

With real-time insights into production bottlenecks and operational inefficiencies, manufacturers can make informed decisions to improve productivity. 

Through monitoring machine utilization, measuring Key Performance Indicators (KPIs), identifying bottlenecks, and assessing deviations from production potential, real-time data facilitates better resource utilization and higher production rates.

Additionally, it enables the prompt meeting of market demand by effectively planning maintenance and machine downtime.

Use case example:

A case study highlighted a significant discrepancy in a company’s perception of machine utilization within the field of industrial manufacturing.

At Fastenal Manufacturing, production managers were under the impression that their machines were “always running,” yet the data revealed that the machines were active only 39% of the time.

5. Streamlined Data Access

Real-time data aggregation from diverse sources (such as sensors, cameras, RFID tags, PLCs, SCADA systems, MES systems, ERP systems, and IoT platforms) facilitates a holistic view of operations, enabling quicker, data-driven decision-making from anywhere, on any device, at any given time.

This reduces the time spent on data collection and analysis, fostering a culture of informed decision-making and freeing up employee time for more creative tasks.

6. Energy Management

Real-time data enables monitoring and control of energy consumption across manufacturing operations. Especially with the impending mandate of ESG reporting, this will become a key solution for all manufacturers to meet requirements.

By providing real-time data from machines and sensors, manufacturers (or other organizations) will be able to report energy consumption and improve their energy efficiency.

More about ESG in our blog: SDGs vs ESGs: Why Are They Important In the Digital Landscape

Use case example:

A case study of a food production system showed that the collection of real-time energy data led to optimized energy consumption and significant savings of approximately 163,000 kWh in the year 2017

7. Supply Chain Optimization and On-Time delivery

On-Time Delivery is influenced by various factors, including production cycle time, inventory management, supplier reliability, transportation logistics, and order processing efficiency.

Effective scheduling and production planning are essential for ensuring manufacturing operations align with customer demand and lead times.

Real-time visibility into the production floor, inventory levels, and order status is crucial for tracking progress and identifying potential delays.

Continuous monitoring and analysis of On-Time Delivery performance help identify areas for improvement and drive operational excellence.

8. Customization and Personalization

Real-time data supports the customization of production processes to meet specific customer requirements.

Even when the production has already started and the customer wants to change something, real-time data enables tracking of the order in the production process to assess the feasibility of changes.

9. Workforce Productivity and Safety

Through real-time monitoring of operational conditions and employee performance, manufacturers can create a safer and more productive work environment.

This continuous monitoring allows for the identification of underperforming or overperforming employees, aiding in performance management.

As a result, there’s a reduction in accident rates, an improvement in employee morale, and an increase in overall productivity levels.


Concrete Manufacturer Digitalization: A Case in Point

In a bid to drive innovation within the concrete manufacturing sector, we embarked on a project aimed at overhauling operational processes for one of the leading players in Slovenia. 

The core of this venture was the creation of a Digital Twin, alongside the integration of IoT solutions, to provide real-time data across some production stages.

The integration of diverse data sources and local data from the client into a single, unified system in real-time, was pivotal in achieving the project’s goals.

Benefits Realized

Enhanced Control: Instant access to critical data allowed for immediate adjustments based on various factors such as humidity, temperatures, and ingredient conditions, propelling a new level of control over production processes.

Reduced Downtimes: Continuous monitoring and instant data access were key in minimizing production downtimes, ensuring smooth operations.

Improved Quality Assurance: Automating the process of quality control ensured more accurate results and saved a significant amount of time, especially since it’s a lengthy procedure.

Efficiency & Optimization: The unification of data into a singular system facilitated an easy achievement of production capabilities, enabling optimized maintenance schedules and processes.

Data-Driven Decision Making: Empowering the manufacturer to make informed, accurate decisions, optimizing operational workflows, and boosting overall productivity.

Conclusion

Real-time data, when harnessed correctly, can significantly uplift manufacturing operations, as evidenced by our Concrete Manufacturer Digitalization project.

Discover more about how Digital Twins and Industry 4.0 solutions can be tailored to address specific manufacturing challenges by exploring our solutions: Industry 4.0 and Digital twins