Unlock manufacturing excellence with big data. Learn how it drives efficiency, innovation, and competitiveness in today’s complex production processes.
What is big data?
Over the previous decades, manufacturers were seen to utilize Six Sigma and Lean initiatives. The objective was to fuel efficiency, improve quality, and boost productivity. With the advent of Industry 4.0, companies have new technology generating huge amounts of data. This is referred to as the ‘big data’. And, it has become an indispensable asset in manufacturing. It helps companies to reduce costs, enhance efficiency, and continuously innovate.
With production processes becoming increasingly interdependent and complex, collecting, analyzing, and applying vast volumes of information is increasingly vital. This enables businesses to stay competitive in the global manufacturing landscape. In this blog, we’ll examine the role of data within manufacturing and explore its collection, analysis, and application to different operational aspects, along with possible resulting improvements.
Big data in the manufacturing industry
It refers to the large volumes of structured and unstructured information generated during production processes. This includes structured information from IIoT sensors, production processes, supply chains, and customer interactions. These allow manufacturers to optimize and innovate through data analytics for informed decision-making.
How manufacturers collect big data
Data collection in manufacturing is accomplished using various advanced technologies. Let’s explore a few.
Industrial Internet of Things (IIoT)
By collecting information regarding equipment performance, production output, and environmental conditions in real-time, IIoT sensors play a pivotal role. They generate continuous streams of information that allow for precise monitoring and control over manufacturing. Such use of IIoT sensors is done by capabilities such as OEEfficienci that is connected to a cloud-based platform – OmniConnect™. By collecting and integrating data from different batch processes and machines, OEEfficienci offers to identify stoppages and issues for enhanced overall equipment efficiency, optimizing key asset management.
Manufacturing execution systems (MESs)
They play an integral part in production by recording every step from start to finish. They capture information on production processes, quality performance, and other metrics.
Enterprise resource planning (ERP) software
It integrates data from multiple departments across the organization on materials, production schedules, and customer orders.
The role of analytics in manufacturing
Manufacturing is a big industry, and the amount of data available is typically measured in terms of terabyte. Trying to understand the data is similar to drinking from a firehose. This is what makes analytics the central element of any organization’s capability, to make the most of the information that lies within these big data sets.
This sector is seeing the emergence of technology, opening up new avenues for production optimization. Three of the most well-known are:
Cloud platforms
The cloud offers a scalable, secure storage system that allows businesses to save, retrieve, and analyze large amounts of data without the expense of servers on-premises.
Advanced analytics tools
They include statistical analysis, forecasting, and predictive models that enable firms to collect and perform sophisticated analyses of historical data collected from the factory floor to increase production processes.
Artificial Intelligence (AI)
AI or machine learning systems employ advanced analytics to identify patterns or relationships, as well as anomalies within vast databases. Furthermore, AI is capable of processing non-structured information, bettering user experience over the course of time. This allows for self-assured decisions based on real time information.
Applications in manufacturing
It has quickly become an essential aspect of manufacturing to drive significant advances and improvements across several processes and products. Noteworthy examples of data use in manufacturing include:
1. Predictive maintenance:
Data gathered through IIoT sensors allow for a proactive approach to maintenance. This enables timely dealt equipment failures, thus reducing downtime and increasing machinery lifespan.
2. Quality control
Manufacturing data helps companies effectively monitor product quality. Businesses are able to reduce waste while conducting early identification of defects. This enables businesses to exceed quality standards, ensuring products of superior quality.
3. Supply chain optimization
It allows for increasingly optimized supply chains. This is achieved by assessing inventory levels, supplier performance, and transportation logistics. Effective management, reduced costs and faster delivery times are its results.
4. Product development and innovation:
New offerings to meet customers’ requirements are developed by conducting studies. These studies inform product innovation efforts while assuring cost-efficiency for companies.
5. Energy management
Data on energy consumption patterns is analyzed to optimize energy use. This reduces costs and minimizes environmental impact.
What’s next?
The future is now for big data analytics in manufacturing. AI, machine learning, and IoT have driven significant advancements, causing it to evolve greatly. As these technologies become further embedded into the manufacturing processes, we see more advancement in the gathering of big data and its analysis.
AI and predictive analytics further enhance real-time decision-making. It is only a matter of time before the use of autonomous manufacturing systems that self-optimize with minimal human intervention will become prevalent. This will result in peak operational efficiency. Moreover, edge computing plays a significant role in shaping the future of big data in manufacturing. By processing data closer to the source, edge computing reduces latency and enables faster decision-making. This is particularly useful in settings where critical real-time data analysis is occurring.
As the manufacturing industry continues to evolve, the role of big data analytics will become increasingly important. Companies that effectively harness the power of big data will gain a competitive edge, allowing them to innovate and meet the demands of a rapidly changing market.
To explore how your company can be at the forefront of this evolving technological landscape, talk to our experts and learn more.
