What is big data?

Big data refers to extremely large, complex data sets that are too massive for traditional computer systems to handle. Today, advanced technology such as machine learning is capable of processing and analyzing big data sets to reveal trends and patterns. This has the potential for revolutionizing manufacturing data analytics, helping plants discover important insights that they can apply toward optimizing efficiency, cutting costs, and boosting revenue.

Use cases for big data in manufacturing

There are many possible applications for big data analytics within manufacturing. We review some examples below.

Improving manufacturing yield

There are numerous factors that might impact manufacturing yield at various stages of the production process. Big data can locate patterns, pointing to potential areas for continuous improvement.

Supply chain management

Big data can help maintain the supply chain by understanding the distribution of products and where they are needed. This can help optimize supply chains to better coordinate suppliers, prevent stockpiling, and reduce risk.

Predictive monitoring

Tracking and analyzing data from throughout an entire plant can help identify anomalies and catch unexpected issues early on so that engineers can resolve them before they become larger, costly problems.

Predictive maintenance

Machine learning tools can track plant data to predict wear and tear on equipment and send alerts when a machine part requires maintenance or repair. This can be used to streamline the maintenance schedules and improve uptime.

Production forecasting

AI tools can analyze operations, business, and supplier data in order to anticipate future demand. This allows plants to optimize production and better prepare for the future.

Risk evaluation

Big data can calculate and foresee risks involved in manufacturing, helping plants take preventive measures to reduce losses.

How does big data in manufacturing make process plants more productive?

There are countless possible applications for big data in process manufacturing. Nearly every system and process in place in a plant can benefit from making smarter, more strategic data-based decisions. With machine learning and artificial intelligence, big data sets that once seemed impossibly unwieldy can now be managed and crunched.

 

It is undeniable that there are valuable, actionable insights – needles to be found in the big data haystack. The right technology can reveal these insights, giving plants the information they need to increase operational efficiency, boost production, reduce loss, and ultimately improve performance.