Industrial companies are looking towards AI to improve various aspects of their plant operations, such as: 

• Reduce downtime 
• Schedule maintenance 
• Improve product quality  

However, achieving these operational impacts from AI is challenging.  

Methods to Integrate Big Data in Plant Operations 

Organizing the Big Data 

Companies will have to engineer their big data to include knowledge of various operations such as mass balance or thermodynamic relationships.  

Formation of Cross-functional Data-science Teams 

They will also need to form cross-functional data science teams that include employees who are capable of bridging the gap between machine learning approaches and process knowledge.  

A true transformation can be achieved once these elements are combined with an agile way of working that advocates iterative improvement and a bias to implement findings. 

This article was contributed by our expert Manoj K Jha
 

Frequently Asked Questions Answered by Manoj K Jha

1. How can industrial companies leverage big data to optimize their supply chain management and reduce costs?

Overall, Big data has a transformative impact on Supply Chain Management by providing organizations with the ability to analyze vast and diverse datasets to gain valuable insights.  

The stages of Big Data in Supply Chain Management include: 

• Planning 
• Provisioning 
• Performance 
• Delivery 
• Inverse logistics 

Through Big Data analytics, organizations can improve supplier management, optimize inventory levels, enhance supply chain visibility, improve the customer experience, and proactively manage risks.  

By leveraging the power of Big Data, businesses can make data-driven decisions, improve operational efficiency, reduce costs, and ultimately gain a competitive advantage in the market.