Advanced analytics in manufacturing
What is advanced analytics?
Advanced analytics is a catch-all phrase for the newest tools and methods for extracting more meaning from big data. It includes a number of types of analytics, like predictive analytics and manufacturing analytics, and it’s used by companies in every industry and vertical to improve their understanding of everything to do with their business.
Advanced analytics draws on automation and artificial intelligence to mine data for patterns and insights. Advanced analytics can include machine learning (ML); data modeling; neural networks; data visualization; forecasting; semantic analysis; complex event processing; and more. These tools combine data from multiple sources to produce predictions and insights into changing business conditions, market demands, and the plant itself.
Process plants have been slow to apply advanced analytics, largely because their datasets are so large and complicated, but that’s exactly why process manufacturing plants stand to gain so much from the newest wave of analytics. The best-advanced analytics tools are powerful enough to cope with complex plant data, but intuitive enough for non-data science experts to use independently. Finally, the process industry can benefit from accurate, real-time insights into opportunities, risks, trends, and changing demand in their vertical.
How can advanced analytics help process manufacturers?
Advanced analytics effectively provides visibility into every aspect of the plant, its equipment, and processes; the target market and customer demands; and broader economic conditions. With the help of advanced analytics, process plants can:
Improve business strategy by:
- Driving innovation
- Raising the customer experience
- Monitoring market trends and fluctuations
- Modeling risks and opportunities
- Predicting customer demands and concerns
- Gaining insight into supply chain inefficiencies
- Future-proofing business operations
Reduce costs across the business by:
- Tracking prices for raw materials
- Identifying and remove bottlenecks that reduce productivity
- Cutting waste of energy, water, and other resources
- Detecting early signs of anomalies before they snowball into costly part failure
- Spotting opportunities to improve process with minimal outlay
- Cutting downtime
Achieve Overall Equipment Effectiveness (OEE) by:
- Reducing time to root cause analysis
- Improving equipment lifecycle
- Refining maintenance schedules to keep all equipment running as efficiently as possible
- Increasing product quality
How can process plants make the most of advanced analytics?
Invest in human resources
Even the most advanced analytics platform relies on humans to set it up and run it. Check that you have employees with the necessary skill in place, including data scientists to configure parameters and train and test ML models if your analytics solution requires it, and process engineers with enough time to take responsibility for using the tools and following up on their predictions.
Democratize access to analytics insights
If you want to see the true value of your advanced analytics platforms, you need to open them up to as much of the plant as possible. Look for self-service tools that can be used independently by engineers and plant managers without any data science background, and invest in training courses so that everyone knows how to make the most of the new platforms.
Gather your plant data
Advanced analytics tools need large datasets to work their magic to their fullest extent. That’s not a problem for process plants, which have masses of data, but that data is frequently isolated in disparate formulas, frameworks, and systems. Before bringing in an advanced analytics platform, find a data processing warehouse that can combine all your data streams and convert them to a unified format for easy analysis.
Lead a broad culture shift
Advanced analytics and other AI-powered platforms are more than just another tool you’re bringing into the plant. They are part of a digital transformation that demands an organization-wide culture shift. Educate employees about the benefits and challenges of digital transformation to ensure that everyone is on board with the digitalization journey.
Start with the areas of maximum ROI
When you can quickly demonstrate the value of your new analytics tools, you’ll be able to gather employee support and participation much more easily. Map your business needs to identify the areas that need the most improvement, absorb the most employee time, or have the biggest impact on profitability, and start there to quickly prove the value of your investment.
What are the benefits of advanced analytics for process plants?
Implementing advanced analytics to process manufacturing plants gives you visibility into your plant, market, supply chain, and customer demands, enabling you to cut costs, increase profitability, refine production quality and improve customer experience. Use advanced analytics platforms to enhance business strategy and drive innovation to future-proof your organization and boost your bottom line.