Chemical Industry Meets Industry 4.0 and OEE Goals with Real-time Analytics to Increase Factory Performance
The chemical industry accounts for 12% of manufacturing in North America, transforming raw materials into chemical-based products. It serves many industries including automotive, agriculture, consumer goods, industrial operations, and transportation. Chemical sectors include pigments, food additives, synthetic rubber, polymers, resins, plastics, acids, and fertilizers.
The chemical industry faces many challenges including variations in the availability, quality, and cost of raw materials, meeting fluctuating demand for products in a global economy, and adhering to increasingly strict regulations. One of the biggest challenges in chemical manufacturing today is learning how to combine production and control system data in real-time to adjust formulas and processes as product flows through production.
Moving forward, chemical manufacturers need more efficient ways to monitor quality issues in real-time, particularly for the quality and performance of large reactors. Correcting flaws in the production process and predicting downtime of machines are critical factors for increasing efficiencies on the production floor.
The productivity of chemical manufacturers can be improved by smart manufacturing techniques such as predictive asset management which collects data from sensors on critical equipment so operators can identify patterns to predict and diagnose possible breakdowns. Advanced analytics from these techniques can substantially raise the level of understanding of what happens in a chemical plant’s manufacturing operations. Since energy costs contribute significantly to chemical manufacturing costs, predicting these potential breakdowns and preventing them can reduce energy waste.
To remain competitive, chemical manufacturers need to increase productivity and improve quality to meet customer’s specifications while reducing costs. Investing in digital transformation allows businesses to gain better control of processes and ensure clearer analytical insights to improve production decisions.