Overview
Polyurethane production in plastics & polymers production
Reliable and Durable Process and Monitoring Instrumentation for the Polyurethane Production
Polyurethane is the basis for many foam and insulating materials, for moulding materials, elastic fibres, polyurethane paints and adhesives. Polyurethane is manufactured in several intermediate stages using the intermediate products aniline, MDA (methylenedianiline) and MDI (methylene diphenyl diisocyanate). Firstly, aniline is created from nitrobenzene, water and hydrochloric acid in a continuous liquid phase hydrogenation process using an iron catalyst. In the next step, MDA develops as the aniline condenses with formaldehyde in the presence of hydrochloric acid as a catalyst. Adding caustic soda neutralises the mixture and the MDA can be separated. A raw MDI mixture develops by phosgenating MDA in a solvent. The solvent, excess phosgene and the hydrochloric acid by-product are recovered and recycled. Next, the MDI is treated by way of fractional distillation, crystallisation or sublimation so that this main pre-product can be used to manufacture polyurethanes.
The operating conditions for manufacturing MDI present huge challenges for the flow, pressure and level measuring systems in terms of reliability and durability. Besides their extremely corrosive properties, the produced substances tend to crystallise out and are partly toxic. KROHNE's portfolio includes many quality products in this respect that meet these types of process requirements. For example, ultrasonic flowmeters based on the transit time difference principle for use in the flow and return of the solvent with a high phosgene load. The device can also detect changes in the process, concentration changes or contamination in the liquid by way of sound velocity. It can also reliably monitor the cooling of the highly exothermal phosgene synthesis using our electronic differential pressure measurement systems. And use of the CalSys analysis management and data acquisition system (AMADAS) enables predictive maintenance of the process analytics, keeping faults and maintenance costs to a minimum. The increased availability improves yield and the quality of the product at the same time.