Methanol is a clear liquid chemical that is water soluble and readily biodegradable, comprised of four parts hydrogen, one-part oxygen and one-part carbon. It is the simplest member of a group of organic chemicals called alcohols.
Methanol is used to produce other chemical derivatives, which are themselves used to produce thousands of products such as building materials, carpeting, foams, resins, plastics, paints, polyester and health and pharmaceutical products.
Methanol also is a clean-burning, biodegradable fuel making it an attractive alternative fuel for powering vehicles and ships and for a source of energy.
Methanol is typically produced on an industrial scale using natural gas as the primary feedstock.
However, methanol can be made from many feedstocks including coal, solid waste, wood, biomass, biogas and waste CO2.
Methanol production is not as complex as natural gas processing but the processes and activities are equally as critical to record and analyze.
It is critical to record each specific process and its related components (physical and IoT), component status, component reading, process input (feedstock, additive, catalyst, etc.), process output (intermediate substance, waste, product), tests, related parties, party roles and responsibilties, product and substance storage, shipments and associated timeframe measurements to provide data for real-time monitoring, complex analysis of quantities produced and resulting quality measurements.
This is just a brief description of the complex processes and data relationships that were used to develop the suite of logical data models that comprise the Methanol Production offering.
Data is the essential component of this complex process without which methanol could not be safely and economically produced in large quantities. Complex process such as methanol production are made clear by large-format, detailed data models that speak the same language as both IT, process engineers and management.