(82d) Gleaning Value from Digitalization in Process Manufacturing

The world has gone through three Industrial Revolutions over the past three centuries with the advent of steam driven machines to mass production lines and automation and is now going through a fourth with Digitalization. Digital transformation through the application of the Industry 4.0 technologies for increased global collaborative teams, augmented intelligence, and real time decisions utilizing insightful information is rapidly becoming the standard.

Digital transformation captures additional revenue and identifies opportunities using digital technologies to make higher quality information readily available. Digital transformation enables improved decision not possible with pre-digitalization paradigms. Digital transformation entails a process whereby several Digital technologies are seamlessly integrated, requiring relevant expertise and domain experience to do so. Data is the key raw material in the Digital transformation process.

There is no dearth of data available from Process manufacturing. However, direct use of data for business intelligence can be misleading. Advanced analytics and impactful presentation of data that is converted to information, is necessary to enable use of data for decision making. The Industrial Internet of Things (IIoT) is a valuable tool that can facilitate advanced analytics execution and the digital transformation process, if utilized appropriately. Digital technology software tools by themselves requires specalized engineering effort (Decision Insight Engineering), to convert it into a readily utilizable solution that could provide Augmented Intelligenceto the manufacturer’s teams to meet the digitalization objective.

The objective of any digitalization initiative is to capture revenue and value; not to implement new technology for the sake of doing so. The selection of digital technologies to implement are based on “Use Cases” whose value proposition is known up front. Defining the “Use Case” and its estimated value is the key to ensure a successful Digitalization planning process.

Such a Digitalization initiative helped a US petrochemical manufacturing major to address multiple operational challenges:

• Furnace Run-Length below Design
• High Emmissions of SOx, NOx, etc.
• Frequent Failure of Assets : Higher Equipment Downtime / Unplanned Shutdowns
• Lower Throughput

This paper will outline a roadmap for Digtal transformation in Process manufacturing, the nature and significance of the work that Decision Insight Engineeringentails and the Digital technology tools that it helps convert to directly usable solutions, along with a case example of an application for a US ethylene manufacturer.