IIoT Can Rewire The Process Industry

Digitalization can offer process industries increased process optimization and plant efficiency. Industrial Internet of Things (IIoT) adds predictive maintenance, asset information management, and open device configurability.

Digitalization can offer many advantages to process industries, such as new opportunities in process optimization and increases in plant efficiency. The Industrial Internet of Things (IIoT) offers predictive maintenance, asset information management, and open device configurability to a vertical that is just beginning to embrace Industrie 4.0.

Process plants are built around myriad of moving parts, and increasing age brings inefficiencies. While utility prices rise, legacy plant equipment incrementally adds to upkeep costs. Legacy plants waste approximately 30% of the energy they consume.

The convergence of information technology (IT) and operations technology (OT) data helps factory operations. This is where the buzz around IIoT starts making sense. As sensors and Internet- protocol-enabled devices proliferate, IIoT ultimately will dominate the factory floor. With more effective information analysis manufacturers will be able to create leaner processes, streamline operations, and drive cost efficiencies. In a connected ecosystem, machines can send alerts that communicate their status, enabling production detours without disruption. Imagine the possibilities across multiple sites connected by a cloud-based enterprise resource planning (ERP) system. Intelligence and best practices established in one model plant could be seamlessly exported and implemented across every connected facility.

Efficiency increase: 82%

If reports are to be believed, manufacturing plants experience an 82% efficiency increase with digitized processes. Addressing utility costs, a major Japanese chemical producer embedded 148 steam traps with sensors, leading to a 7% reduction in the cost of steam.

With IIoT, plant operators can access more asset-related data. As IIoT links edge sensors and analytics, it will provide benefits by:

• Cost-effectively collecting data using wireless, low-energy sensors

• Developing data-driven, strategic, actionable operational intelligence

• Presenting this information to plant managers at the right time

  • Delivering performance improvements once corrective actions have been taken.

Going by present standards, operators have been leveraging this information to transition from reactive maintenance activities to a more efficient predictive maintenance framework. Implementing efficient maintenance prioritization across multiple sites is a major hurdle that remains.

Maintenance, AI, optimization

Combining computerized maintenance management system software and data gathered through IIoT, maintenance personnel can monitor asset groups, specifying parameters for triggering alerts, automating responses, and work order generation by directly interfacing with cloud ERP.

The process industries will find advantages in using artificial intelligence (AI). To increase plant safety, operators have been reducing manual intervention on the factory floor. Manufacturing systems that have capitalized on machine learning and predictive data analytics reportedly have improved production capacity by 20%, while lowering resource use by 4%. Human faculty for reasoning and logic are essential to manufacturing. As machines begin to think as we do, AI will become the central nervous system of the connected plant ecosystem, and using intelligence derived from to squeeze the maximum value out of every dollar spent.