Rewire the process industry with IIoT

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


The convergence of industrial manufacturing systems with the capabilities of advanced distributed computing technology, low-cost sensors, and the Industrial Internet of Things is rapidly transforming the value chain. Courtesy: L and T Technology Services Ltd.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.

In China, in 2016, the country's wind curtailment rate reached 17%; wind energy wasted almost equaled the total electricity consumed by Beijing in a year.

The U.S. contributes 30% of the world's waste through industrial pollution while consuming 25% of its resources.

Regulators increasingly are pressuring the industrial sector to reduce waste, curb pollution, and improve resource utilization—incentivizing efficiency and penalizing violations. In a customer-dominated business landscape, manufacturers will have to explore options for boosting competitiveness. Since utility supply costs generally are beyond manufacturers' control, some creative thinking is necessary for reducing operating and production costs.

Help from IT-OT convergence

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. As manufacturers realize the potential of these tools and capabilities to collect information, they will be able to create leaner processes, streamline operations, and drive cost efficiencies.

Consider the simple task of equipment maintenance. In the connected ecosystem, machines can send alerts that communicate their status, enabling production detours without disruption. This is just one production line in one factory. 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. 

82% Efficiency increase

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 an increasing volume of asset-related data. As the bridge between 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. 

Improving maintenance

This sets the stage for deploying total productive maintenance (TPM). Developed in the 1950s, this eight-pillared model's goal is to focus perpetually on preventive and proactive techniques for enhancing equipment reliability and, eventually, productivity.

Combining computerized maintenance management system (CMMS) 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. 

Artificial intelligence

The process industries will find advantages in using artificial intelligence (AI). in a bid to increase plant safety, operators have been striving to reduce the need for manual intervention on the factory floor.

Amit Chadha is president of sales and business development and is a member of the board at L and T Technology Services Ltd. Courtesy: L and T Technology Services Ltd.Robotics and process automation have been successfully used across industries to that effect. Greater workflow efficiencies will increase throughput and material consumption. The stream of data generated by IIoT presents excellent opportunities. Manufacturing systems that have capitalized on machine learning and predictive data analytics reportedly have improved production capacity by 20%, while lowering resource utilization by 4%. 

Asset optimization

Human faculty for reasoning and logic are essential to manufacturing. As machines begin to think like we do, AI will become the central nervous system of the connected plant ecosystem, and using intelligence derived from data analytics to squeeze the maximum value out of every dollar spent.

Amit Chadha is president of sales and business development and is a member of the board at L&T Technology Services Ltd., a CFE Media Content Partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, KEYWORDS: IIoT, artificial intelligence

Digitalization increases efficiency compared to traditional methods. Sensors and monitoring will move maintenance from reactive to proactive. Artificial intelligence will increase optimization. Consider this How can greater digitalization and automation expand your opportunities for optimization? Online extra: See and link to more info in the online version of this article. 

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