Reduce costs and improve performance with intelligent design and common sense
The Internet of Things, Industry 4.0, and energy management can be combined to make a heady cocktail that suggests an exciting future with reduced costs and improved performance. However, as is the case with any cocktail, you could be left with a severe hangover, wondering where all the promise and money went.
Disruptive technologies are emerging at an unprecedented rate. It is difficult to know which technologies offer genuine savings versus those that may be rendered obsolete before they achieve their potential. It is challenging for organizations to cut through the hype and identify those technologies that are applicable to their needs and can deliver an immediate positive return on investment.
This article examines the Internet of Things (IoT) and Industry 4.0 from the perspective of realizing energy cost and consumption savings. What options, if any, are cost effective now? How can an organization introduce the IoT and move toward Industry 4.0 without compromising its financial performance?
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All the above and energy efficiency
Proponents of the Internet of Things and Industry 4.0 have identified energy efficiency as a significant potential benefit. The American Council for an Energy Efficiency Economy estimated potential savings of 12 to 22 percent of all energy consumed, while the consultant McKinsey suggests 10 to 20 percent energy savings.
These are high-level estimates for potential future benefits. But what energy cost and consumption savings have existing IoT technologies achieved to date? Where is the potential, and what would be the best way to identify what is relevant to your organization now?
Looking through the lens of EN 16247:2014, efficiency opportunities can be broadly classified across building, process, and transport. Figure 2 is a summary of some deployed technologies and their efficacy for reducing energy consumption.
Figure 2. Selected IoT technologies from the perspective of EN 16247: 2014 (energy audits).
Process
Traditional industrial energy management focuses on the efficient provision and use of process energy needs, such as heating, cooling, compressed air, and electricity. The IoT has a wealth of new data streams to support energy management measures. Process industries may be slower to adopt some of these technologies than the consumer market due to a greater familiarity with the use of sensors and automation. A key driver for the digital transformation for the process industries is maintaining global competitiveness and technological advances, therefore forcing the alignment of production and wider business processes through the tools that offer new possibilities for business models.
Monitoring-led preventative maintenance, condition-based maintenance, and predictive maintenance
To increase reliability and efficiency, and to gain other operating benefits, such as reduced maintenance and improved safety, many refineries and process plants are turning to the IoT. Technologies, such as acoustic monitoring of steam traps, condition monitoring of pumps, and heat exchanger performance, all wirelessly connected to supervisory control and data acquisition and analytics systems, provide cost-effective installation and paybacks of less than six months.
“Calculations show the difference in operating costs associated with equipment reliability and energy efficiency between a well-run refinery and an average one is about $12.3 million per year for a typical 250,000 barrel-per-day facility. Assuming about 60 percent of refineries are not operating as well as they could, the overall worldwide financial impact runs to billions of dollars annually,” says Deanna Johnson of Emerson Process Management.
Set point control
A new generation of software tools for energy efficiency allows two ways of energy plant management: open loop, where the optimal set points are indicated to the operators to manually set the optimization variables; or closed loop, where the set points are sent directly to each optimizable variable. These implementations can typically achieve energy-cost reductions from 3 to 8 percent for the open-loop model, and 6 to 15 percent for closed-loop applications.
Read the full article as publiched in isa.org By Brian Dwyer, C.Eng MIEI, and Joao Bassa, MSc