As the Industrial Internet of Things continues its digital transformation of the manufacturing sector, smart factories are exploring how real-time analytics can not only improve efficiency and increase profitability, but also reduce energy costs across plant-wide operations, individual factories and production lines.
Improving energy efficiency has traditionally been challenging for manufacturers, because of the variety of plant machinery and production equipment at each facility, in addition to the building, lighting and HVAC systems that contribute to the overall energy footprint.
Additionally, larger manufacturers often have extensive operations that span multiple states, utilities and energy markets, along with cumbersome energy bills that only provide a general overview of energy consumption, but not the detailed, granular equipment usage data needed to significantly drive cost savings.
As machines on the factory floor become more connected, however, plant managers and operations engineers can access more and more machine data, but can often feel overwhelmed by the volume of information that can be captured, while others are hesitant to devote resources to implementing a new system, even if that system has the potential to save money for the company.
By embracing energy efficiency as a cornerstone of an organization’s overall IIoT strategy, many manufacturers have been able to identify potential savings that offset the initial cost of implementing a manufacturing analytics solution to meet their performance, quality and production capacity targets for 2018 and beyond.
According to an article InTech Magazine in January 2017, early adopters of IIoT have been able to reduce energy expenses by 30 percent and lower operating costs by 20 percent, while increasing production availability and capacity by two extra weeks.
To accomplish this, an IIoT analytics solution can be configured to collect, monitor and analyze smart sensor data from a wide range of systems on the factory floor, from valve pumps and conveyor belts to air compressors and HVAC systems, as well as servers and data centers.
Organizations then leverage IIoT analytics to correlate all of this machine data to track energy consumption, power load and operating temperatures across equipment running in their facilities to identify potential energy waste, optimize production schedules and dramatically reduce energy costs.
By comparing actual equipment performance over time with projected equipment management and maintenance schedules, IIoT analytics allows organizations to save operating costs by understanding the relationship between energy usage and overall system performance across multiple facilities and locations.
Armed with this data, companies can determine which equipment is wasting the most energy, reduce performance inefficiencies, calculate the cost of operating equipment at peak and non-peak times and implement smart energy plans to eliminate production waste, lower plant wide energy costs and even potentially qualify for energy rebates from utilities.
The Database of State Incentives for Renewables and Efficiency (DSIRE) provides a comprehensive source of information on incentives and policies that support renewable energy and energy efficiency throughout the United States, allowing organizations to quickly and easily search to see which corporate tax credits, loans, grants and rebates might be available in their zip code or state.
Electricity Local is another resource that provides organizations with a comprehensive electricity guide on thousands of cities and towns all across the United States to calculate energy rates and compare consumptions trends when building business justification for the energy savings impact that an IIoT analytics solution can have across manufacturing operations.
IIoT analytics can provide the detailed equipment usage data needed to document energy consumption, prove compliance with energy efficiency programs and validate investment in smart manufacturing initiatives to fully realize the transformative power of IIoT to reduce plant-wide operating costs.
“Industrial IoT can help companies identify problems early through predictive analytics and save money as a result,” according to a Tech Republic article from June 2017, but a company “needs to first identify where they’ve had problems in the past, and which assets are most valuable.”
Contact Sightline Systems today to document the potential energy savings of an IIoT analytics solution, calculate your Return on Investment (ROI) and develop an initial Proof of Concept for your organization.