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Identifying the Immediate ROI of the Industrial IoT

By Jeff Elliott B

y now, most manufacturers have heard of the promise of the Industrial Internet of

Things (IIoT). In this bold new future of manufacturing, newly installed sensors will collect previously un- available data on equipment, parts, inventory, and even personnel that will then be shared with existing sys- tems in an interconnected system where machines learn from other ma- chines and executives can analyze re- ports based on the accumulated data. By doing so, manufacturers can

stamp out inefficiencies, eliminate bottlenecks and ultimately stream- line operations to become more com- petitive and profitable. However, de- spite the tremendous potential, there is a palpable hesitation by some in the industry to jump into the deep end of the Industrial IoT pool. This hesitation stems from one

primary concern: If a company in- vests in IoT, what specific ROI can it expect and when? How will it

streamline the company’s process such that it translates into greater efficiencies and actual revenue in the short and long term? Although it may come as a sur-

prise, the potential return can actu- ally be identified and quantified pri- or to any implementation. Further- more, implementations can be scala- ble for those that want to start with “baby steps.” In many cases, this is being fa-

cilitated by a new breed of managed service providers dedicated to IIoT that have the expertise to conduct in- plant evaluations that pinpoint a specific, achievable ROI. These providers can then imple-

ment and manage all aspects from end to end so manufacturers can fo- cus on core competencies and not worry about becoming IIoT experts. Like their IT counterparts, this can often be done on a monthly fee sched- ule that minimizes, or eliminates, up-front capital investment costs.

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Defining IIoT Despite all the fanfare for the

Internet of Things, the truth is that many manufacturers still have only a partial understanding of what it is and how it applies to industry. While it might appear complicated from the outside, IIoT is merely a logical ex- tension of the increasing automation and connectivity that has been a part of the plant environment for decades. In some ways, many of the com-

ponent parts already exist in a plant or are collected by more manual methods. However, a core principle of the IIoT is to vastly supplement and improve upon the data collected through the integration of sensors in such items as products, equipment, and containers that are integral parts of the process. In many cases, these sensors pro-

vide a tremendous wealth of critical in- formation to increase efficiency and streamline operations. Armed with this new information, IIoT then seeks to facilitate M2M (machine-to-ma- chine) intelligence and interaction so that the system can learn to become more efficient, based on the available data points and traffic patterns. The mass of data collected is

turned into reports that can be ana- lyzed by operations personnel to pro- vide further insight into ways to in- crease operational savings and rev- enue.

In manufacturing, the net re-

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than just collect data; it must be turned into actionable insights that increase productivity, generate sav- ings or uncover new income streams. For Pacesetter, a national processor and distributor of flat rolled steel that operates processing facilities in Atlanta, Chicago and Houston, IIoT holds great promise. The company is currently work-

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ing with Industrial Intelligence, a managed service provider that offers full, turnkey end-to-end installed IIoT solutions, to install sensors in each of Pacesetter’s facilities to in- crease efficiency by using dashboards that allow management to view in- formation in real time. “Having access to real-time data

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from the sensors and being able to log in and see it to figure out the answer to a problem or question so you can make a better decision — that type of access is incredible,” says Pacesetter CEO Aviva Leebow Wolmer.

In a recently completed project,

Industrial Intelligence installed sen- sors designed to track production schedules throughout the plant. The information revealed two bottlenecks: one in which coils were not immedi- ately ready for processing, slowing production, and another where the skids on which they are placed for shipping were often not ready.

Despite the tremendous potential, there is a palpable hesitation by some in the industry to jump into the deep end of the Industrial IoT pool.

By making the status of both

coil and skids available for real-time monitoring and alerting key person- nel when production slowed, Paceset- ter was able to push the production schedule through the existing ERP system. This increased productivity at the Atlanta plant by 30 percent. Implementations in the other two fa- cilities yielded similar increases in productivity.

Taking the First Step According to Darren Tessitore,

COO of Industrial Intelligence, the process of examining the possible ROI begins with a factory walk- through. This allows the company to leverage its expertise in manufactur- ing process improvement and IoT en- gineers that understand the back- end technologies. A detailed analysis is then pre-

pared, outlining the scope of the rec- ommended IIoT implementation, ex- act areas and opportunities for im- provement and the location of new sensors.

According to Tessitore, this cov-

ers the entire gamut: all hardware and software, station monitors, etc.; the building of real-time alerts, re- ports and analytics; training man- agement on how to use data points to increase profits; and even continu- ously monitoring and improving the system as needed. “Unless you’re a huge company,

you really don’t have somebody who can come in and guide you and create a cost-effective solution to help you compete with the larger players in the space,” says Leebow Wolmer. “I think that’s what Industrial Intelli- gence offers that can’t be created on

your own.” Contact: Industrial Intelligence,

LLC, 1045 Big Shanty Road, Kenne- saw, GA 30144 % 770-462-2940 E-mail: Web: r

July, 2017

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