With the rapid pace of technological growth, it’s not always easy to imagine where digital

transformation is taking the manufacturing sector, but one good way of doing this is to take

a closer look at the “Digital Twin” concept within the industrial Internet of Things (IoT).

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As IoT connectivity provides the manufacturing sector with an increasing number of ways to

access sensor-driven data locked in industrial machines and equipment, the need for data

analysis, management, and control methods has also become more crucial.

The amount of data collected from monitoring a smart factory is enormous, but if that data

isn’t aggregated and organized in a way that can support the decision-making process, then

it’s of no use.

One method that’s proving to be invaluable to engineering and customer service teams that

are looking to leverage collected data is that of the “Digital Twin”.

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Keywords

Control Valves, Predictive Maintenance, Process Analytics, Industrial Internet

of Things (IIoT), Expertise as a Service (EaaS), Seeq

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Summary

At ARC Advisory Group’s 20th Annual Industry Forum in Orlando, Florida,

Shawn Anderson, Senior Research Specialist for Fisher Valves, a

division of Emerson Process Management, gave a presentation on how the

company is leveraging the Industrial Internet of Things (IIoT) to help end

users reduce valve-related unplanned downtime.

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Keywords

Analytics, Manufacturing Productivity, Clean-in-place, Product Filling

Overview

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Abbott’s nutrition business, a division of the global healthcare company,

manufactures a wide variety of science-based

nutrition products. These range from Similac

brand infant formula to adult nutrition brands

such as Ensure. Recently, ARC had the opportunity

to speak with James Li, an engineering

manager in the Abbott Nutrition division. We

discussed how the company uses Big Data and

analytics to improve manufacturing productivity.

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Keywords

Manufacturing Intelligence, Operations Intelligence, Real-time Data, Discovery

and Investigational Software, Operations Data, Industrial Analytics,

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Avangrid Renewables, Seeq

Overview

Avangrid Renewables is a subsidiary of AVANGRID, Inc., and part of the

IBERDROLA Group. Spain-based Iberdrola S.A. is the largest wind energy

company in the world. As ARC Advisory Group recently learned, the company

collects a wide variety of data from many different sources. However,

in the past it faced challenges when it came to gaining

useful insight from these data. Particularly

problematic, was the difficulty determining and

documenting lost generation across its wind turbine

fleet time due to voluntary generation

curtailment to meet contractual obligations. Inability

to do so, can lead to lost revenues.

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Of Microbrews and Medicines Understanding Their Similarities and Differences in Bioprocessing

Can Help Improve Yields and Quality While Reducing Cost

by Lisa J. Graham

Keywords

SPM, FSM, IIoT, OEM, Ingersoll Rand, TCS, Coherent, Fisher Valves, Seeq

Overview

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The prime reason most industrial plants still have internal, on-site mainte-nance staffs is to reduce repair times and unplanned downtime, which negatively impact revenue, customer satisfaction, cost, and other key busi-ness metrics. In most plants today, contracting with the equipment manufacturer for maintenance usually results in unacceptably long periods of downtime for critical equipment while waiting for a technician to arrive – particularly with the typi-cal two passes required for inspection and repair.

However, emerging Industrial IoT (IIoT)-enabled condition monitoring and predictive maintenance approaches allow manufacturers to re-consider outsourcing to the OEM. Faced with the current skills shortage and other constraints, many will find OEM supplier-provided services appealing.

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Seeq® is an advanced analytics solution for process manufacturing data.

With Seeq applications, you and your team can rapidly investigate and share insights from operations and manufacturing data sources to improve production outcomes. OSIsoft PI, Honeywell PHD, GE Proficy, and other historians, as well as relational data from SQL Server, Oracle, and MySQL may be easily integrated to find insights that enable continuous improvement in production yield, quality, availability and other KPIs.

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Organizations benefit from using Seeq’s solutions to quickly find insights in production data and share them among teams, operations, and other key roles. Seeq enables engineers and subject matter experts (SME) to get more value from data already collected and enables organizations to rapidly access and execute on those insights.

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Process manufacturing organizations run on data—from a manufacturing, operations, and business perspective.

The data generation and collection strategies at the center of manufacturing processes have evolved dramatically, especially in recent years. Process manufacturers now collect and store huge volumes of data throughout their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos.

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These advances have coincided with the proliferation of connected sensors and increasingly inexpensive storage, leading to an Industrial Internet of Things (IIoT) projected to generate more than 4 trillion gigabytes of data per year by 2020, according to IDC Research.

Data analytics solutions have a huge positive impact on the growing volumes of data in many sectors, from retail to finance. So why aren’t these solutions widely leveraged in process manufacturing? With so much data and the promise of so many new technologies, why is it so difficult to apply these technologies to process manufacturing and gain the same benefits as other sectors?

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