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Tech & Trends


HOW EDGE COMPUTING AND IOT CAN REINVENT MANUFACTURING

By Chris Pemberton, Aug 09, 2022

This article is the third in a series exploring use cases and innovative
approaches to edge computing and IoT across a range of industries where these
technologies are expected to deliver outsized business value.





THE EDGE-TO-CLOUD OPPORTUNITY

The manufacturing sector tends to gain real-time access to much of their data at
the edge versus in the cloud. Many reasons for this include lower latency,
increased cybersecurity, manageable data analytics, expanded interoperability,
and reduced storage costs. These all may be valid reasons for staying near the
edge, but by doing so, manufacturers are missing an opportunity to modernize
their operations, increase revenues, and accelerate ROI.

Cloud computing provides an untapped vein for conducting big-data insights at
scale. By expanding the capabilities of data-driven analytics in the cloud,
manufacturers can identify and solve issues across a global big-data footprint.

Edge computing is a first step toward digital transformation, and some
manufacturers are beginning to take subsequent steps by moving their data to the
cloud for greater business impact. Here are three use cases of edge computing
and Industrial IoT (IIoT) — the use of IoT in industrial sectors and
applications — that are having an impact.

IIot takes networked sensors and intelligent devices and puts those technologies
to use directly on the manufacturing floor, collecting data to drive artificial
intelligence, predictive analytics and preventative maintenance, and machine
learning.


1. INVENTORY TRACKING AND PLANT MONITORING

Tracking inventory and monitoring plant operations are becoming common uses for
IIoT to improve operational efficiencies and productivity. To track the lifespan
of its inventory, Microsoft’s plant in Suzhou, China took advantage of machine
learning (ML) at the edge. Within hours of launching ML, the plant was able to
identify inventory that was close to being obsolete. As stated by Darren Coil,
director of business strategy, in a McKinsey report, “The data was always there,
but we weren’t seeing it until IoT highlighted it for us.” The report also notes
that a five-person team discovered and addressed this finding, saving the plant
nearly $5 million in one year and cutting inventory costs by $200 million.

The next step for Microsoft would be to apply cloud-based inventory management
to monitor and maintain not just the health of its inventory, but also inventory
levels across global teams, locations, and applications. Data derived from
tracking inventory at the edge could then be disseminated at scale, resulting in
benefits such as new innovations that provide value throughout the enterprise.

Texmark Chemicals wanted to monitor its plants more effectively as part of its
vision to build a “refinery of the future.” In 2018, the Texas-based
petrochemical company completed an IIoT project designed to make chemicals
safely and more cost-effectively, as well as to obtain better process analytics
and increase up-time, productivity, and worker safety. Texmark worked with a
number of partners, including Deloitte, Hewlett-Packard Enterprise, and Aruba on
a three-phase build-out that included both a digital foundation of edge-to-core
connectivity and location-based services that used wireless sensors, both
high-speed data and video capture analytics, and a turnkey IoT solution
featuring predictive maintenance and asset monitoring.

The plant is automated by sensored devices and advanced analytics, which
generate insights and reduce any risks for human errors. For example, sensors
were placed on the plant’s pumps to monitor performance. Before that, the pumps
were monitored through a hardwired connection to a control center. This approach
cost between $2,000 and $7,000. By placing $300 worth of wireless sensors on the
pumps, Texmark has derived considerable savings. In addition, the company has
seen a 50 percent reduction in planned maintenance costs, with the potential to
significantly reduce the 35,000 hours that employees spend monitoring the plant
each year. Imagine the possibilities if Texmark could run data and analytics in
the cloud across multiple plants and its supply chain.


2. AFTER-SALES SUPPORT

Superior after-sales support can make or break a sale. Once a product leaves the
factory, manufacturers can gain a competitive edge by monitoring the product’s
operation to provide the right support at the right time. This was the case at
Johnson Controls-Hitachi Air Conditioning (JCHAC), a manufacturer of industrial
air conditioning equipment in 150 countries. The company wanted to provide
superior customer service and generate new revenue, yet it needed a
cost-effective way to proactively monitor and conduct maintenance and other
services on its air conditioning installations to improve product performance.

During manufacturing, the destination of an air conditioning unit is usually
unknown, making it impossible to fit the right local SIM in the factory.
Marubeni Network Solutions worked with JCHAC to provide it with a global
connectivity service for an initial 120,000 units annually using a global
communications management end-to-end IoT connectivity platform from Nokia. The
technology enables JCHAC to factory-fit its air conditioning units with a
standard SIM to provide connectivity in its target markets, avoiding the costs
and complexity of manufacturing variants for every country.

JCHAC can also manage its installed air conditioners remotely, regardless of
location, for an accurate view of their performance. Rather than implement
maintenance in fixed intervals, the company can identify problems before they
escalate, saving money on repair costs and call-out fees and extending product
lifespans. The next step for JCHAC would be to aggregate all of its sensor data
residing at the edge and run large-scale analytics and ML in the cloud. This
would provide data teams with insights into not just regional edge environments,
but also global performance.


3. IMPROVING BROWNFIELD SITES

Contrary to what some data leaders may believe, not all IIoT applications
require the development of new greenfield facilities. In fact, updating older
plants and legacy equipment can be enough in certain situations.

At its Czech Republic-based Rakona plant, which dates back to 1875, Procter &
Gamble (P&G) produces four million cases of dishwashing soaps and fabric
enhancers daily. After ultimately shifting to liquid products, the plant had to
ramp up capacity, which required digitization and automation. To address the
shortcomings of manual sampling and subsequent delays in product releases, the
company eventually rolled out an in-process quality-control system in its legacy
systems. Sensors now monitor product characteristics, allowing operators to
obtain data that helps determine batch quality for release. Using sensors also
lets workers stop the line if a deviation occurs. The results of using sensors
are a 50 percent reduction in reworking and complaints, less scrap, fewer
quality inspections, and a reduction in throughput time of 24 hours.

By expanding the capabilities of data-driven analytics in the cloud,
manufacturers can identify and solve issues across a global big-data footprint.

The Rakona plant is just one example of P&G’s efforts to digitize manufacturing.
Accessing data at scale is the next step in P&G’s digital transformation. In
collaboration with Microsoft, P&G will leverage the Microsoft Azure cloud
platform to digitize and integrate data from more than 100 manufacturing sites
globally and will also enhance its AI, ML, and edge computing services for
real-time visibility that gives P&G employees the ability to both analyze
production data and use AI to make quick decisions that drive improvement and
exponential impact.

With the enormous amounts of IIoT data at their disposal, manufacturers have the
potential to access and act on that data at scale by moving edge datasets to the
cloud for large-scale analytics and insights. The edge-to-cloud opportunity
provides a number of benefits: reduction in plant operating costs; increased
agility, such as the ability to keep up with new developments and technologies;
and the ability to scale AI, ML, and data analytics globally in order to make
smarter business decisions.

Learn more about how to activate edge and IoT data at scale for use in any cloud
environment.

SHARE

--------------------------------------------------------------------------------


CHRIS PEMBERTON, VP OF MARKETING, WANDISCO

Chris has deep expertise in modern B2B technology marketing and connecting
brands with buyers through powerful messaging, content, demand gen, and digital
experiences. He has led content strategy with Gartner and Charles Schwab as well
as digital marketing and demand-gen programs for Persado AI, SANS Institute, and
NextHealth Technologies. He delivered double-digit traffic, lead, and revenue
growth for GU Energy Labs and Ghirardelli Chocolate Company. Chris spent years
advising C-level technology executives while at the Corporate Executive Board
(now Gartner) and holds an MBA from the Middlebury Institute of International
Studies as well as certificates in advanced digital marketing analytics.

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