Retail Product Management - Riversand

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Data-Driven Challenges for Industrial
Manufacturers
Riversand is recognized as a leader in The
Forrester Wave Product Information Management
Solutions, Q4 2016
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Data-Driven Challenges for Industrial
Manufacturers
Four challenges that block the road to a
successful implementation of big data and data
analytics at industrial manufacturers. Industrial
manufacturers inhabit a world littered with
uneasiness. Global demand for manufactured
products is growing at a snails pace. Output was
expected to increase by just 3.1 percent in 2016
and is estimated to increase by 3.4 percent in
2017, according to the International Monetary
Fund. In a slow-growth environment such as this,
productivity gains are paramount. And that could
be a boon for industrial manufacturers. Indeed,
industrial manufacturers can best serve their
customers (and themselves) by designing tools and
equipment that improve the efficiency, costs, and
performance of factories and other capital
projects. For customers, the desire for
efficiency and quality improvements are a given,
but companies increasingly want visibility deep
into their supply chains They want connectivity
tools that provide insight into production
levels, inventory and capacity availability,
quality levels, and order status from all their
suppliers.
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Time-Triggered Versus Event-Triggered Control
Systems
Most of the todays manufacturing is centered
around stable technological systems based on
pre-determined levels of demand. Usually, the
production process is triggered by a specific
demand schedule which is automatically fed into
the ERPs and the manufacturing execution systems
(MESs) which pull all the necessary resources
from the supply chain. After the production ends,
the finished product is packaged and shipped to
the final customer through various distribution
channels. The long-term aim of the manufacturing
companies is to move on from these time-triggered
systems towards more efficient event-triggered
control systems where the company produces only
when the customer orders the product. The factory
will be required to respond to the data signal
(the order) only when it occurs, allowing the
company to utilize their capital efficiently and
configure the systems to collect data and
communicate it where and when needed.
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Data Sharing, Not Just Data Exchange
Another significant challenge for the
manufacturing enterprises is to create a unified
data model and tie in together all the
independent systems in the manufacturing process
(starting with design, engineering production,
distribution, and selling). Data needs to be
integrated and shared to every business unit in
order to minimize the wasted materials and
activities. An excellent example of system
integration is how one drill manufacturer has
been helping its customers chemical plants, oil
refineries, and other process manufacturers
operate their plants more effectively by
leveraging IoT in the form of wireless drill
sensors, which can detect potential failures in
valves before they lead to a spill or shutdown.
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Handling Legacy Systems
Introducing and integrating new technologies
within well-established technical ecosystems can
bring about new data challenges. These tend to
arise not only when migrating information from
one system to another, but also when trying to
understand how older systems fit with the modern
developments. The lack of a well-defined
interface, proper documentation, and different
programming languages could be a barrier towards
smooth integration within the existing design and
manufacturing environment.
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Security Challenges
Lastly, all the systems which are interconnected
via the Internet are susceptible to data
breaches. This is not yet the case for
industrial control systems, which often have
unique protocols and limited computing power.
Many of these systems were designed and installed
at a time when industrial security was not a
prime concern. They are connected via gateways
that bridge the internet and the controlled
device 1. Still, these gateways need to be able
to handle networking and security risks and be
strong enough to avoid unauthorized access to
data.
If connected machines the primary components of
the Internet of Things (IoT) are to be the
backbone of industry in the near future,
industrial manufacturers will have to figure out
how to manage the data coming from an avalanche
of sensors, integrated equipment and platforms,
and faster information processing systems.
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An MDM solution
An MDM solution serves as a hub for the
enterprise data by integrating data from multiple
sources (including legacy systems) into a single
repository (the single source of truth) and
help manufacturers to manage data related to
products, customers, and distribution locations
by sharing it across the business. An MDM
solution works for both time-triggered and
event-triggered systems, integrates easily with
legacy systems and enables restricted access to
various user groups through data governance rules.
Read about how Top Industrial Producer uses
Riversands MDMCenter to Achieve Global
Repository Functionality Missing from Traditional
ERP and Homegrown Systems
Read 2017 Industrial Manufacturing Trends
at pwc.smh.re Reference 1 https//hbr.org/2016
/05/the-biggest-challenges-of-data-driven-manufact
uring
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Riversand is an innovative leader in Master Data
Management, powering industries from the world's
largest to SMBs. Riversand's single integrated,
scalable and robust multi-domain MDM platform
caters to a variety of use cases across multiple
verticals. In addition Riversand offers specific
solutions such as Vendor Portal, Spare Parts
Management, Material Master, GDSN on-boarding,
Media Assets Management, Print Publishing etc.
Business value which Riversand provides include
accelerated time-to-market, increased sales,
improved order accuracy, reduced costs and
enhanced customer service. Customer satisfaction
is at the heart of Riversand's innovation. For
more information, visit Riversand.com and follow
_at_RiversandMDM on Twitter.
2016 Riversand Technologies Inc. All rights
reserved.