Leading
firms in automotive and manufacturing have deployed predictive simulation
models to ask and answer major business process change and new technology
investment questions for decades. Unlike many other predictive analytics
technologies, predictive simulation has been deployed at scale for many years
by these firms and has been embedded as business as usual by many for major
capital expenditure decisions. Many less structured firms have avoided using
such technologies, preferring to rely on experience and intuition; however,
time is fast running out for gut-feel management as operations become more
complex, connected and agile.
The implementation
of Industry 4.0 naturally generates similar opportunities, risks and business
questions to the implementation of new technologies in the past. It’s therefore
reassuring to know that well-proven software technology is available that can
provide a highly visual predictive model of your business and gage the impact
of different implementation options. By capturing your business logic, rules,
assets and processes within a digital model, businesses can access a visually
rich and statistically accurate method for testing their investment options and
future changes across their organisation.
These
models are able to simplify complex operational behaviours. The future-state
data they provide is ideal for empowering clearer planning decisions, building
comprehensive cost justifications and managing many of the risks associated
with change. For these reasons alone predictive simulation offers an ideal
starting point when considering investments in digital transformation through
the application of Industry 4.0 technologies.
For
many, a real value-add from a predictive simulation model is its ability to
understand the complex dynamics of the current-state business before moving
towards full digitisation. Capturing
processes and data in a visual, dynamic model secures the cross-functional
engagement needed to establish effective strategic alternative investment
options. As investments in new Industry
4.0 technologies are made, the data driving such models can be refined via
operational data sources such as those provided by modern equipment and
real-time data sensors. As the level of digitisation progresses the model can
hook into increasingly accurate and timely data flows providing both enhanced
predictions based on business plans but also a real-time ‘digital twin’
representation of current operations and schedules.
A
predictive digital twin is capable of showing the current state of the business
across different media, offering management a view of the business that
surpasses traditional reports. Options include 3D visualisation, augmented and
virtual reality and dashboards that not only show key performance indicators, but
allow individual points of interest to be examined in detail, drilling down
into deep business data. Such dashboards can use predictive data to alert when
and where potential future problems may occur. Using the right Industry 4.0
technologies, they can even provide the controls necessary to invoke remedial
action. This form of dashboard will increasingly become the digital control
panel or ‘predictive management cockpit’ for tomorrow’s operations managers.
Hayward Tyler, a
designer and manufacturer of mission critical pumps and motors, used this
technology to create a digital twin of their manufacturing facility. This award
winning approach demonstrated how the factory would operate before it was even
constructed and validated the development of a new carrier transportation,
designed specifically to improve throughput throughout the facility. The
predictive simulation technology is currently being developed to improve
production scheduling capability to keep customers informed of when they can
expect to receive their orders.
This post has been written by Andrew Aitken, COO, Lanner who are exhibiting at Subcon 6-8 June at the NEC. Register now for a free visitor pass at www.subconshow.co.uk
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