Why we need Digitization?
Why we need
Digitization ? ….very precisely it is required to increase the overall
competitiveness of any business entity.
Digitization is the
process of turning the non-digital formats of information into digital formats.
At industrial level it is the process of capturing an analog signals and
converting them into digital signals.
During the process of
digitization the existing systems and processes stays same way and the format
of information is changed.
At industrial/ Manufacturing
level digitization is about operational efficiency of all the facilities from
end-to-end from design to build to operations to maintenance to optimization in
a closed loop so to finally optimising the complete value chain in the
plant/factory.
Challenges –
Major part of the digitization work to be done
relates to technology issues arising from the actual fact that
today’s plants aren’t highly connected yet. These include:
• lack of strategy for coping with legacy systems and equipment;
• limited availability of machine health data; and
• complexity of potential solution space (where to focus).
• The other leading hurdles don't seem to be about technology, but relate to normal business issues:
• lack of budget;
• management vision and buy-in; and
• ROI or business case for digital transformation.
• lack of strategy for coping with legacy systems and equipment;
• limited availability of machine health data; and
• complexity of potential solution space (where to focus).
• The other leading hurdles don't seem to be about technology, but relate to normal business issues:
• lack of budget;
• management vision and buy-in; and
• ROI or business case for digital transformation.
Digitization is
all about transforming manufacturing operations using the foremost
recent technology and it often starts with connecting factory floor
equipment. -
·
Increase productivity and reduce downtime
In this case data analytics changes things – when a digital layer is added over the present equipment, it start generating data in real time. After feeding this data into an analytics solution, a real-time view of how efficiently the shop floor is functioning may be taken for instance which sections are lying idle or consuming more power than they must.
One can deploy preventive measures and eventually predictive measures. These measures prevent unplanned downtime, hence preventing losses. In effect, they make sure that the equipment effectiveness is higher as a result increases productivity.
·
Tracking resources, material and other people
Most important advantage of digitisation is that the automated tracking of resources, material and other people. An outsized number of manufacturers are already using basic RFID technology which ensures both productivity and safety but there is much more to it.
·
Unification
of industrial security for IT and OT applications
It is critical for manufacturing
plants to unify the safety surrounding their physical and virtual assets,
similarly as their reputation and privacy. A piecemeal approach to security is
not any longer effective. So additionally to protecting their IP, it is vital
that their security infrastructure covers plant assets and production integrity
too with security products, technologies and solutions that are common to both.
This unification will make sure that approach to security with relevance IT and
operational technology (OT) is over-arching and not an afterthought.
·
Developing a digital
specification for the shop floor
Connectivity and IoT: the employment of Technology in manufacturing has grown haphazardly within
the past for many reasons so networks aren't properly designed, which
successively ends up in downtime. On the shop floor, downtime implies huge
losses to the highest and bottom lines. Hence a sound digital
foundation/network infrastructure connecting all assets and machines is the
inspiration of a digitised workplace.
Analytics: the knowledge data generated
from the shop floor, i.e., the whole set of machines using various tools,
controllers and sensors can then be extracted, filtered and analysed. An
analytics layer helps interpret the analysed data to produce real-time insights
to assist real-time higher cognitive process. What’s important to notice is
that doing this doesn't mean that each one old machines have to be replaced;
rather it ensures that there's data flowing in even from these machines by
adding the correct set of sensors, controllers, etc.
For more information visit here:- https://reckersmech.com/variant-management-in-north-india/
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