Impact of Industrial Analytics in Fostering Manufacturing Transformation

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Impact of Industrial Analytics in Fostering
Manufacturing Transformation
If data is oil, manufacturing is the brightest
lamp powered from it. Manufacturing is expected
to generate 1812 Petabytes (PB) of data every
year, a lot more than BFSI, healthcare many
other industries, according to Deloitte.
Industrial Analytics today are helping optimize
every facet of manufacturing by enabling
proactive decision making automation across
organizations through the access of the right
data to the right people on time.
What does Industrial Analytics exactly
do? Industrial Analytics Definition Industrial
Analytics collects, analyses, and uses data
generated in industrial operations through
machines, processes, and people. Traditionally
Manufacturers have always been using data to
improve their efficiency machine health for
years. But what has changed now with technologies
like IoT is how the data is captured. In the
past, data collection was done manually, with
plant operators recording data or feeding it in
a machine. But these approaches are flawed- they
are time-consuming and prone to human errors and
biases. This data is still grassroots and not
actionable for decision-making, particularly at
a senior level. With digital transformation, tons
of strategically placed sensors capture every
critical machine data, recorded and analyzed in
real-time. The level of insights that emerge is
actionable for every level. Here is how
industrial analytics is transforming various use
cases in manufacturing, improving the efficiency
and productivity of machines, processes people
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Improving Manufacturing Supply Chain In a
hyperconnected world, manufacturing processes and
supply chains are getting increasingly extensive
and complicated. Industrial Analytics enable
manufacturers to hone in on every stage of the
manufacturing process and study supply chains in
minute detail, accounting for individual
activities and tasks. Based on machine health,
inventory status, forecasting of orders,
preparation, and choice of suppliers can be made
in advance. In the current scenario of a
dynamically changing environment, a resilient
supply chain can make or break your enterprise.
IReduce Downtime Manufacturers can extend the
life of critical assets by using data to predict
when they will fail. Predictive maintenance
systems today collect past data to produce
insights that arent visible using traditional
methods. For example, companies may utilize
industrial analytics to identify the conditions
that may cause a machine to malfunction and
monitor input parameters to act before the
equipment breaks or be prepared to replace it
when it does, reducing downtime. Factors like
Misaligned shafts, lubricant oil contamination
and excessive vibrations can result in unplanned
downtime if not controlled in time. Technologies
like Infinite Uptimes IDAP can allow plant
managers to track these in real-time and predict
anomalies with a prescribed solution, effectively
minimizing planned and unplanned
downtime. Since machine downtime can cause a
loss of around 260,000 an hour per hour for a
manufacturing company, this is one of the most
critical use cases for industrial analytics.
To Know more about Impact of Industrial
Analytics https//www.infinite-uptime.com/impact-
of-industrial-analytics-in-fostering-manufacturing
-transformation/