In the previous blog, we
discussed IOT (Internet of Things) impact to consumers and challenges in data
management. This blog focus on the various industries impact of IOT and how it
is revolutionizing them. Later we also discuss the importance of applying the
data management principles for improving the outcomes.
Consumer IOT made the
significant impact by providing valuable services to customers with many smart
devices makes life easy for the users. But commercial usage of IOT adaptation
might be slow but there is a potential to disrupt and revolutionize the
industries and solve many of the business challenges they never had solutions
in the past. As shown in the visual of ice burg the Industrial/commercial
IOT is very large with many solutions
like smart sensors, smart buildings, smart factories, digital supply chains.
Industry 4.0
The world of manufacturing is going thru major
disruption and revolutions which is called as
Fourth Industry revolution.
First industry revolution which happened till
the eighteenth century where availability of steam and water. Availability of
steam provided the first mechanization of the world. Hand production methods
moved towards to machines. Textile production improved productivity, steam
machines provided better transportation . Second industry revolution started in
the early nineteenth century with innovation and adaptation of electricity and
improvement of the manufacturing process of assembly lines. This revolution
moved towards mass production of goods. Availability of transportation
facilities to provide these goods to
sell across the country or even world.
The assembly lines process managed might be a paper-based process but
still efficiently deliver product in mass scales like hundreds of cars in a
month or thousands of soup cans. The mass production process even went in the
agricultural process of invention of better seeds by GMO, drift irrigation,
supply chain to reach product in the market intern able to reach all kinds of
foods on everybody's kitchen tables.
After the invention of the
computer and software started third industrial revolution improved the
industrial engineering to next phase of improvements. Moving paper based
process into computer applications, automation of process all improved overall
performance which improved output. Automation of the production, which improved
productions worldwide and made mass production more efficient. Now the world of
manufacturing going thru next revolution. The fourth industrial revolution,
also termed Industry 4.0, is being characterized as an increasing digitization
and interconnection of value chains and business models. Industry 4.0 creates
Smart Factories and is based upon cyber-physical systems allowing the
manufacturer to control the entire production from one platform. Industry 4.0 involved achieving total
connectivity with IOT (Internet of things) which also called industry internet. Industry 4.0 makes the existing manufacturing
applications increase the complexities in very significant level which
involving adapting new machinery or changes to existing physical systems. With
the emergence of big data platforms where they can collect the massive amount
of data and as well as intelligent devices which can collect and send a large
amount of data paired together comes with the new generation of software
applications which are a lot more intelligent with least amount of human
interference.
In short, whether it is a jet
engine, turbine, commercial conveyor belts when connected with smart sensors
sends data in real time can help to track, optimize, predict what to repair,
when to repair and even when to replace. This will change how manufacturing
industries operate be supporting their large and expensive machines. For
example, GE who is known to build large Jet Engines, Turbines are looking to
digitize their operations to improve their productivity as well as their
customers. Also Electrical engines in
cars with many smart sensors taking cars close to driver-less cars.
Smarter Devices /Machines
Many
existing Machines are integrated with external IOT devices which collect a lot
of information and send to central IOT application. A smart Nest thermostat
will help to operate the HVAC systems more efficiently and also collect
information about Air conditioner performance. Next level of HVAC systems is
coming with inbuilt IOT chip which can help to operate the system, collect
health data, diagnosis and selfheal the systems. New generation turbine has built in 200 plus
sensors collect a large amount of data helps to operate more efficiently and
manage its maintenance schedule.
Whether it is Industry distribution network or
Factor Floor there will be a lot of smart sensors gathering a large amount of
information and alerts any changes significantly impact the outcome, many of
these devices can be operated over the internet thru an IPAD, kiosk or Laptop.
With all the real-time information and instructions efficiently processed could
improve processing efficiency very significantly also reduce human interaction
or manual work.
Many times in factory floor
some of the machines are critical for the production process and if any
breakdown will stop the production. When machines break down technicians want
to fix the machine with very limited data and spend a lot of time
troubleshooting to find the root cause. Due to the criticality of the machine
sometimes these are replaced even they are operating in good condition because
there is no way they know when it is time to replace. Machine replacement cycle
is based on the usage duration not the status of the machine at the current
state. But the smart machines will constantly send health diagnostics and
performance data which could help to easily identify the problems with the
machinery. Also with all the information from IOT machines can gather health
information and could even heal very trivial problems without a technical get
involved.
Smart Meters
Utility companies had the
major technological revolution by introducing smart meters which can collect
the usage data and send to the Local utility company in very real time.This
information can help to optimize the distribution of utilities and also evolve
incentives to change the usage patterns. The real-time energy usage data can
help to identify fallouts, energy loss etc.. This gives the tremendous ability
for the utility company to have more accurate energy forecast, efficient
distribution. The next level of revolution could be capturing data of various
circuit breakers to identify inefficient appliances and suggest customer on
replacing them. The smart utilities,
smart sensors, smart devices could lead to smart buildings which have higher
energy efficiency and comfortable environment for the customers. Also,
management of facilities is a lot more efficient with smarter devices around
over the Internet/Intranet.
Smart Factories
Automated process control,
real-time production monitoring, real-time integrated manufacturing and
environmental conditioning/monitoring are made possible because of IOT devices
adoption, the platform for able to consume a large amount of data and analyze (
Big data platform). Part of industry 3.0
moved many manual processes into computer applications but still managed by
Factory operators and quality control also manual process in some cases. All of
these are slowly moving to automation of business process with many health and
quality information from the machines collected, analyzed and decisions are
made in control centers. Smarter
logistics, smarter Machines/Robots, smart grids, smart buildings, smart sensors
and smarter controls (Kiosks, control center, mobile applications) are making
factories optimizing and improving productivity least amount of labor costs. In
short smart factories, revolution is fueled by IOT devices and large data
platforms.
Similarly, supply chains are
optimizing with total connectivity between suppliers, warehouse, Factory
(Production), distributors, consumers with real-time information. This helps to
move forecasting model to close to real time demand model, real-time inventory
management, accurate logistics and overall revolutionize the manufacturing and
retail industries.
Now let’s discuss about “Data Management”
With the industrial
revolutions brings the new set of software applications and a large amount of
data/information. These applications are
very different than conventional enterprise applications we are building from
last three decades. These applications connect with devices in real time and
gather information in very real time at times many gigabytes of data for every
hour. Most of these applications have high scalability, high availability,
demanding and critical business needs. When hundreds of these devices
communicate in very real-time required sub-second response times and at times
in the range of thousands of Transactions of seconds. Also, devices could be
set up in the very large geographical area so that forces to keep these IOT
applications running in cloud-based infrastructure (sometimes it could be even
on a private cloud).
The cloud-based IOT
applications also need to still connect with existing enterprise applications
(ERP, CRM, sales/marketing, customer service, etc...) and exchange data so the
IOT application operates to fulfill the customer needs. In last thirty years,
the enterprise application collected lots of data in application and current
data management methodology segregates this data into two groups, Master data,
and Transactional data. Master data
tells who is the customer, where is the location and what is the product.
Transaction data will be all the operations using customer data like customer
purchases, customer support requests, customer browsing history and much
more. In this environment, Transactional
data is typically 100 times of master data but still, master data is critical
to better understand and analyze Transactions for better business decisions.
If you look at below diagram
wherein current data ecosystem without IOT devices where current enterprise
applications focus on master and transactional data, but device usage data
never captured by the application as all those are the manual and user-driven
process. The usage data if they
collected could be the larger volume than transactional data. The usage data
might have lot more critical information to help enterprise operate
efficiently, improve the device to perform better. Before IOT there is no easy way to collect the usage
data and the industry 4.0 enabled to collect usage data and also automate the
device usage.
Data organization Before IOT
Data organization with IOT
As you could see in the
diagram of "Data Management with IOT devices" where IOT applications
are collecting the usage data will change the data management paradigm. The
usage data still need to connect with Transactional data and master data to
give the complete context of the information. The IOT device data still need to
understand the customer, location, and device.
Even smart devices will be
maturing on both hardware and software design and implementation. We all heard
of multiple generations of the same device and sometimes even have subversions
of the hardware of the same device in the usage. Similarly, there are multiple
versions of firmware exist which is communicating to the central IOT Cloud
application. To understand the
interactions between the device goods to, it is very important to know the
right hardware and software versions the device running. Next Similarly we need
to know where the device operating accurately, also who is the customer and
users of the device. The device could change locations or change the
users/customers.
All these lead to the
importance of Master data and managing it with MDM methodology and then
integrate the MDM data with Transactional and usage data. So it is important to
understand the intersection between these different elements of data and plan
enterprise echo system where all of these can co-exist.
When an enterprise already
invested in Enterprise operational systems like SAP ERP, CRM and many other
sales, marketing, customer service systems it is important to integrate with
the cloud applications and also their corresponding analytical platforms. Every
new sale, operational systems need to connect back to IOT applications. For
example, when a device gets registered first times, the device customer/user
get identified and connected to Enterprise customer master. Same time location
information also tied with the Device and customer. Whenever customer/location
changes they need to be updated in both IOT application and enterprise
applications. Enterprise applications provide support and IOT Cloud
applications should have consistent customer information related to the device.
In manufacturing plants, the devices could be
a machine in the product plant represented in ERP systems and the Information
from the device need to reflected into ERP systems so an enterprise can take
advantage of up to date latest information from the devices.
