Industry 4.0

so it all starts with the first

industrial revolution which happened in

the late 1700s and this is where

water and steam power fueled a lot of

growth in agriculture and textiles back

in the time then about 100 years later

in the late 1800s we had the second

industrial revolution and this

revolution was driven by electrification

and the advent of electricity and more

importantly the advent of modern mass

manufacturing so production lines became

more common and everything that was

enabled by electricity in the economy

that was enabled by electricity and then

finally in the 1970s is when the advent

of the computer and supercomputer really

fueled that third industrial revolution

so this is where supercomputers and

enterprise resource planning and other

sorts of technologies really started to

digitize businesses and economies

throughout the world which leads us to

industry 4.0 which is an extension of

the third industrial revolution but

certainly a big shake-up and a big

change and pivot towards where we're

headed in the future and that's what

the third industrial revolution really

laid the foundation for industry 4.0 and

the computerization digitization of

businesses throughout the world really

gave us the building blocks and the

pieces that are leading us to industry

4.0

and the key difference though with

industry 4.0 is focusing on connectivity

and tying together all this technology

and all this data that's been

accumulating over years and decades so

one of the things that's being fueled by

this connectivity are the end-to-end

business processes that is the

foundation for industry 4.0 so

internally instead of having separate

systems and silos and processes

throughout the organization industry 4.0

is really focused on how we pull

together all those business processes

and all the data and the information in

the workflows throughout the entire

internal

organization but it's not just about

internal operations that we're

connecting we're also connecting

suppliers the suppliers and vendors that

we work with making sure that we capture

data and integrate our business

processes and workflows with them and

most importantly integrating with our

customers so capturing data at the

customer level in ways that we haven't

been able to do in the past and one of

the keys to all of this integration when

we talk about the internal integration

of business processes as well as the

integration to suppliers and especially

that integration to customers

is the whole technology of devices so in

other words devices and sensors that are

capturing data throughout the entire

value chain from the customer order

through the internal operations to the

vendors as well

and some examples of devices and that

sort of connectivity that's being

created is on a manufacturing shop floor

for example you have robotics and

machines that are producing materials or

producing finished goods and their

sensors on those machines that are

capturing data about what they're

actually doing and the volume of

production the quality it's also

capturing data around potential

predictive maintenance things of that

nature

you also have on the consumer or

customer level probably the most

commonly understood device is something

like an apple watch or a wearable device

that's capturing data about me

personally and you personally every day

and that's capturing a ton of data

that's now connected to the modern

enterprise and that is a key part of

industry 4.0 is that whole connectivity

of the entire value chain technology and

data behind it as well as the devices

that enable it

one of the key components of industry

4.0 is artificial intelligence so i

mentioned before how the third

industrial revolution led us to

digitization and the capturing of data

throughout organizations and for decades

now organizations have been capturing

data but they haven't had good

information and they haven't been able

to make good use of that data for the

most part until now with industry 4.0

though we have emerging technologies

like artificial intelligence that

actually can make use of that data and

give us some predictive analytics and

some deeper understanding when it comes

to customer behavior for example and

really understanding and anticipating

what our customer needs might be and

what their purchasing decisions might

look like and what their overall

consumer behavior might look like ai can

also be used for things like predictive

maintenance so when you have machines on

the shop floor you have sensors on them

that can predict when those machines

might need to be

maintained or repaired and so it's a way

to anticipate potential problems so you

don't have to wait until they break but

you're also not investing too much money

in maintaining or repairing things that

don't necessarily need it yet so ai is a

key component of industry 4.0 and really

making organizations smarter and making

better use of the data that they already

have and also introducing new data via

some of the smart devices and sensors

in addition to connectivity internet of

things artificial intelligence some of

the other things we've talked about

there's a number of other key components

that are important to understand about

industry 4.0 first of all are the

systems and devices which we've briefly

talked about the enterprise technologies

the systems and devices on the shop

floor your suppliers your customers all

connecting

via sensors and devices that's all an

important part of industry 4.0 and a

prerequisite to realizing the benefits

of industry 4.0 in addition you also

need big data you need to have the data

that's used as an input into artificial

intelligence and some of the other smart

factory type of thinking and the smart

factory type of

functionality that we've talked about so

far so having that data captured in

systems and more importantly being able

to use that data via artificial

intelligence and other analytical tools

is very important another intangible

prerequisite to industry 4.0 is

operational and technological innovation

so in other words you as an organization

need to have a culture of innovation and

a willingness to try new things and a

willingness to think outside the box of

the way things have always operated so

it's really looking at ways that you can

use technology and operational

improvements to really leverage the full

potential of industry 4.0 and finally

and most importantly you need to have

organizational change management you

need to manage the organization through

the change because industry 4.0 is not

just about technology and process

improvements and inner connectivity

internet of things and all that stuff

i've talked about more importantly and

more than anything it's a cultural shift

it's a different way of operating as an

organization your employees are going to

be affected in pretty significant ways

more so than they've been affected by

computers in the past so it's important

to have a very solid change management

strategy in order to be successful in

your industry 4.0 initiatives

Ethical Implications

there's also a dark side and that is the

ethical implications of industry 4.0 and

some things to think about are what does

this mean to your workforce if we're

going to displace workers because we're

now automating their jobs or replacing

them with machines and sensors and data

that can do some of the work that they

were doing what does that mean to you as

an organization how are you going to

manage that change and more importantly

is that the right thing to do is that an

ethical thing to do and i think that's

something that every organization has to

answer for themselves and that's more of

a societal question as well even if

employees don't lose their jobs though

you also have the question of their

purpose if computers are doing a lot of

the jobs that humans once did and even

if that doesn't necessarily mean i lose

my job does that undermine my sense of

meaning and purpose within the

organization that's another ethical

question or dilemma that needs to be

answered and then finally it begs the

question of government regulation is

this the type of thing that should be

regulated by government does there need

to be additional safety nets does there

need to be

additional fallbacks for organizations

and individuals that might be affected

negatively by industry 4.0 so we're

still a ways out from that becoming a

reality but it is very real risk that

becomes more and more apparent over time

as more organizations move to industry

4.0

so i hope this has given you some things

to think about as you think about your

transition to industry 4.0 and if you're

going through any sort of digital or

business transformation i encourage you

to check out some of the links i've

included below including a link to our

digital transformation report which

provides best practices around how to

manage transformation within your

organization including things like

industry 4.0

How do we move those bits more effectively, more cost effectively, thinking about different patterns

and different things that we could do. So I'm happy to tell you that we've thought about this. We've launched something called adaptive ingestion

that we believe will reduce the cost of moving data to the cloud by about 70%.

And that's tested. So we've thought about this in terms of creating a warm tier where data is immediately accessible.

We still have our low latency instant access time series streaming as well for any of those. 

And we still have real time events, real time alarms . 

But a lot of your data doesn't need to move in real time. A lot of that data is there for audit purposes. It might be there for daily production max mins.

 So when we think about 15 minute interval data, we can send that data to a warm store.  We can do that 96 times a day instead of thousands of times a day. We can do all these roll-ups in the edge hanks to SiteWise Edge. We can move all that data in a very, very optimized fashion to reduce the cost overall.   And as I said, our results are around 70%,  

it was actually kind of difficult to get data back out of SiteWise if you weren't using one of our own tools. we thought harder about making sure that this is available through simple query interfaces.

So we now have a SQL-like interface that you could use to pull data from SiteWise.  this year, we've launched around 15 new enhancements to SiteWise overall.

The vast majority of equipment downtime in Toyota comes from unplanned machine breakdowns.  That's our unplanned corrective work orders up there. Where we are going, through a solid predictive maintenance system, is that we can do the correct

planned maintenance on non-production time to prevent downtime during production, increasing ROA,  and reducing downtime. So this is where AWS came in. So we had a lot of data.

 how many abnormalities are detected within a production  line.

data

That's an enormous amount of data. Unfortunately, most of it is locked down. What I mean by locked down essentially means that the data is in silos,

typically in either systems that are hermetic to external connection, so unable to extract the data, or it's simply very expensive, and takes a long time to implement a solution

we have equipment that's simply too old to be connected. So there are solutions for that as well. The point being, there's a lot of data  that resides on shop floors, but that data is not accessible in most cases. So over 90% of it being locked down.

https://www.youtube.com/watch?v=cJ4dSAUsTKg&ab_channel=AWSEvents

OPC Unified Architecture is a cross-platform, open-source, IEC62541 standard for data exchange from sensors to cloud applications developed by the OPC Foundation.

OPC Unified Architecture (OPC UA) is a machine-to-machine communication protocol used for industrial automation and developed by the OPC Foundation. The OPC UA platform in an platform-independent service-oriented architecture that integrates individual OPC Classic specifications into an extensible framework.