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Lecture – 09
Manufacturing Radar - II

(Refer Slide Time: 00:15)

Welcome back guys. We are in the second session of the technology radar for
manufacturing. Just to recap from the last session, we briefly looked at the definition
of technology radar and its components. We looked at the emerging technology radar.
We looked at the manufacturing radar. In the current session, we are going to go a
little bit deeper into each of the technology and understand as to which journey map
or how the journey map going to be.
(Refer Slide Time: 00:51)

So, the first one that I want to look at is the wait and watch. That means you know,
these are new technologies that are emerging and it has the potential to dramatically
change or impact the industry and there are certain early adapters of this technology,
people, process, standards need to be involved in that. So where does it stand is what
we are going to be looking at. Let us go into the radar companion and see what it says.
(Refer Slide Time: 01:41)

Circular economy is about is a term describing the economic model that separates the
ability to achieve economic growth from consumption of virgin natural resources.
This is based on closed-loop system and the idea is to reduce pollution and to the
extent possible, encourage the, encouraging the returning, recycling, remanufacturing
and reuse of product and materials.

It becomes very important in the manufacturing aspect of it. Let us look at some of
the trends that we see in the market. You know, like you said, this is based on the
closed-loop system that reduce pollution and to extend of life cycles, products and
materials by encouraging return, recycling, remanufacturing and reuse of products.

Now in terms of the model the people are adapting, you can see the flowchart here.
You know, normally the raw material comes in and the design is what is consuming
the raw material or gets used in the manufacturing, consumption and when during the
consumption lifecycle, there is some maintenance you may be doing that, and then
when it comes to the reuse and refurbish is another cycle that you will do.

But before you discard what we are trying to do is to figure out from the product,
which could which are the part that could be potentially reused is what we are looking
at effectively Then the recycled components feeds into the raw material part of it and
then it completes the cycle and the residual waste is the one that is going.

Now if you, you know if you want to look at the one that needs to look at the circular
economy is probably the PCB industry or electronic industry. Electronic waste is a
major problem for us and how do we make use of the raw material and then have it
sustainable is something that we need to look at it.

Whereas if you look at somebody like automobile manufacturing, they have adapted
the circular economy in a much more effective fashion and some manufacturing are
able to say that they only have 2% residual waste in the in their cycle of operations.
So, if you look at the overall picture, the data suggests that the companies are
engaging in a piecemeal convention resource and cost efficiency initiative.

They have not completely integrated all the activities together. So that is the one that
is giving the indication that you have to wait and watch in terms of standardizing so
that everybody can look into that. But whereas you know, if you look at the
manufacturer or retailer, you know they have embraced the circular economy and they
will alter their business model, operating model, value proposition, product and
service offering even is coming into a new model.

There is a link that I have given here, I do not know if it will, so there is a link that
you will be able to check out later on that is talking about how Renault has completely
achieved the circular economy in a much more effective fashion. So much for the
circular economy. It should have given you an indication of the nature of wait

It still gives you transformational benefit, how do we look at evaluating them and
build our journey map around that. Let us look at the next technology.
(Refer Slide Time: 05:57)

We call it smart assets. You know this you are probably familiar with that. So smart
assets are records of assets stored on a blockchain and a distributed ledger where the
ownership and the transfer can be managed through smart contracts and the smart
contracts is improving. The programming environment is using a framework called
solidity. That is also making very popular in the market.

So, the flow, the activity, the fulfillment, the SLAs, all these activities, will depend on
human beings to fulfill it, whereas in smart contracts, all of them happens in an
automatic fashion. Again, you know, we are saying wait and watch not because of the
technology that needs to mature, but in terms of practices that need to mature with
respect to each of the operation.

If you look at manufacturing as a whole, even within manufacturing automobile is
very different from let us say discrete manufacturing. So, the flow that we have and

the operations that we need to do, the quality control that we need to do, everything
becomes different. In order to manage that effectively, the smart contract will have to
be configured differently.

That is why that variation will happen between the industry if you will. So, what are
the different components that are affecting, in the smart contract, and that is given in
the picture on the left-hand side here. So, what you have is the predictive machine
analytics managing, managing the overall productivity of the machines here. It will be
able to tell you about failures before it happens.

So that your overall workflow is effectively managed. The industrial augmented
reality will help you to figure out about defect in a much more effective fashion and
the IoT and supply chain management will help you to improve the flow of your
manufacturing and there is this technology called cobots means that they are bots, but
they will be able to work with the human beings, variations or customization if you

They are looking at augmenting human beings efficiencies and productivity. So, they
work as well in synchronization and the modular equipment will help you to manage
your workflow and the configurations of the cobots and the computer vision will help
you to do the quality check on that and the IoT embedded system will track all the
products that you are deploying into the customer environment.

The unmanned tracks will make sure that the end user delivers it. So, if you look at
the overall flow needs to happen in a very effective fashion without much human
intervention and most of them is done by the specific value that are there in the flow
and that is managed by the smart contracts. All of these becomes very important and
in order to adapt the smart assets how do you go about doing that?

You know, that is what is given in the right-hand side. We need to do a, we need to
have a, conduct an inventory of organizational transaction, work flow, business
process and figure out what are the participating entities in that and then we need to
consider the interaction that can be encoded in simple programming rules. You know,

it could be that your assets, the delivery needs to happen within specific time maybe
within some specific temperature.

If you look at pharma, the output will have to be maintained at specific temperature
even while you know, getting shipped in the air or something like that. All of them
need to be captured within the smart contract programming and then we have to
identify the virtual assets that will play a key role for our business in the future, where
the smart as a technology can play a role.

So that becomes an important aspect as well. If you look at the blockchain per se,
there are many platforms that are available in the market. Figure out which blockchain
will be more suitable for you to implement. You know, most of the blockchain is an
open source, you will be able to use any of them. So, this is what is involved and it is
a very impactful technology,

and you will be able to use it for your productivity and efficiency. But you need to
develop skills around that to make it happen.
(Refer Slide Time: 11:35)

Let us look at some of the adapt one. This one is a very thought provocative,
imaginative, creative aspect of it. Generative design is you know, the word itself is
very provocative. The design needs to be automatically generated. Can it be done? 5,
10 years back it would have been difficult. Today, it is very easy, because there is this

AI grown technology called generative application network, adversarial network,
which is called as GAN.

It is able to figure out as to from the past design that you have, and the user
orientation that is out there, and the feedback from the customer, all of them put
together, if we are able to design it, then you probably you know, we had been doing
it manually and the person who is able to do this is called some kind of a guru in
design and things like that but interestingly using AI you will be able to do that

This is already being done by many of the CAD tools you know, such as Augmenta,
Autodesk, ESTECO, PTC. They are looking at it. It is not only in the progressive
manner, looking at all the past design, can I improve the shape? Can I improve the
material strength of it? Can it have more light if it is an architectural system that you
have? Can it be more resilient? Can I make the design more environmentally

You know like, we talked about the circular economy. Can I make the design in such
a way that we have 100% circular economy based or recommended material? All of
them becomes suddenly possible. That is why the generative design becomes such an
important one for manufacturing. That is why we are saying pilot, do a pilot on that,
and it is going to have an impact on your manufacturing.

You will be able to come up with the best possible design not necessarily you know,
they used to have another technology glyph called cloud sourcing. You know, you
look at all the global players and then they will contribute to that, using that you will
do the design, not like that. This one is more like you know, the intelligence is
gathered and it is put in the artificial intelligence framework.

It will be able to come up with a recommendation and then it can tell you about some
of the trends, some of the constraint that you have. Within that you will be able to

design your, design your solutions. So, the generative design algorithms can be multi-
disciplinary. That means you know it can have design aspect of it. It can have strength

of material aspect of it.

It can have environmental aspect of it, policy design aspect of it. It can be multiple
things. Incorporating aesthetics, cost, sustainability, function, reliability,
manufacturability, serviceability, all of them can be converged, and it can really
handle the complex wicked problem as well. I have given a link that has looked at the
various technologies and architectural solutions that are out there. When you have
some time take a look at that. Let us look at the next technology here.
(Refer Slide Time: 15:28)

If there is one technology that has been beaten to death, in the last two, three years, it
is machine learning. Machine learning is going to have impact on every other
technology that you have, every other industry that you have. But let us look at some
of the aspects and vectors around that. Machine learning is a technical discipline that
identify patterns and generate prediction based on analyzing large set of data.

There are major three sub disciplines that we have to be looking at it. You know
supervising learning, unsupervised learning, and then reinforcement learning. These
are the components that you need to be looking at it in terms of practicing it. You
need to adapt machine learning from this aspect. That is, you know, do you have a
competitive value built around the solution that you are doing?

That is very high. If you are saying that you know, I have put machine learning to use
in order to derive a particular solution or service. And that will give you a competitive
edge for you. You know and almost I would say all the vendors are looking at

machine learning as aspect. It is also based on data, it is based on audio signals, visual

and is also added with the generative adversarial network. There are several
components that are coming together in that. So, I think you know, piloting or
machine learning becomes a very important technology that you need to pilot right
now. It is more like, right now you got to adapt that. You know, that kind of a
technology is what we are looking at.
(Refer Slide Time: 17:22)

Adopt is very interesting. You know, that means that people, process, technology,
standardization, everything is mature there. You just have to look, adapt tech
technology, and start using it and that is what is adopt is about. Here, we looked at the
immersive experience, AR, VR and MR. There are some solutions that are there in the
market that are completely fascinating.

Software went through something called DevOps, development and operations
combined together and they felt you know, it can be done by one person or one
resource. Here, what is happening is sales and service can emerge together and the
answer seems to be yeah. Now what do we need and you know, let us say you know,
you want to service a part.

That means you know, you need to know what are the components of the machinery.
You need to know how to open it. You need to figure out which component is going

where. You need to disassemble it, do some service on it and do it. And all of them
very interestingly can be done using the AR.

You look at you know, something like a machine part, you know, what you see on the
right hand side, and your tablet or your mobile, if you, you can develop app or there
are some already existing app, you show that in the camera, it will show the internal
parts of the engine to you. It will tell you sequence by which you can open it up,
dislodge it, and you will be able to service this and put it.

So, interestingly you know, how do we used to do this 5, 10 years back or even year
back or even in some places now. You go through some you know, reams of manuals
and figure out which component is there, go through the standardized coding. You
need to know the standards. There are lot of paper related, reference manual related
complication is all taken away and your productivity is increased like anything in this.

This is about one aspect of the AR, the application in terms of the where it can be
applied, how it can be used is you know, typically they use only technology, you
know or technology and education where it can be effectively used. When the new
technology comes, there is always this you know, digital divide that happens in terms
of, you need to get experience about the technology.

But you need expensive technology environment to make it available for them.
Whereas if you have the AR or VR it will be able to give you the immersive
experience, hands on experience, and you will be able to internalize the knowledge
around how to make it work for you. Here again, the DDD dull, dangerous and
duplicate jobs are good targets for AR application.

Let us say you want to train somebody for a disaster recovery, work in a nuclear plant,
make them ready for, you know operational sensibilities on what to do next, and
things like that. It is not a difficult thing anymore. It used to be a complicated thing. It
is not a difficult thing anymore. So, this kind of benefits is overwhelmingly helping
everybody everywhere.

So, if you want to adapt this, what do I need to do is what is kind of you know
indicated here. Devise an integration strategy for immersive experience, which will
integrate the core experience, the incumbent application, which is you know, it could
be a PLM, QMS, MES. There are several applications that are there. It is going to
help identify feedback loops between the operator and the interaction between those

A lot more need to be gained out of the immersive experience. In all the technology
that we talked so far is all transformational benefits that you will have. So, immediate
gratification you will have if you are able to adapt the immersive technology, you
know that is what I would say and you could like I said, you know, what I have done
is only taken six technologies as example.

There are over you know, if you look at the let us look into the manufacturing part.
There are several technologies that you will see here. There are over 68 technologies
that are there and even if you had to go back to indication of how many technologies
are in the transformational realm, there are over 15 to 16 technologies that are there.

At minimum I would say you know; you need to be evaluating this. So that could be a
good journey map you could be having.
(Refer Slide Time: 22:48)

Let us look at the last part, which is the smart factory. We looked at smart assets. We
are looking at smart factory. What are the difference between them? We already know

that the smart asset is very close to distributed ledger or a blockchain technology
tightly integrated with the business flow into that.

Now, if you look at the smart factory, you know, it is more like a concept that is used
to describe application of different combination of modern technology to create hyper
flexible self-adapting manufacturing capability. Sometimes you could call it as
industry 4.0. But it is becoming more than that, you know. There is one other lecture
that I am going to be giving that is on the agile manufacturing.

That again is kind of will lean on the smart factory, because sometimes your
production could be disrupted. Your production capacity will have to be reconfigured
and remodified for a new set of product, model and design may be needed. So those
are some of the requirements around the smart factory establishment.

In order to make it happen, you know we have to do a you know, smart factory
concept role as a part of agile supply system and integrated with the connected
customer demand because when the customer demand varies your production will
have to change as well. We will see more in the agile manufacturing in a short while.
Then we have to differentiate between the Brownfield and the new Greenfield

and we have to look at the innovation as a way to make the smart factory happen and
identify the ideal technology combination that aligns smart factory with specific
segments and its supports. So as a concept, the underlying fabric will be the digital the
transformation integrated with the IoT, that is collecting the data and the Edge
analytics that is processing the data.

It is all combined into the AI fabric to help your overall manufacturing and production
capability in a much more effective and efficient fashion. These are the six important
transformational technology that we looked at. We looked at each of the categories
actually, you know wait and watch. We also looked at the adapt, and we also looked
at the pilot ones.

So, with this, you know, I am just wrapping up this session. So, to summarize, we
looked at radar as a tool. We looked at emerging technologies. We looked at
manufacturing technology and each of the radar and the companions that we have.
And then we went a little bit deeper and we looked at transformation and technology
alone. Two samples of each of wait, pilot and adapt.

We had a very good understanding I hope and when you look at this as a whole
journey, this exercise could be something like a two day workshop to figure out what
are the technologies that is going to make you more productive, more efficient, and
then be adaptive in the future environment or in disaster environment as well. Thank
you for the opportunity. Thank you.