Smart Facilities Management With Intelligent Digital Twins

Smart Facilities Management with Intelligent Digital Twins

🔍 Overview: In this video, we provide an in-depth introduction to the world of Smart Facilities Management using Intelligent Digital...

Transcript

Smart Facilities Management with Intelligent Digital Twins

🔍 Overview: In this video, we provide an in-depth introduction to the world of Smart Facilities Management using Intelligent Digital... this is just a quick introduction to

Smart facilities management using

intelligent digital Twins and it will

give you a common operating picture that

puts you in control

when we talk to

asset managers and Facility Owners we

hear some of the challenges that they

see is really around asset monitoring

prioritizing repairs budget constraints

emergencies and unplanned events

trying to coordinate with other

departments vandalism public misuse

Regulatory Compliance technology

integration vendor and contract

management

public engagement and and feedback staff

training and management and also

environmental concerns so quite a

complex set of challenges that

facilities managers are trying to

address and digital twins help in some

way to address some of this so some of

the typical applications or use cases

and these are this is just a few

examples

that digital twins are being applied to

in facilities management is really

around predictive maintenance for

infrastructure helping with asset

monitoring and prioritizing repairs

having sensors there it can predict when

assets May Fail and it can use all sorts

of algorithms and things like that we'll

we'll dive a little bit deeper into it

and I'll show you some examples of how

it does it

another application area or use cases

around resource optimization and

budgeting really helping with budget

constraints which quite often is one of

the bigger challenges for facilities

compared to other Industries

we also deal quite often with things

like Disaster Response and recovery from

that so knowing when certain certain

events and emergencies unplanned events

happen and what can be done

even with that operations intelligence

real-time intelligence getting that

common operating picture knowing what to

do next

the other key challenge that we that we

address with digital twins is

integration to other external systems

and quite often there's a whole bunch of

departments in different silos they're

done really well work well together and

it's one of the benefits that a digital

twin can bring is being able to

integrate that so for example of a

rainwater main breaks always predicted

to to to break then that information can

be relayed to things like traffic and

traffic Management systems and other

applications and and systems that are in

the organization

and quite often the influence of the

public and trying to keep them involved

as well as updated is one of the key use

cases that again is slightly different

in Facilities Management to what we see

in some of the other Industries now

this is all around very specific use

cases and if we come from a controller

automation engineering background

you should be familiar with this ISO 95

model which is kind of the Purdue model

or how we control have controllers and

things in the plant and throughout our

our facilities and how that rolls up

into skyde systems and the different

Management Systems so those are

typically referred to as

distributed control systems and

Facilities Management they vary

depending on what the type of

infrastructure it is that you are trying

to manage so if you go to pump water

filtration plants pumping stations more

sophisticated than what you find in some

of the

recreational Services areas like parks

and some of the others but what we've

done is we've taken that same picture

and kind of flipped it over and said so

what what does a digital twin provide

for you if you've got a distributed

um control system on the one hand this

gives you a distributed intelligence

system by using all of these different

use cases and that's the main difference

between having a digital twin and just

have for those previous few use cases

that I showed just have some point

solutions that that work in isolation

what you can now do is at your

facilities level at the at the plant

level you can have multiple different

use cases

and again we'll touch on on some of them

I'll show you examples of that but we

can start rolling them up integrating a

more compa

composite one that gives us a better

tactical view so this might be

operational at the lower level getting

to a more of a tactical view at the next

level

and then being able to bring in business

logic business rules

and models at a

at a higher level which will give us the

ability to create this control tower now

if we combine the two we actually get a

new level a strategic level and that's

the common operating picture or this

executive control tower that gives us

the opportunity to to make better

decisions even though at level one where

the digital twin operate its use case is

still very specific like we saw in the

previous example where or the the

previous slide where we it's

specifically around certain asset

maintenance or event response or those

but it's the combination of being able

to bring all of that together it's a

real benefit of the digital twin

and now you also have some levers that

you can pull depending on budget States

or some other uh

operational or strategic levers that you

may have you can change some of the

business rules and that will influence

how these digital Twins then behave so

can we spend more money on predictive

maintenance

what is the situation with our staffing

in terms of resources and and that kind

of thing

so this is the real opportunity with

digital twins being able to create this

common operating picture by stringing

together or building it up from multiple

different use cases so the core Focus

for Us is around the use case and the

way that we like to do this in practice

how do we actually build this is to

create this common operating picture

you've got the assets on the left hand

side and then we have this capability

which we call data stream designer that

can suck information from multiple

different systems

and it can transform it it can apply

some analytics to it and we can then

create some actions coming out of that

we can also bring in things like AI into

this and I'll be showing you some

examples of what this looks like in an

actual application

um for predictive maintenance

you don't always have to have the AI

side of it sometimes we just have

engineering calculations thresholds

those kind of things more condition

monitoring but as we move to predictive

maintenance and predictive use cases

predictive operations

we start bringing in more AI

the XM Pro app designer is the third

element so this is the visualization and

this visualization is not there to

replace existing 3D GIS models or Point

scans and things that we've done or

Bim models or that it is really taking

those and actually using some of those

user interfaces like Gia systems and

putting the contextual information

around it with the recommendations which

is the next step that's actually what

you really want to in certain events

occur or likely to occur

you want to create a recommendation for

someone to do something it might be to

investigate it it might be to repair it

it might be to

discard it it doesn't matter what it

what the what the outcome is different

scenarios will have different outcomes

but how can we make sure that we have

consistency around what the recommended

action is so that we can Empower people

processes and provide some automation

around this as we go forward

around certain areas or outcomes in our

operations

a little bit more sophisticated version

of the same common number writing

pictures I've got all of these things on

the left hand side senses I've got all

of these systems inside my organization

and I'm trying to get the response done

with people processes and automation

and what we do we have this

user interface where we can in a visual

way build the data streams again get

data from multiple different systems

apply analytics to it provide context to

it so not only do I can I bring in

sensor data but I can bring in

maintenance records I can bring in

weather data I can bring in all sorts of

data and build a for my specific problem

a a data stream that will feed and give

me the the information that I need

to create a common operating picture and

in this common operating picture you can

see at the operational level at the

bottom the Tactical level which is the

planning level and the Strategic level

everyone's looking at the same data but

through a different lens for different

reasons for different things that I want

to see at the top it's more kpis

at the middle level it's more on

planning when we have when do we have

multiple things

in the workshop at the same time and

we're over capacity so we can't actually

deal with that and at the bottom you

know looking at the actual facility and

while I'm there what's happening

um do it but it's all the same data and

this is what we call event intelligence

and now when certain events occur

based on the real-time data

we can turn that into operations

intelligence for for the decision

support and if we combine that with

recommendations which is a key element

of our solution

through our recommendation manager and

recommendation rules

that can also bring in from other alarms

and alerts and things that you may have

in the organization but at this at the

highest level and at the lowest level it

all works the same and you can combine

all sorts of different systems to create

a set of recommendation rules and I'll

be showing you what that looks like

it enables you to empower the smartest

people in your business to pull the

levers as I mentioned earlier

it will reduce the risk of being

blindsided by key business events that

are happening or likely to happen and it

also improves the accountability because

you now create a feedback loop a closed

loop feedback system

so that you have the visibility around

you know always getting better are we

closing the work orders you know

is the facility running better so you

can create those closed loop monitoring

capability that also improves the

accountability for that

as you can see we've got some elements

in terms of what is in excellent Pro

um so we call that our intelligent

digital twin Suite consists of four

different areas the data stream designer

AI the app designer and the

recommendation manager and before we go

into that I'd like to highlight uh

something that we quite often see when

we talk about digital twins people just

see the visualization part they see this

really nice

digital twin user experience that has

got dashboards it's got bi it's got 3D

it's got IR VR all sorts of really nice

looking visual interaction the challenge

with that is uh

that that is just the visualization

like this Iceberg the real challenge 80

of the work sit below the surface and

that is where you need to make sure that

it's safe secure reliable that it's

trustworthy you need to be able to

integrate all these different systems

and then Wrangle that data provide

analytics over that being able to bring

in things like AI that it's not just

Standalone but it's that it's baked into

the business process and then creating

these recommendations that can run on

top of that that is all the things that

are required to actually build a

successful digital twin at the end of

the day it's not just about the user

interface that sits at the top

and what we're starting to see in some

instances we don't even need a user

interface because we can automate the

whole process

for those tedious things that you

actually don't want a human to

to get involved with so what I'll be

doing next is taking you through an

example we'll just take the predictive

maintenance for infrastructure

and looking at a facility management

um

application at a very high level in

terms of how we how we address that

specific challenge now for us from a

smart Asset Management point of view it

is really how do we connect to the data

how do we provide the recommendations

and alerts for the planning team so be

able to to plan work then actually

create the work orders work requests

into the backend systems that you may

already have

and um

augment that with additional information

so that it's not just this things like

safety information additional context

operational information that you can

actually pass on to that work ordering

request to make it more rich and then

also checking or verifying that the work

has been done so for us that's the

closed loop process that we like to

follow around smartassive management

and in terms of use cases for facilities

management we see applications around

condition monitoring prescriptive

maintenance predictive maintenance

machine intelligence this is where we're

getting to move the real-time

operational side of things or autonomous

operations

and from a talk from a technology aspect

it uses things what we call composable

so we can make reusable blocks so we

don't have to build it every single time

make some really smart integration

automate some of the business process

areas of that and we try to do all of

this in a no code application

development which environment which I'll

show you so that you don't have to code

the stuff

and lastly the real objective of this is

that you can

reduce downtime increase the asset life

and the cost that you have around it but

we also see more and more that there's

emphasis on the ESG side of things the

environmental societal and government uh

the the the the governance requirements

so that is the objective of of using

digital twins to help you with smart

Asset Management now before we go into

the example and also just take a a brief

minute to explain how we often see the

journey happens because

you may have so many different things

that you could potentially do and one of

the approaches is to look at from a

for the predictive maintenance condition

monitoring prescriptive maintenance type

use cases is to go and look at or

analyze who are The Bad actors and what

percentage of impact do they have so you

can see the size of the block they

represent that I can also then look for

a certain bad actor maybe say it's in

the pump stations and certain

centrifugal pumps I can look at the type

of failure modes that they have you know

the bearing failure see all failures

um whatever it may be and then for those

failure modes trying to understand what

the root causes are

and the reason why that why we want to

have the root cause is that we know what

to look for so what are the lead

indicators that tell us something is

causing so which will cause a certain

failure and that results in the bad

actor

so now that we understand what the root

causes are and what and the the this is

really the bread and butter of a lot of

Maintenance organizations that we have

right or the the work that we see being

done right now

so understanding what the root causes

are

and then look for what are the lead

indicators for that root cause so is it

the is it the the

plan maintenance history the tonnage the

motor arms the vibration the flow the

whatever the lead indicators are and

that from what systems do we need to

bring them so that we can create these

rules either rule-based AI based

the person who's been there 30 years and

also applying some engineering

calculations because most of the things

that we do still subscribe to the lower

laws of physics so we can use our

engineering calculations to do that so

that's just some other approach that we

take but to get back to how the software

worked led me jump in and briefly show

you so I'm going to start with with

again with this picture we have the data

stream designer

um and that gives us the ability to

embed AI as well the visualization

aspect is in the app designer and we

have the recommendation manager that

drives it I will start with the app

designer number three the the user

interface so if you recall our

tip of the iceberg I'll start with the

application designer show you what the

what or how we

the the the the the the information the

interaction and then I'll show you

behind the scenes below the water line

how we do this