Whenever I ask people “in one word tell me what BIM is all about”, coordination always makes its way in there. I do remember up until 2004 (when my role shifted) I actually carried out coordination as part of my day to day activities of design and configuration. It never occurred to me to work otherwise. Why do abortive work when it can be avoided? Reference other disciplines into your working environment, design, analyse, configure, avoid and flag items of doubt/priority for discussion. Admittedly this was primarily in 2D at the time and elements of 3D. I was not alone in this, my colleagues did the same. So what has happened in our industry? Why do we wait until a point in time to “coordinate” and flag 10/100/1000s of errors when we could be eliminating a few at a time as we work! That is why I still cough and splutter when I see it left as a secondary activity.

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A New Chapter

So it has been a while but I may well get back into this blogging lark. Time will tell. So a bit of a change going from BIM to Information Management (IM), or is it? We shall have to just wait and see. After 5 and a half years away from design it does feel like “coming home” but also with a new view of the world and a different way of engaging, improving and transforming. So raise a glass or two to the future, it’s so bright you gotta wear shades.

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Autodesk University Moscow Keynote

Risk is that we ignore trends and our competitors don’t. Trends

* Growth of cloud computing

* Digital everything

* Machine learning
35th Anniversary of Autodesk and autocad. 
What do we do with cloud/infinite computing. 

Generative design for the mass market. 20-30k compute nodes.

Sending to manufacture will be as common as send to print. 

As designed will be as built. 
Digital manufacture. 

Robots on site. 

Automotive. Everyone worries about tesla. Redefine the value proposition. New relationship with the car. 
We want intelligent connected devices. Smarter and better over time. 

Smart bridge. 320 sensors. Photo catalytic concrete. 

Boeing 787. 3D printed titanium parts. If you can pass rigorous aviation standards then you can do anything. 

Varma 12 Norwegian hydro plant renovation. 

Used dynamo. Drones for construction monitoring. 

Rotterdam ram lab 3D printed propellor plus 5 axis Cnc. 

Point of need manufacturing. 

Guess 2 poweplant in moscow. RPBW. 

Apes project bureau

Use smock stacks to bring in air. 
Teach an algorithm the essence of a thing and it can then iterate it. 

Ash the robot has eyes. Learns and progressively adapts. 

Designed built and monitored by machine in Dutch bridge. 
The next big platform is data. 

The age of AI and generative design. 
Tom wujek

Explore emergent tech 


Technology will become active creative partners. 

Industrial Age the fuel was coal. Data is the new commodity. The cloud is the pipeline. 

Capture, compute and create. 

Designs will become fluid and agile. 

Generative design define the problem, constraints and goals. 

Empowerment of the novice. 

Turned people into a source of data for generative design. Autodesk Toronto office. 

From directive to adaptive. 
Robotic systems 

Robots are dumb, dangerous, blind and expensive. 

More money in H&S around the robot rather than the robot itself. 

Ash can weld in 3D. 

3d space and enter the robots world. 

Robot called She. 
Addative manufacturing 

Visarium mold for airbus panel design. 

Inspectable into inscrutable structures. 
Our tools are creating a black box. Less understandable does not mean unreliable. 

Moving from if then statements to in depth knowledge/insightful. Looking outwards into the world. 
Robots can see and learn and deal with the mess and complexity of the world. 

Replace the real world with a simulation where the machine can learn at computer speed and not real,world. 

Within hours bishop learned a lifetime of knowledge. Once bishop knows all the robots know. 

Gets the gist and then re-applies that knowledge to other materials. 
Maya fluid simulation tool. 

Trained maya with machine learning using image recognition to produce effects. 

Novice to expert in a very short period of time.

From calculation to intuition. 
Project IQ as part of BIM360

Predictive data base for site. 

Type in but now moving to image recognition. 

Looking at project management forwards. 

Moving from recipe to reasoning.
In order for self driving cars to work you have to let go of the wheel. 

Computation power double every year eventually every 6 months. 

Not only represent our ideas but for machines to understand our ideas. 
Machines will possess Insight, expertise, knows industry and knows business. 
What should the next generation of tools look like?

Wealth of expertise. 

Long hours after I went home. 

Explore more design solutions. 

Learn and get better over time. 
What might the Autodesk echo look like?

The future is always closer than you think. 

Innovate. Open platforms. Force for positive change. 

Fusion 360. BIM 360 and shotgun. 

Forge – open. Cloud based api for micro services. 

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BIM and “For Information”.

Hello there readers (I am sure there are a few of you left).

Something that always makes me smile is when “things” are issued for information. What exactly does that mean? Rather than explore that here I will make two quick observations.

  1. In BS1192:2007+A2:2016, graphical models are the only data type that CANNOT be issued “for information”. See table 5, S2 status does not apply to graphical models.
  2. Secondly, if it us just “for information”  are we are saying the recipient is going to charge the client to rebuild the model?
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@BIMShowLive 2017 ‘Auf Wiedersehen, BIM – an International Perspective

‘Auf Wiedersehen, BIM – an International PerspectiveAcross the globe data is becoming a critical raw material of the modern construction organisation turning that into meaningful insight will drive a new wave of sector innovation.
As we enter a new cognitive era of construction there are many questions that need answered:
• How will AI and machine learning impact on construction?
• Is there a growing need for under understanding and reasoning and insight based on an industry awash with data?
• What will machines learning to scan huge amounts of data to predict costs and get clients best deals – mean to the professions?
From BIM mandates to supplier innovation we are witnessing digital disruption on a worldwide scale. This presentation will examine the key issues of improved functionality to the existing BIM value proposition and show how this is manifesting across the globe.
Case studies will be referenced especially from Australia and New Zealand including who Transport for New South Wales (TfNSW) are and why are they spending AU$11Bn/yr. on infrastructure
– the TfNSW Digital Engineering Scoping Study:
– Capability and Capacity
– Information Requirements
– Processes and Procedures
– Standards
– Technology
– Impact on supply chain across Australia and government approach to DE/BIM
– I3<;. AECOM’s new Information Management service:
– overview, genesis, market plays, project examples (Denver Airport, Sydney Opera House)
– Summary thoughts on future of industry – Construction 4.0
Speaker: Steve Appleby, AECOMVIEW BIOG<;
BIM being the precursor to construction 4.0

Australia – the lucky country


The BIM intelligence tool – periscope

Forge to get models online. 

Digitised the Australian health guidance through dynamo and linking to client requirements 

The digitisation of the construction sector is global and not always called BIM. 

Digitisation of the asset strategy. 

Smart ICT for infrastructure report in Australia. 49 submissions. 


Clients talking LOD is not helpful as it’s a lazy approach but it’s a start. Likewise setting project value on when to do BIM. 

National BIM guidelines and BMP. Natspec

NZ have the BIM acceleration comittiee. Only really 2 number tier 1 contractors. 

New Zealand BIM handbook. 

Transport for New South Wales. Committed spend of 10bn per year for next four years. 

They want to be leaders in this space. 


More of a focus on digital engineering. 

Planning, design and delivery of data. 

Healthy start team go out and help the supply chain to get going. 
i3 – information – intelligence – integration 

PLQs are answered by pulling together multiple elements of data from different systems. 

Digital asset performance management. 

Repair before fail. 

Capture and use data to improve customer outcomes. 

Network view – asset view – model view 


6 man data and analytics team in Perth. 

Syndney opera house managers want to leave a legacy. 

Dedicated inhouse modelling team.


Continuous commissioning 

Performance tuning and predictive maintenance 

L3 realtime data exchanges?

IBM Watson analytics 

Lifecycle data science

Cognitive asset management

Optimisation of operational delivery. 

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@BIMShowLive 2017 “Let’s Get Judgmental” – Analyzing & processing Revit Projects for automated output & validation of COBie data

“Let’s Get Judgmental” – Analyzing & processing Revit Projects for automated output & validation of COBie dataThis session will present how real-life architectural projects have used Dynamo Studio to accelerate time consuming challenges like model maintenance/auditing Revit models, verify the data and preparing it for COBie export.
We will explore how Dynamo Studio can automatically create valuable project reports and export them to Excel and Power BI. For example creating reports of elements which have not been modelled to best practice, flagging them in the model to streamline corrective actions.
We will also touch on some limitations of Revit dealing with warnings and automated workarounds to help correcting them.
Finally, I will demonstrate ways to check your data before exporting for information exchanges and creation of COBie data.
Speaker: Thorsten Strathaus, Flanagan LawrenceVIEW BIOG<;
COBie is an information structure and IFC THE model file exchange format. It’s a container and everyone knows how to work with containers. 

the operations piece is still missing from the construction strategy

A matured client might look at a building in a different way. 

Three bits of simple data. Where it came from. How long it will last and how much to replace. 

But then you want to be able to further classify to help analyse. Type and name. 

Designers didn’t study at uni to fill in cobie spreadsheets 


Spanner in the works. Duplicates and overlaps. Wrong number and wrong metrics. 

Revit warnings are tracked at an office level monthly. 

Warnings are grouped and ordered by risk. 

Using dynamo to feed the warnings back into revit to create views to remedial purposes. 

A piece of information can be used up to 200 times from creation into operation. 

Part M analysis. Diagram 12. 

Two uniclass codes. Product and system. 

Autodesk cobie extension for revit doesn’t work properly with standard fields and you have to move this data to the right fields. 42 values on 4 sheets. 

Only a few values from the trades. (6)

Parameter name mapping to get the revit parameter into the cobie field using dynamo. 

Using power BI after 90 minutes to analyse the data and drill down. 

Right data and right time for the right people. 

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@BIMShowLive 2017 opening address and keynote

Chairs Opening AddressSpeaker: Simon Rawlinson, VIEW BIOG
Have we been doing the right thing? Construction leadership council is focused on digital, manufacturing and performance. (In that order)
We are challenged by the complexity of what we do. We have to be able to explain things in the language of an infant and to be able to enthuse your audience so that they engage and want to get in board. 
What are the consequences of bringing together data and digital for our industry. 
Keynote – Nell Watson

Speaker: Nell Watson, VIEW BIOG
 Building a better world with machine intelligence. 

Child minds increase in complexity by 2% per day. 

Brain parts – reptile – mammal – frontal cortxt. 

Two systems. Dual process theory. 

System 1 makes assumptions about the world. 

Machines lack the capacity to make reasonable assumptions. 

Learning through teaching/structured, play/unstructured and reinforcement. 

Convolutional neural networks

Singularity university

Aipoly app for the blind for shape recognition

Most of the algorithms are 20 years old but the training data has only been available in the last 3 years

Any process that a human can do in a 1 second loop can be done by machines. 

Intuitive intelligence is now a utility. 

Big data – knowledge – experience – creativity. 

Company – automated insights

#neuraldoodle to synthesised image

Magic pony technology

Virtual realms for a full fat world 

Predicted sound

Interactive dynamic video. 

Crot spot

How machines can protect our world. 

For the time bring it makes sense to keep the human and the machine together. 

Machines can learn from other machines. Autonomous cars learn collectively from other autonomous cars. 

Machines learn in both the real world and virtual world. 

Ubiquitous intelligence. 

There is more computational power in the bit coin hash network than the top 500 supercomputers. 

Swarm intelligence within the buildings trying to understand their users. 

Flip side being security of such power. 

Hacking of control systems. 

The new age of the machine payable web. Machines will be paying for things on your behalf as well as earning money on your behalf. 

Your autonomous car could uber on your behalf when you don’t need it. 

Anticipatory design. Netflix. Nest. Pandora. “No thinking”

Pinterest algorithm for finding objects in photos. 

Generative design. 

Computer optimised design than can only have been created/invented by machines. 

Design by financial return. 

Design by style and generative design. We go from creator to curator of machine made content. 

We don’t know who is going to win Web 3.0

Appeal to bots may have more leverage that appeal to humans. 

These agents are beginning to understand us. Personality insights. 

USC institute for creative technologies simsensei

All the hard things are solved. The soft stuff, not so. 

Intelligent machines that truly understand us, help us, do things on our behalf. The best of man and machine working together. 

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