Thinking About the Future of Complex

Technological Systems: Which

Technologies Should Shape their Designs?

Jeffrey L Funk

Division of Engineering and Technology Management

National University of Singapore

Presented at the 1st Asia-Pacific Conference on

Complex System Design and Management

Different Technologies have Different

Annual Rates of Improvement

0

5

10

15

20

25

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 >42

Number of Technologies by Annual Rates of Improvement

Annual Rates of Improvement

Source: Nagy B, Farmer D, Bui Q, Trancik J 2013. Statistical Basis for Predicting Technological Progress. PLoS ONE 8(2): e52669. doi:10.1371/journal.pone.0052669NREL, 2013

67%: <9% per year

89%: <15% per year

How Should this Impact on the Design of

Complex Systems?

Complex systems are expected to last many decades, if not longer

They are composed of many technologies, often with different

rates of improvement

Rates of improvement impact on the tradeoffs inherent in

complex systems; tradeoffs between

different component technologies

cost and performance in an overall system

If the rates of improvement are rapid, the tradeoffs, i.e.,

economics, will change in a few years and even more so in a few

decades!

How Should this Impact on the Design of

Complex Systems? (2)

Rapid changes also enable new forms of designs

at the system and sub-system levels

complex systems should be flexible to accommodate such changes

But to design such flexibility, we must understand rates of

improvement and the potential changes that they might bring

But many ignore rates of improvement

Universities rarely discuss them, including sustainability courses

Inter-Governmental Panel on Climate Change emphasizes wind turbines

even as their reports claim rate of improvement is 2% per year over last

30 years

How can we Better Understand and Analyze

Potential Changes in System Design?

Understanding potential changes is like predicting the future

Which is obviously very difficult

These difficulties are compounded by cognitive biases (Nobel

Laureate, Daniel Kahneman)

People assess relative importance of issues, including new technologies

by ease of retrieving from memory

largely determined by what they see, read, and hear

Second, judgments and decisions are guided directly by feelings

of liking and disliking

Many people “like” some technologies and dislike others for emotional

and not logical reasons

Isn’t there a more deliberate and logical way?

Understanding rates of improvement can help us better understand when

new types of system designs might become economically feasible

Technologies must have some level of performance and price for

specific applications before they become economically feasible

Technologies that experience faster rates of improvement are more likely to

become economically feasible….

They are also more likely to become economically feasible for increasing number

of applications and thus diffuse…

And, they are more likely to impact on higher-level systems

But which technologies are experiencing rapid rates of improvement and

why?

Methodology

We used time series data that are reported in

scientific and engineering journals such as Nature, Science, Phys Status

Solidi and IEEE

annual reports by reputable scientific organizations such as International

Solid State Circuits Conference

archival social science publications

general technology and technology-specific web sites

Most data are from single sources and often single figures

Data was collected on multiple dimensions when possible

Data are for best laboratory results, commercialized products, and

some combinations of these two

Technologies Experiencing Rapid Rates of Improvements

(Information Transformation)

Technology Dimensions of measure Time Period Rate Per YearIntegrated Circuits Number of transistors per chip 1971-2011 38%

MEMS Number of Electrodes per Eye 2002-2013 46%

Drops per second for printer 1985-2009 61%

Organic Transistors Mobility 1994-2007 101%

Power ICs Current Density 1993-2012 16%

Carbon Nanotube

Transistors

1/Purity (% metallic) 1999-2011 32%

Density (per micrometer) 2006-2011 357%

Superconducting

Josephson Junctions

1/Clock period 1990-2010 20%

1/Bit energy 1990-2010 10%

Qubit Lifetimes 1999-2012 142%

Bits per Qubit lifetime 2005-2013 137%

Photonics Number of Optical Channels 1983-2011 39%

Computers Instructions per unit time 1979-2009 36%

Instructions per time and dollar 1979-2009 52%

Quantum Computers Number of Qubits 2002-2012 107%

Technologies Experiencing Rapid Rates of Improvements

(Information Storage)

Technology Dimensions of

measure

Time Period Rate per Year

Magnetic Storage Recording density

(disks)

1991-2011 56%

Recording density

(tape)

1993-2011 32%

Cost per bit 1956-2007 33%

Flash Memory Storage Capacity 2001-2013 47%

Resistive RAM 2006-2013 272%

Ferro-electric RAM 2001-2009 37%

Phase Change RAM 2004-2012 63%

Magneto RAM 2002-2011 58%

Technologies Experiencing Rapid Rates of Improvements

Information Transmission, Materials and Biological Transformation

Technology

Domain

Sub-Technology Dimensions of

measure

Time

Period

Rate Per

YearInformation

Transmission

Last Mile Wireline Bits per second 1982-2010 48.7%

Wireless, 100 m Bits per second 1996-2013 79.1%

Wireless, 10 m 1995-2010 58.4%

Wireless, 1 meter (USB) 1996-2008 77.8%

Materials

Transformation

Carbon Nanotubes 1/Minimum Theoretical

Energy for Production

1999-2008 86.3%

Biological

Transformation

DNA Sequencing per unit cost 2001-2013 146%

Synthesizing per cost 2002-2010 84.3%

Cellulosic Ethanol Output per cost 2001-2012 13.9%

Technologies Experiencing Rapid Rates of Improvements(Energy Transformation and Transmission)

Technology

Domain

Sub-Technology Dimensions of

measure

Time

Period

Rate Per

YearEnergy Trans-

formation

Light Emitting

Diodes (LEDs)

Luminosity per Watt 1965-2008 31%

Lumens per Dollar 2000-2010 40.5%

Organic LEDs Luminosity per Watt 1987-2005 29%

GaAs Lasers Power/length-bar 1987-2007 30%

LCDs Square meters per dollar 2001-2011 11.0%

Quantum Dot

Displays

External Efficiency 1994-2009 79.0%

Solar Cells Peak Watt Per Dollar 2004-2013 21.0%

Photo-sensors

(Camera chips)

Pixels per dollar 1983-2013 48.7%

Light sensitivity 1986-2008 18%

Energy

Transmission

Super-conductors Current-length per dollar 2004-2010 115%

How can this Data be Used? To understand reasons for rapid improvements1

To analyze past1,2, current, or future3 changes in specific systems

To analyze changes in tradeoffs between different designs at

system level, sub-system level1,2

can this be better done with detailed cost models?

For future, to better understand when new forms of designs might become economically feasible3

To design systems that accommodate future design changes

To help students create new businesses that are based on new technologies or systems composed from new technologies

1 Funk, 2013, Technology Change and the Rise of New Industries, Stanford University Press; Funk J 2013 What Drives Exponential Improvements? California Management

Review 55(3): 134-152, Spring 2013: Funk J and Magee C 2015 Rapid Improvements with No Commercial Production: How do the improvements occur? Research Policy

2 Funk J 2009. Systems, Components, and Technological Discontinuities: The case of magnetic recording and playback equipment, Research Policy 38(7): 1079-1216.

3 Funk J and Magee C 2014. Exponential Change: What drives it? What does it tell us about the future?

MRI and CT

Scanners Laptops MP3 Players

Calculators Video Set-top boxes E-Book Readers

Digital Games Web Browsers Digital TV

Watches Mobile Digital Cameras Smart Phones

PCs Phones PDAs Tablet Computers

The Past: Increases in the Number of Transistors Make New

Forms of Electronic Products Economically Feasible

For more details, see Funk J, Technology Change and the Rise of New Industries, Stanford University Press 2013

slidehttp://www.slideshare.net/Funk98/how-is-technology-change-creating-new-opportunities-in-integrated-circuits-ics-and-electronic-systems

What’s

Next?

If we add magnetic disks, new displays,

glass fiber, lasers, and photo-sensors

The list of new systems becomes much longer

New forms of Internet content and applications have become possible over the last 20 years

More recently: Big Data, Cloud Computing, Social Networking

How did changes in tradeoffs impact on the emergence of these systems?

How are these changes impacting on current design choices?

Example of Changing Tradeoffs in Design

High cost of ICs and computers in the 1960s and 1970s

meant that most computers were shared

Many expected diffusion to occur through remote use of computers

As the cost of ICs dropped in the 1970s and 1980s, the fast

response time from PCs outweighed the low utilization of

PCs

Further reductions in cost of ICs and improvements in

display performance caused tradeoffs to change in favor of

portable computers

Tradeoffs for computers continue to change as cost and

performance of ICs and other electronic components rise

For more details, see Funk J, Technology Change and the Rise of New Industries, Stanford University Press 2013

slidehttp://www.slideshare.net/Funk98/how-is-technology-change-creating-new-opportunities-in-integrated-circuits-ics-and-electronic-systems

Changing Tradeoffs in Design of Electric Vehicles

Low energy storage density of batteries (1/25th of gasoline) makes it hard for

electric vehicles to have same range, weight, cost of conventional vehicles

Improvements in “components” are changing tradeoffs involved with electric vehicles

Faster rate of improvement for components in vehicle charging (power electronics 16% and other ICs 30-40%) stations than in batteries (5% per year) changes the tradeoffs towards a dense system of charging stations

Rates of improvement for power electronics and ICs also improve economics of wireless charging, which reduces set-up time for vehicles and maintenance cost for charging stations

For more details, see: http://www.slideshare.net/Funk98/it-and-transportation-systems http://www.slideshare.net/Funk98/microgrids-electric-vehicles-and-wireless-charging

Changing Tradeoffs in Public Transportation

Continued improvements in GPS and smart mobile phones (both cheaper and better) are changing the economics of

Buses

Bike sharing

Understanding bus arrival times and locations becomes easier with GPS and smart phones

Facilitates use of buses

Also managing bus routes

Smart phones help us find bike stations and borrow bikes

Helps integrate bike and train transport

Also determining station locations and redistributing bikes

For more details, see: http://www.slideshare.net/Funk98/it-and-transportation-systems

http://www.slideshare.net/Funk98/how-is-technology-change-creating-new-opportunities-in-integrated-circuits-ics-and-electronic-systems

http://www.slideshare.net/Funk98/how-is-technology-change-creating-new-opportunities-in-humancomputer-interfaces

Changing Tradeoffs in Automated Vehicles

Falling cost of ICs, lasers, MEMS (about 30% to 40% per year)

will make Automated Vehicles (AVs) 90% cheaper in 10 years

Dedicating roads or lanes in roads to AVs would dramatically

increase their benefits

Higher road capacity, faster travel time and thus better fuel

efficiency

Lower costs for traffic police, auto insurance, ambulance,

emergency vehicles

Dedicating roads to AVs would reduce technical requirements

Cars could rely more on wireless communication, magnetic stripes

and other inexpensive sensors than on LIDAR

For more details, see: http://www.slideshare.net/Funk98/it-and-transportation-systems http://www.slideshare.net/Funk98/smart-infrastructure-for-autonomous-vehicles

http://www.slideshare.net/Funk98/dedicated-roads-for-autonomous-vehicles http://www.slideshare.net/Funk98/autonomous-vehicles-28513504

Sustainability is a Design Problem!

Better product (and process) designs for systems are needed for

sustainability

Better designs for transportation, electric vehicle, and other systems

Technology change and improvements in components is key enabler of better

system design

Even solar cells require better designs

Installation is biggest percentage of total cost

How can we design solar cells for easier installation/implementation?

Just implementing IPCC’s approved list of technologies with subsidies

is misguided

Let’s help students understand rapidly improving technologies and

their impact on design tradeoffs in higher level systems

Can we do more Detailed Cost Analyses?

For example, can we simulate transportation systems and the impact of reduced costs of information technologies on design of transportation systems?

These simulations must consider

Composition of system

Current costs of each component and their rates of improvement

Impact of these component costs on design of system

Extent of improvements before system becomes economically feasible

Students should be doing this in order to understand when new designs become economically feasible in future

Rate of Improvement

Exte

nt

of

Impro

vem

ent

Needed

Small

Large

Slow Fast

For the Future: When Will New Technologies or New

Systems Composed of Them Become Economically Feasible?

Now or Probably

Very Soon

Probably

Never

Within

5 to 15 Years?

Within 5-15

Years?

My Research and Teaching Analyzes Economic

Feasibility of Many Technologies

Integrated circuits (ICs) and electronic systems

Internet of Things, Sensors, MEMS and Bio-electronic ICs

Lighting and Displays

Information Technology for Transportation Systems

Human Computer Interfaces

Nanotechnology

Superconductivity

Solar cells, wind turbines

Telecommunication

These analyses are available here: http://www.slideshare.net/Funk98/presentations

Students have Done Further Analyses

on More Than 50 Technologies

New forms of electronic systems: smart homes, robotic exoskeletons, smart grid, 3D

scanners, eye tracking, pico-projectors, wireless charging of phones and vehicles, 3D Holography, Ink Jet Printers, light field image sensors, wearable computing, solar gliders for telecom, quantum computers

health care: Bioprinters, bionic eyes, wearable health care devices, bio-sensors

displays: flexible OLEDs, conformal electronics, virtual retinal, transparent displays

materials: carbon-nanotubes, aerogels, superconductors, bio-luminescence, membranes

transportation and energy: automated vehicles, dedicated roads for automated vehicles, electric vehicles, wireless charging, smart grid, commercial drones

These analyses are available here: http://www.slideshare.net/Funk98/presentations

My Analyses and Student Analyses

Helps students understand

the tradeoffs in systems between

New forms of designs

Different technologies

when new technologies or new forms of designs might become economically feasible

which technologies will form the basis for new businesses

Many will argue that you can’t predict the future

But all actions assume predictions

And assuming no improvements is clearly a worse prediction than assuming faster improvements in some technologies than in other technologies

What do these Analyses tell us about Future?

No end to Moore’s Law and improvements in MEMS and Bio-Electronic ICs

In combination with the Internet, this is enabling

More Big Data Analysis, Cloud computing, Social Networking

Internet of Things and Home Automation

Better control of all systems (logistics, factories)

For health care

Computer assistants for doctors

Mobile phones become the center for health care

Drug delivery, Bionic eyes, Exoskeletons, Cyborgs

DNA sequencers and synthesizers change drug and materials development

What do these Technologies tell us about Future? (2)

Human computer interfaces

Better displays including more flexibility and more responsive to touch and voice

Augmented reality, Virtual reality, Wearable computing

Food and agriculture

better sensors for global value chains of food (and other products)

prescriptive planting and laser leveled fields

Energy

Rapid reductions in cost of solar cells (but not in installation costs)

Materials

Ultra-thin materials with high strength-to weight ratios

Nano-particles and fibers

Carbon nanotubes for electronics and other applications

What do these Technologies…. (3) Energy

Did any of the technologies mentioned on the last two slides

surprise you?

But what about energy?

Wind turbines: 2% rate of improvement per year over last 30 years

Li-ion batteries: 5% rate of improvement over last 20 years

Even non-module (installation) costs for solar cells only fall 4% per year

How can these slow rates of improvement make a meaningful

contribution to sustainability when they are still far from

competitive with existing technologies?

Yet the IPCC and sustainability organizations focus on these

technologies

Energy: New Systems to Consider and Analyze

More efficient logistics for humans and freight through better computers and

RFID tags

Smart lighting (and heating) systems that combine LEDs with motion sensors

and other ICs can reduce lighting and heating costs

Smart water and other systems through better sensors reduce water usage

Better sensors for smarter agriculture, aquaculture, and food logistics can

increase availability of food

Smart grid (through better Internet) can enable more charging points and a

greater frequency of vehicle recharging and thus reduce need for battery

storage capacity

Better digital and power (MOSFETS) ICs and thin film coils reduce cost of

wireless charging and thus further facilitate frequent recharging and need

for battery storage capacity in vehicles

Energy: New Systems to Consider and Analyze (2)

In combination with existing and improved mobile phones, cheaper and

better GPS can help vehicles find charging points, cities improve bus

service, and commuters increase their use of public transportation

Existing and better mobile phones can also facilitate the sharing

economy including the sharing of bicycles to overcome crowded

parking lots in cities

Roads dedicated to autonomous vehicle (through improvements in ICs,

MEMS, and lasers) can increase road capacity and fuel efficiency

Improvements in superconductors lead to longer and more efficient

energy transmission and better generators, motors, and transformers

Overall smarter cities that use less energy, water, and other resources

through better sensors

Conclusions

Understanding rates of improvement can help us design

better systems

Systems that benefit from technologies with rapid

improvements

Systems that can be upgraded with the new technologies

Let’s help students design their future

Lets give students the data and methods to design their

future

Appendix

Quantity (Q)

Price (P)

q

p

Diffusion often starts in segments/users that are willing to pay more

for products and services than are other segments/users

Demand

Curve

Supply Curve

Typical movement of

supply curve over time Typical

movement

of demand

curve over

time

Quantity (Q)

Price (P)

q

p

Maximum Threshold of Price: the maximum price that the market will

pay for a new technology

Demand

Curve

Supply Curve

Typical movement of

supply curve over time Typical

movement

of demand

curve over

time

Quantity (Q)

Performance

(P)

q

p

Sometimes, diffusion starts in segments/users that have

lower performance expectations than other segments/users

Supply

Curve

Demand

Curve

Quantity (Q)

Performance

(P)

Minimum Threshold of Performance: the minimum performance

the market will accept for a new technology

Supply

Curve

Demand

Curve

Typical

movement

of supply

curve over

time

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12

Figure 2. Number of Chemical Technologies by Annual Rates of Improvement

Annual Rates of Improvement

0

2

4

6

8

10

12

14

16

18

20

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14

Annual Rates of Improvement

Figure 3. Number of Non-Chemical

Technologies by Annual Rates of Improvement

Focusing on Technologies with Annual Rates Under 15%