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Revision as of 01:41, 6 April 2007
Intro
In Western countries many industrial process are becoming highly automated already, but human effort is needed for construction and commissioning as well as maintenance and repair. In developing nations, there is not much automation at all due to labour being so cheap; however this is a great waste of human lives.
These self-repairing systems are based on technologies and knowledge that we already possess. No fictional concepts or unattainable artificial intelligence are required to make this happen. We have the ability today to create systems that provide for the global population's basic needs and far beyond, while minimising our impact on the environment – these two aspects are not mutually exclusive.
Contents
Self-maintenance and repair
If complicated physical systems were able to be serviced and repaired completely automatically there would be many advantages. There would be higher productivity and efficiency without people in the loop - we tend to slow things down and are error prone; also people could be freed up to do something less menial; and the systems could scale quickly when more capacity is needed.
Machines today, such as industrial machinery, are designed to be looked after and serviced by people, and it would likely need artificial intelligence beyond our current capabilities to maintain or repair these systems completely autonomously. However it is feasible to design them from the outset to be maintained autonomously; designed in a modular fashion with components easily removed and replaced by another machine, and embedded wired or wireless sensors giving the ability to diagnose faults on all significant parts.
Many parameters can now be sensed with solid-state sensors, manufactured on tiny silicon chips, which can be embedded within functioning machines. If the signatures from multiple sensors relating to each machine function is known when operating within normal bounds, it provides a method for pin-pointing problems with great accuracy. Vibration, temperature, rotation, pressure, distance, voltage, acceleration and structural integrity as examples. This already happens to a certain extent on machines today such as vehicles but it only applies to a small sub-set of vital components.
What we are talking about here is having multiple micro-sensors within every single component and also scattered throughout structural parts. A little similar to the way humans and animals have pain receptors that let the brain know when a part is damaged. Unlike humans, however, the computer would have a complete blueprint for how it functions, which would allow precise diagnosis, and flawless new parts could be fabricated to replace broken ones,
Operations can be assessed in real-time and if there is a failure then the defective parts, or the relevant sub-assembly, can be replaced. In many instances it may be possible to know a failure is imminent before it actually happens due to an abnormal rise in temperature or vibration for example. With the system containing a full three-dimensional schematic with exact positions and extraction paths for every part, a repair machine can swap the part without requiring any human intervention.
Where would the replacement parts come from? Either held locally in a store, or shipped in via automated transport, or even manufactured on demand via additive fabrication or CNC milling.
So the physical aspects of the machines need to be designed with autonomous replacement in mind, with magnetic, RFID or optical cues that can easily be read by a repair robot, and highly modular design of components allowing them to easily be extracted and replaced. For instance, a gearbox that slots in or out as a single cartridge.
This same principle, by extension could allow these self-maintaining systems to become self-building too, which means that scaling up facilities becomes easy. More autonomous farming equipment required? Just increase the scale of the agricultural manufacturing facilities, and now you have a greater output of agricultural machinery. A little simplistic perhaps, but you get the idea.
- The shape of sensors to come
Hitachi's µ-Chip (shown in top image) is 0.4 x 0.4mm in size. With a small antennae (not shown) it is able to transmit a 128 bit ID number. However, in the lower image is a microscope image of Hitachi's new 'RFID powder', currently in development, shown next to a human hair. It is 64 times smaller by area than the original µ-Chip and has the same capability and can be embedded within a sheet of paper [1]. It will not be long before various types of solid-state sensor can be made on a similar scale and embedded within every component of a machine giving unprecedented information relating to its operation.
A quite different approach to self-repairing machines would be to build them out of self-healing materials 
. It is likely that sophisticated self-repairing machines in the future will utilise both these methods.
Increasing capacity automatically as required
A major advantage of having processes almost completely automated is that capacity can easily be scaled up. Just as the manufacturing and construction machinery can be repaired automatically, more manufacturing machinery can also be created by machine, as needed.
This capability means we will be able to do things that are simply not possible at the moment. Mega-scale engineering projects become feasible. If a task is complicated, tedious and a great effort we only need to design the system for the job and let it get on with it. Easier said than done of course. But as these systems become more sophisticated, so will the design tools used to create them. People will be able to interface with these complex systems at ever higher levels of abstraction (although there will be plenty of technically-minded who understand the lower levels too). It will be similar to high-level programming languages hiding the lower levels of code - the individual nuts and bolts will be like the zeros and ones of machine code .
Automated infrastructure
These complex systems can be developed using the power of open collaborative design, which has the additional benefit of giving transparency to their development. Having the industrial infrastructure fully automated means it can be easily scaled up to provide everything that the global population requires with ultimate flexibility, and it frees people up to do things that people are good at and want to do.
People in control
These systems needs to be carefully controlled by people. We will always need to understand how they work, at every level, and they will need to be monitored. Some people wonder whether we will get to a stage where the machines are so sophisticated, and we have relied on them for so long, that no-one will actually know how they work, and therefore we will not be fully in control of them. The reality is that there will always be people interested in this sort of thing - engineers, scientists and geeks in general. They want to know how to make things and understand how they work. There always have been technically-minded people, and have no doubt there always will be.
People will need to improve the designs and make sure they are safe and efficient. We must always remain part of the loop in terms of ultimate control. It is highly likely that we will develop computer-controlled systems more capable at certain tasks than we are, in fact we already have done, but this trend will inevitably continue until there is very little in terms of systems control that can't be done better by a computer. But however sophisticated these systems become they are still just tools for our service — a means to an end. There will always be a threshold where higher-level decisions can only be made with the judgement of people, communities or wider society, and it is important that this threshold should not creep upwards unnoticed over time.
How closed does 'closed' need to be?
Advanced automation/How closed does 'closed' need to be?
See also
- Turning virtual designs into physical objects (digital manufacturing) - for information on various smaller scale computer-controlled flexible manufacturing techniques
- Nanotechnology
- Open-source robotics
Not manufacturing as such, but an important part of the jigsaw:
- Willow Garage, started by an early Google employee, and has close links with Stanford University. They are developing ROS (Robot Operating System) , OpenCV and the PR2 hardware platform. Mission & History
