N
N. Thornton
- Jan 1, 1970
- 0
Todays blue sky
---------------
Todays blue sky is a machine that will save its owners a fortune.
Large organisations such as councils, hotel chains, and many others
buy large quantities of electronic equipment: with a suitable machine
much of this expenditure could be avoided.
New goods are so cheap because they are made by machines, used goods
are so costly to repair because they are repaired by hand, slowly and
expensively. The central idea here is to change that, and develop a
repair machine that can churn out repaired goods at speed and in
quantity, with only one human operator.
It would take the best of the following faulty goods:
microwaves
driers
stereos and radios
TVs
videos
washing machines
hoovers (vacuum cleaners to the Americans)
and apply a fast mechanised and automated repair process to them.
As well as junk and low value items, tips and dumps also have a
regular supply of modern non-working goods in othewise good condition.
For example Dyson vacs now turn up regularly at dumps, along with many
items just out of guarantee. Many retail chains also offer to take
customers' old goods away. A lot of quality material is buried along
with the junk simply because repair is too costly.
This machine gets round the problem of repair cost in 2 ways. Firstly
it drastically reduces labour costs.
Secondly it almost completely eliminates parts costs. It logs all
items it checks, and decides what to do with the items it does not
repair. Most it dumps in the scrap bin, but it will select some to
keep in a parts pile, the size of which is determined by the operator.
After the first week it will thus supply itself with parts for
repairs. Only low value items that must be new are bought, things like
hoover bags for example.
So how would this machine work?
-------------------------------
This is what it would need to do with each item:
1. pick the item up and position it for testing
2. identify the item, by make, model no, etc
3. when it cant do that it would test it to see what it does, using
the item's external connectors, and narrowing the options down by
optical word recognition.
4. test it to see how it works and whats wrong
5. remove covers when necessary
6. either recall specific circuit information or use general purpose
fault analysis approaches.
7. apply the necessary tests to work out what the problem part is
8. work out how to fix it
9. either label the item saying which component to replace, and which
dead machine to source it from, and place it in the repair pile, cover
ready removed, with donor machine next to it.
10. Or decide that its not worth repairing, and drop it in the scrap
bin
11. Or ditto but put it in the parts pile
12. pick up and function and safety test the item after repair.
13. Fully stock control the repaired items.
It would pick the items up itself, and run its processes on item after
item, churning out a stream of goods labelled with how to repair them
in less than say 20 minutes, with only the easy repairs being chosen.
The following goods would be rejected:
not of sufficient value
takes too long to repair
spare parts needed that arent immediately accessible onsite free
any goods the company already has too many of
The machine will maintain a folder of choice related data which helps
it intelligently assess which goods to repair. This folder will
contain information for example on which items the company has no
interest in, any it particularly needs, any specific models with known
problems, make or model preferences, and any other issues that affect
which goods it should select for repairs.
Basically this (imaginary) machine takes a slow manual repair process
and turns it into a conveyor belt operation with high output per
person, more like a factory.
A factory makes one item on a line, and thus uses simple machines
specific to that task. This repair machine must cover a range of goods
and a range of models, and test and diagnose faults, making it need to
be much more complex. On the other hand it is dealing with goods that
have already been almost completely manufactured: they will need only
one item replacing. All the rest of the manufacture has been done
already. Not only that but the materials it works with are much
cheaper than a factory's, because they are simply scrap rather than a
selection of new designed and made to order parts. Thus this machine
has cost advantages over a factory as well as its own
complexity/expense downside.
I think this is the way forward. It is probably more a question of
when these machines will come into use rather than whether.
Can we do it now?
-----------------
I think the answer is yes, that we already have all the technology we
need to develop such a machine. Lets look at each step of the process
and see what we have.
1. pick the item up and position it for testing
- this is straightforward with robot arms and video shape recognition.
2. identify the item, by make, model no, etc
- cameras, optical character recognition and a database are all well
within todays technology
3. when it cant do that it would test it to see what it does, using
the item's external connectors, narrowing the options down first by
optical word recognition.
- it is not difficult to use meters, sig gen, scope etc, and apply
power to mains type connectors or leads. Text recognition would
greatly speed things up by identifying keywords like volume, tuning,
cassette, spin, bio-profile, 40C, and so on.
4. test it to see how it works and whats wrong
- once intended functions have been identified it can run a test
routine to see what the item does. Robot arms can operate the
controls. It could even apply a series of thumps to check for any poor
connections.
5. remove covers when necessary
- in most cases fairly straightforward using robot arms, with a
machine with all the necessary tools. How to open this case also needs
to be covered, which I expect could be done, and a general plan of
attack routine might be worth adding for any items it cant work out.
6. either recall specific circuit information or use general purpose
fault analysis approaches.
- such approaches are well known
7. apply the necessary tests to work out what the problem part is
- this often requires probing internal parts. Video would need to be
able to recognise some of the key parts, the more it could recognise
the more tests it could run. Object recognition is a known science.
It wont need to get it right 100% of the time, but the more tests it
can correctly apply the more items it can repair. Electrical probes
can be applied using todays robot arm technology, with some
electronics to detect when it contacts.
8. work out how to fix it
- these techniques are well known. If the part rcognition is good it
should be possible to do this with a good success rate.
9. either label the item saying which component to replace, and which
dead machine to source it from, and place it in the repair pile, cover
ready removed, with donor machine next to it.
10. Or decide that its not worth repairing, and drop it in the scrap
bin
11. Or ditto but put it in the parts pile
- these 3 are simple.
12. function and safety test the item after repair.
- all known technology.
13. Fully stock control the repaired items.
- EPOS and order systems are well established already
All these methods can be done today.
Is it worth it?
---------------
The value of such equipment would be considerable. Rather than use it
to repair scrapped goods and sell them second hand, it would be of
greater value if it is used instead to supply a stream of goods to
organisations that are currently buying new, because the goods
produced wipe out the new goods purchase costs, rather than only
achieving used goods prices less all the costs involved in selling.
Once such kit is developed it could output a stream of items every
day. The development cost is quite substantial, but its use is also
very large, not just for the first machine itslf, but the whole genre
of repair machines that will follow. Is it worth it? You tell me.
Thats my thought for the morning, I've left plenty of debateables in
there. What do you think?
Regards, NT
---------------
Todays blue sky is a machine that will save its owners a fortune.
Large organisations such as councils, hotel chains, and many others
buy large quantities of electronic equipment: with a suitable machine
much of this expenditure could be avoided.
New goods are so cheap because they are made by machines, used goods
are so costly to repair because they are repaired by hand, slowly and
expensively. The central idea here is to change that, and develop a
repair machine that can churn out repaired goods at speed and in
quantity, with only one human operator.
It would take the best of the following faulty goods:
microwaves
driers
stereos and radios
TVs
videos
washing machines
hoovers (vacuum cleaners to the Americans)
and apply a fast mechanised and automated repair process to them.
As well as junk and low value items, tips and dumps also have a
regular supply of modern non-working goods in othewise good condition.
For example Dyson vacs now turn up regularly at dumps, along with many
items just out of guarantee. Many retail chains also offer to take
customers' old goods away. A lot of quality material is buried along
with the junk simply because repair is too costly.
This machine gets round the problem of repair cost in 2 ways. Firstly
it drastically reduces labour costs.
Secondly it almost completely eliminates parts costs. It logs all
items it checks, and decides what to do with the items it does not
repair. Most it dumps in the scrap bin, but it will select some to
keep in a parts pile, the size of which is determined by the operator.
After the first week it will thus supply itself with parts for
repairs. Only low value items that must be new are bought, things like
hoover bags for example.
So how would this machine work?
-------------------------------
This is what it would need to do with each item:
1. pick the item up and position it for testing
2. identify the item, by make, model no, etc
3. when it cant do that it would test it to see what it does, using
the item's external connectors, and narrowing the options down by
optical word recognition.
4. test it to see how it works and whats wrong
5. remove covers when necessary
6. either recall specific circuit information or use general purpose
fault analysis approaches.
7. apply the necessary tests to work out what the problem part is
8. work out how to fix it
9. either label the item saying which component to replace, and which
dead machine to source it from, and place it in the repair pile, cover
ready removed, with donor machine next to it.
10. Or decide that its not worth repairing, and drop it in the scrap
bin
11. Or ditto but put it in the parts pile
12. pick up and function and safety test the item after repair.
13. Fully stock control the repaired items.
It would pick the items up itself, and run its processes on item after
item, churning out a stream of goods labelled with how to repair them
in less than say 20 minutes, with only the easy repairs being chosen.
The following goods would be rejected:
not of sufficient value
takes too long to repair
spare parts needed that arent immediately accessible onsite free
any goods the company already has too many of
The machine will maintain a folder of choice related data which helps
it intelligently assess which goods to repair. This folder will
contain information for example on which items the company has no
interest in, any it particularly needs, any specific models with known
problems, make or model preferences, and any other issues that affect
which goods it should select for repairs.
Basically this (imaginary) machine takes a slow manual repair process
and turns it into a conveyor belt operation with high output per
person, more like a factory.
A factory makes one item on a line, and thus uses simple machines
specific to that task. This repair machine must cover a range of goods
and a range of models, and test and diagnose faults, making it need to
be much more complex. On the other hand it is dealing with goods that
have already been almost completely manufactured: they will need only
one item replacing. All the rest of the manufacture has been done
already. Not only that but the materials it works with are much
cheaper than a factory's, because they are simply scrap rather than a
selection of new designed and made to order parts. Thus this machine
has cost advantages over a factory as well as its own
complexity/expense downside.
I think this is the way forward. It is probably more a question of
when these machines will come into use rather than whether.
Can we do it now?
-----------------
I think the answer is yes, that we already have all the technology we
need to develop such a machine. Lets look at each step of the process
and see what we have.
1. pick the item up and position it for testing
- this is straightforward with robot arms and video shape recognition.
2. identify the item, by make, model no, etc
- cameras, optical character recognition and a database are all well
within todays technology
3. when it cant do that it would test it to see what it does, using
the item's external connectors, narrowing the options down first by
optical word recognition.
- it is not difficult to use meters, sig gen, scope etc, and apply
power to mains type connectors or leads. Text recognition would
greatly speed things up by identifying keywords like volume, tuning,
cassette, spin, bio-profile, 40C, and so on.
4. test it to see how it works and whats wrong
- once intended functions have been identified it can run a test
routine to see what the item does. Robot arms can operate the
controls. It could even apply a series of thumps to check for any poor
connections.
5. remove covers when necessary
- in most cases fairly straightforward using robot arms, with a
machine with all the necessary tools. How to open this case also needs
to be covered, which I expect could be done, and a general plan of
attack routine might be worth adding for any items it cant work out.
6. either recall specific circuit information or use general purpose
fault analysis approaches.
- such approaches are well known
7. apply the necessary tests to work out what the problem part is
- this often requires probing internal parts. Video would need to be
able to recognise some of the key parts, the more it could recognise
the more tests it could run. Object recognition is a known science.
It wont need to get it right 100% of the time, but the more tests it
can correctly apply the more items it can repair. Electrical probes
can be applied using todays robot arm technology, with some
electronics to detect when it contacts.
8. work out how to fix it
- these techniques are well known. If the part rcognition is good it
should be possible to do this with a good success rate.
9. either label the item saying which component to replace, and which
dead machine to source it from, and place it in the repair pile, cover
ready removed, with donor machine next to it.
10. Or decide that its not worth repairing, and drop it in the scrap
bin
11. Or ditto but put it in the parts pile
- these 3 are simple.
12. function and safety test the item after repair.
- all known technology.
13. Fully stock control the repaired items.
- EPOS and order systems are well established already
All these methods can be done today.
Is it worth it?
---------------
The value of such equipment would be considerable. Rather than use it
to repair scrapped goods and sell them second hand, it would be of
greater value if it is used instead to supply a stream of goods to
organisations that are currently buying new, because the goods
produced wipe out the new goods purchase costs, rather than only
achieving used goods prices less all the costs involved in selling.
Once such kit is developed it could output a stream of items every
day. The development cost is quite substantial, but its use is also
very large, not just for the first machine itslf, but the whole genre
of repair machines that will follow. Is it worth it? You tell me.
Thats my thought for the morning, I've left plenty of debateables in
there. What do you think?
Regards, NT