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We will write p(T =n to indicate that the productivity of machine T is n.
Improving the productivity of machine building industry enterprises can be done following the reverse path proposed by the developed framework.
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One of the most significant limitation of the productivity of machining operations is the regenerative machine tool vibration, also called machine tool chatter, which is a self-excited vibration between the tool and the workpiece induced by the chip formation mechanism.
And we are beginning to get a glimpse of the productivity potential of machine intelligence.
We will say that the productivity of any machine that does not halt is 0. Productivity is a function from Turing machine descriptions (natural numbers) to natural numbers.
If the machine leaves n ones on the tape when it halts, we will say that the productivity of this machine is n.
This too is a function from natural numbers (the number of states) to natural numbers (the maximum productivity of a machine with that number of states).
Only when all these are properly set and controlled it is possible to ensure consistent accuracy and productivity of the machine tool.
In practice, typically the metal removal rate and therefore the productivity of the machine are reduced, in order to avoid such vibrations.
Several issues including accurate programming, proper tool selection, machining feeds and speeds selection, thermal error compensation, vibration monitoring, etc. contribute significantly to the performance and productivity of a machine tool in an industrial scenario.
This study also presented a self-organizing fuzzy controller (SOFC) for manipulating such a system to maintain a constant turning force operation and improve the productivity of the machine tool.
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