Optimizing machining parameters in a framework for adaptive computer control

Davis, Robert P.; Wysk, Richard A.; Agee, Marvin H.; Kimbler, D. L.

doi:10.1016/0360-8352(80)90032-7

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The method is very amenable to planning optimum machine settings and can be used to initialize an adaptive control system which will then reoptimize feed and speed during cut, as described in [5]. However, the principal advantages of the model are: the discrete nature of the resultant solution process, consequent reduction in solution time, and improved solution accuracy.…”

Section: Discussionmentioning

confidence: 99%

“…A number of additional machine parameter optimization problems have been solved using the algorithm described herein and that of Davis, Wysk and Agee [ 5 ] . The results appear similar to that given above (e.g., execution time and Agee is more amenable to an adaptive control structure, when attempting to obtain an optimum steady-state result the procedure given here was consistently more expedient.…”

Section: Ayd ?It Setsmentioning

confidence: 99%

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A Discrete Variable Approach to Machine Parameter Optimization

Hayes

Davis

1979

A I I E Transactions

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Section: Discussionmentioning

confidence: 99%

Section: Ayd ?It Setsmentioning

confidence: 99%

A Discrete Variable Approach to Machine Parameter Optimization

Hayes

Davis

1979

A I I E Transactions

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“…Bedini and Pinotti (1982) proposed an ACC satisfaction strategy incorporating an optimization scheme that uses a hill-climbing method. Davis et al (1980) determined optimum machining parameters and extend their discrete variable approach method to an adaptive control system. Studies have also been done on adaptive control applications for other processes, such as grinding (Amitay et al 1981), and chemical processes (lang et al 1987); see also Arsovski (1983).…”

mentioning

confidence: 99%

An interactive on-line multi-objective optimization approach with application to metal cutting turning operation

Malakooti

1991

International Journal of Production Research

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An on-line supervisory computer control model for optimization of multiple objectiveprogramming problems is developedand applied to machining problems. Specifically, the turning operation is formulated and solved by the approach. For the first time, the characteristics of on-line multi-objective problems are described and an approach for solving such problems is developed. The proposed system maintains feasibility of operations and optimizesobjectives based on the machine performance and on-line interactions with the decision-maker (DM). The model is hierarchical and consists of two levels: level I is designed to protect automated machinery and the workpiece by monitoring the process outputs; and level 2 is designed to optimize the on-line multi-objective problem. The tasks of both levels are accomplished by on-linemonitoring and control of changes in processoutputs via real-time information provided by sensors. The recommended parameters, obtainable from the multi-objective optimization approach, are used to create and update a database for machinability problems for future use. An example is discussed.

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