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Full-Text Articles in Engineering
Droplet Size Regulation In The Short Circuit Gmaw Process Using A Controlled Current Waveform, Dominic Cuiuri, John Norrish, Christopher Cook
Droplet Size Regulation In The Short Circuit Gmaw Process Using A Controlled Current Waveform, Dominic Cuiuri, John Norrish, Christopher Cook
Dominic Cuiuri
Enhanced control of the short-circuit gas metal arc welding (GMAW) process can be achieved through the use of an advanced power source applying a controlled current waveform. By using a current waveform whose period is adapted to suit the requirements of the process, excellent welding performance can be achieved. When the current waveform is of fixed peak amplitude and shape, the control can be considered to be open-loop, as there is no active attempt to regulate a specific process parameter such as arc length, fusion area or dipping frequency. There is scope for more sophisticated control of the process. Using …
Modelling And Simulation Of The Magnetically Impelled Arc Butt (Miab) Process For Transmission Pipeline Applications, John Norrish, Dominic Cuiuri, Mohammad Hossain
Modelling And Simulation Of The Magnetically Impelled Arc Butt (Miab) Process For Transmission Pipeline Applications, John Norrish, Dominic Cuiuri, Mohammad Hossain
Dominic Cuiuri
Early patents for the Magnetically Impelled Arc Butt process (MIAB) date back to 1940 [1] and the basic principles of the process have remained unchanged from this time. The process was however refined in the 1970s for use in the production of automotive components and has been used extensively in this area. Investigation of the process for pipe girth welding have been reported and commercial pipe welding heads are reported to be available in the Ukraine [2], Although the process is well established it is believed that a more fundamental analysis of the mechanisms involved would assist in the optimisation …
Optimal Sensor Distribution For Multi-Station Assembly Process Using Chaos-Embedded Fast-Simulated Annealing, N Shukla, M Tiwari, R Shankar
Optimal Sensor Distribution For Multi-Station Assembly Process Using Chaos-Embedded Fast-Simulated Annealing, N Shukla, M Tiwari, R Shankar
Nagesh Shukla
This paper presents a novel methodology for the allocation of sensors in multi-station assembly processes. It resolves two core issues pertaining to the determination of an optimal number of sensors to be employed and their best locations. To make the traditional approach more effective, the effect of noise on sensor placement is minimized by maximizing the determinant of the Fischer information matrix. A state-space approach is adopted to model the variation propagation pertaining to the transfer of parts in a given multi-station assembly process. Further, the objective function conceived is significant over other contributions with respect to adding the effect …
Multi Station Assembly Process And Determining The Optimal Sensor Placement Using Chaos Embedded Fast Simulated Annealing, Nagesh Shukla, Manoj Tiwari, Ravi Shankar
Multi Station Assembly Process And Determining The Optimal Sensor Placement Using Chaos Embedded Fast Simulated Annealing, Nagesh Shukla, Manoj Tiwari, Ravi Shankar
Nagesh Shukla
This paper presents a new methodology for allocation of sensors in Multi Station Assembly processes. It resolves two core issues i.e. determining the optimal number of sensors to be used and the best locations for each of sensors. The effect of noise on the sensor placement has been minimized by maximizing the determinant of Fisher information matrix. The paper conceives objective function that is significant over other contributions in respect of adding the effect of noise coupled with the sensor data. To optimize the proposed objective function, a new algorithm is developed that combines Chaotic sequences with traditional Evolutionary Fast …