Abstract
Metal forming processes operate in conditions of uncertainty due to parameter variation and imperfect understanding. This uncertainty leads to a degradation of product properties from customer specifications, which can be reduced by the use of closed-loop control. A framework of analysis is presented for understanding closed-loop control in metal forming, allowing an assessment of current and future developments in actuators, sensors and models. This leads to a survey of current and emerging applications across a broad spectrum of metal forming processes, and a discussion of likely developments.
Highlights
Reviews have been published on closed-loop control of electro-discharge machining [166], machine tool feed-drives [169], machine tools [96], machining [104], robotic welding [197], drilling fibre-reinforced plastic composites [165] and additive manufacturing with metal [175]. These reviews raise common themes which translate to the challenge of controlling properties in metal forming: because process behaviour is non-linear, the simplest applications of proportional–integral–derivative (PID) control can act only over a restricted range of actuator settings; the sensors are typically indirect, for example temperatures can be measured only at component surfaces and often at some distance from the region of interest, so are usually interpreted via an ‘observer’ model; because of the non-linearity of the processes, the success of the control system is strongly dependent on the process model available to it, and this must trade-off accuracy against solution speed
All contemporary metal forming machines are equipped with closed-loop control systems, to ensure that the actuators fitted to the equipment lead to the anticipated response of the equipment
This form of closed-loop control is illustrated in Fig. 5 for a subset of Fig. 4 and is not the focus of this paper: in Fig. 5, the feedback relates to the state of the equipment, where this paper considers feedback related to the state of the workpiece
Summary
The technology of metal forming has evolved over 7000 years, from the earliest ornaments and tools, through the mediaeval blacksmith and armourer, to today’s rapid mass production in rolling mills and presses. Plastic composites [165] and additive manufacturing with metal [175] These reviews raise common themes which translate to the challenge of controlling properties in metal forming: because process behaviour is non-linear, the simplest applications of proportional–integral–derivative (PID) control can act only over a restricted range of actuator settings; the sensors are typically indirect, for example temperatures can be measured only at component surfaces and often at some distance from the region of interest, so are usually interpreted via an ‘observer’ model; because of the non-linearity of the processes, the success of the control system is strongly dependent on the process model available to it, and this must trade-off accuracy against solution speed
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