@INPROCEEDINGS{Meyer2016,
  howpublished = {Conference Proceedings},
  author = {Tobias Meyer AND Andreas Unger AND Simon Althoff AND Walter Sextro
	AND Michael Brökelmann AND Matthias Hunstig AND Karsten Guth},
  title = {Reliable Manufacturing of Heavy Copper Wire Bonds Using Online Parameter
	Adaptation},
  booktitle = {IEEE 66th Electronic Components and Technology Conference},
  year = {2016},
  pages = {622-628},
  abstract = {Usage of copper wire bonds allows to push power boundaries imposed
	by aluminum wire bonds. Copper allows higher electrical, thermal
	and mechanical loads than aluminum, which currently is the most commonly
	used material in heavy wire bonding. This is the main driving factor
	for increased usage of copper in high power applications such as
	wind turbines, locomotives or electric vehicles. At the same time,
	usage of copper also increases tool wear and reduces the range of
	parameter values for a stable process, making the process more challenging.
	To overcome these drawbacks, parameter adaptation at runtime using
	self-optimization is desired. A self-optimizing system is based on
	system objectives that evaluate and quantify system performance.
	System parameters can be changed at runtime such that pre-selected
	objective values are reached. For adaptation of bond process parameters,
	model-based self-optimization is employed. Since it is based on a
	model of the system, the bond process was modeled. In addition to
	static model parameters such as wire and substrate material properties
	and vibration characteristics of transducer and tool, variable model
	inputs are process parameters. Main simulation result is bonded area
	in the wiresubstrate contact. This model is then used to find valid
	and optimal working points before operation. The working point is
	composed of normal force and ultrasonic voltage trajectories, which
	are usually determined experimentally. Instead, multiobjective optimalization
	is used to compute trajectories that simultaneously optimize bond
	quality, process duration, tool wear and probability of tool-substrate
	contacts. The values of these objectives are computed using the process
	model. At runtime, selection among pre-determined optimal working
	points is sufficient to prioritize individual objectives. This way,
	the computationally expensive process of numerically solving a multiobjective
	optimal control problem and the demanding high speed bonding process
	are separated. To evaluate to what extent the pre-defined goals of
	self-optimization are met, an offthe- shelf heavy wire bonding machine
	was modified to allow for parameter adaptation and for transmitting
	of measurement data at runtime. This data is received by an external
	computer system and evaluated to select a new working point. Then,
	new process parameters are sent to the modified bonding machine for
	use for subsequent bonds. With these components, a full self-optimizing
	system has been implemented.},
  doi = {10.1109/ECTC.2016.215},
  keywords = {Self-optimization, adaptive system, bond process, copper wire}
}