---
res:
  bibo_abstract:
  - Ultrasonic wire bonding is an indispensable process in the industrial manufacturing
    of semiconductor devices. Copper wire is increasingly replacing the well-established
    aluminium wire because of its superior electrical, thermal and mechanical properties.
    Copper wire processes differ significantly from aluminium processes and are more
    sensitive to disturbances, which reduces the range of parameter values suitable
    for a stable process. Disturbances can be compensated by an adaption of process
    parameters, but finding suitable parameters manually is difficult and time-consuming.
    This paper presents a physical model of the ultrasonic wire bonding process including
    the friction contact between tool and wire. This model yields novel insights into
    the process. A prototype of a multi-objective optimizing bonding machine (MOBM)
    is presented. It uses multi-objective optimization, based on the complete process
    model, to automatically select the best operating point as a compromise of concurrent
    objectives.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Andreas
      foaf_name: Unger, Andreas
      foaf_surname: Unger
  - foaf_Person:
      foaf_givenName: Matthias
      foaf_name: Hunstig, Matthias
      foaf_surname: Hunstig
  - foaf_Person:
      foaf_givenName: Tobias
      foaf_name: Meyer, Tobias
      foaf_surname: Meyer
  - foaf_Person:
      foaf_givenName: Michael
      foaf_name: Brökelmann, Michael
      foaf_surname: Brökelmann
  - foaf_Person:
      foaf_givenName: Walter
      foaf_name: Sextro, Walter
      foaf_surname: Sextro
      foaf_workInfoHomepage: http://www.librecat.org/personId=21220
  bibo_doi: 10.4071/2380-4505-2018.1.000572
  bibo_volume: Vol. 2018, No. 1, pp. 000572-000577.
  dct_date: 2018^xs_gYear
  dct_language: eng
  dct_subject:
  - wire bonding
  - multi-objective optimization
  - process model
  - copper wire
  - self-optimization
  dct_title: Intelligent Production of Wire Bonds using Multi-Objective Optimization
    – Insights, Opportunities and Challenges@
...