TY - GEN
T1 - Automated generation of orienting devices for vibratory bowl feeders
AU - Stocker, C.
AU - Hell, M.
AU - Reisch, R.
AU - Reinhart, G.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Vibratory bowl feeders (VBF) are most frequently used to sort and feed bulk material in automated production systems. To correctly orient the parts for further manipulation, a set of orienting devices has to be selected and sequenced. Today, the design process is expensive and time-consuming, as it is based on a manual trial-and-error approach and requires experienced specialists. Therefore, the goal is to develop a method for the automated, computer-aided generation of orienting devices based on physics simulation. This paper presents the concept of an automated configuration system, starting with a part-specific library of possible traps. For each of these traps, the distribution of orientations after passing the trap is calculated. Based on these distributions, an adapted algorithm solves the configuration task automatically. The paper closes with the discussion of this concept and gives an outlook on future work.
AB - Vibratory bowl feeders (VBF) are most frequently used to sort and feed bulk material in automated production systems. To correctly orient the parts for further manipulation, a set of orienting devices has to be selected and sequenced. Today, the design process is expensive and time-consuming, as it is based on a manual trial-and-error approach and requires experienced specialists. Therefore, the goal is to develop a method for the automated, computer-aided generation of orienting devices based on physics simulation. This paper presents the concept of an automated configuration system, starting with a part-specific library of possible traps. For each of these traps, the distribution of orientations after passing the trap is calculated. Based on these distributions, an adapted algorithm solves the configuration task automatically. The paper closes with the discussion of this concept and gives an outlook on future work.
KW - Manufacturing systems
KW - heuristic algorithms
KW - optimized production technology
UR - http://www.scopus.com/inward/record.url?scp=85045277642&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2017.8290160
DO - 10.1109/IEEM.2017.8290160
M3 - Conference contribution
AN - SCOPUS:85045277642
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 1586
EP - 1590
BT - 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
PB - IEEE Computer Society
T2 - 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
Y2 - 10 December 2017 through 13 December 2017
ER -