The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Multi-Objective Optimization in Industrial Robotic Cell Design
Abstract
It has become a common practice to conduct simulation-based design of industrial robotic cells, where Mechatronic system model of an industrial robot is used to accurately predict robot performance characteristics like cycle time, critical component lifetime, and energy efficiency. However, current robot programming systems do not usually provide functionality for finding the optimal design of robotic cells. Robot cell designers therefore still face significant challenge to manually search in design space for achieving optimal robot cell design in consideration of productivity measured by the cycle time, lifetime, and energy efficiency. In addition, robot cell designers experience even more challenge to consider the trade-offs between cycle time and lifetime as well as cycle time and energy efficiency. In this work, utilization of multi-objective optimization to optimal design of the work cell of an industrial robot is investigated. Solution space and Pareto front are obtained and used to demonstrate the trade-offs between cycle-time and critical component lifetime as well as cycle-time and energy efficiency of an industrial robot. Two types of multi-objective optimization have been investigated and benchmarked using optimal design problem of robotic work cells: 1) single-objective optimization constructed using Weighted Compromise Programming (WCP) of multiple objectives and 2) Pareto front optimization using multi-objective generic algorithm (MOGA-II). Of the industrial robotics significance, a combined design optimization problem is investigated, where design space consisting of design variables defining robot task placement and robot drive-train are simultaneously searched. Optimization efficiency and interesting trade-offs have been explored and successful results demonstrated.
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“Despite the merits of bioinspired optimizers, solving multiobjective problems is a huge challenge as demonstrated in different application domains (e.g. robotics [66], bioinformatics [67], energy and power [68]).”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [67]
Citations
Cites
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905
Fonseca, C. M., & Fleming, P. J. (1998) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/3468.650319 · Cited by 1,241
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Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68
Service-Oriented Reconfiguration in Systems of Systems Assured by Dynamic Modular Safety Cases
Thomas, C., Mirzaei, E., Wudka, B., Siefke, L., & Sommer, V. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-86507-8_2 · Cited by 6
Optimization-based development of ultra high performance Twin Robot Xbar press tending robot system
Feng, X., Patel, R., Pons, R., Casanelles, R., Wäppling, D., Weström, J., & Andersson, H. (2013) · IEEE International Symposium on Robotics (ISR) · doi:10.1109/isr.2013.6695702 · Cited by 2
Self-citationNew robot concept for ultra high performance press tending robot system
Platzer, M., Feng, X., Wäppling, D., Baumli, N., Patel, R., Pons, R., Casanelles, R., & Weström, J. (2013) · IEEE International Symposium on Robotics (ISR) · doi:10.1109/isr.2013.6695703 · Cited by 2
Self-citationSimulation-based Approach for Eco-optimized Production Control Systems
Brecher, C., Müller, S., Kujas, M., & Lohse, W. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.02.201
Metadata
- Authors
- Feng, X., Wa¨ppling, D., Andersson, H., O¨lvander, J., & Tarkian, M.
- Affiliations
- ABB (Sweden) (SE)
- ABB Robotics, Va¨stera˚s, Sweden
- Linköping University (SE)
- Venue
- Volume 1: 36th Design Automation Conference, Parts A and B
- Publisher
- ASMEDC
- Published
- 2010-01-01
- Pages
- 815-823
- OpenAlex
- W2070275093
- Cited by
- 5
- References
- 2
- Citations by year
- 2021: 2 · 2015: 1 · 2013: 2
- FWCI
- 0.59
- Type
- conference paper
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Mechanisms and Dynamics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Scheduling and Optimization Algorithms
- Keywords
- multi-objective optimization, Pareto front, cycle time, energy efficiency, design trade-offs
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