| 1. |
- Barletta, Ilaria Giovanna, 1988, et al.
(författare)
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Fostering sustainable electronic waste management through intelligent sorting equipment
- 2015
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2015-October:Special Session Presentation-Only, s. 459-461
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Konferensbidrag (refereegranskat)abstract
- Joint forces of industry and academia can pave the way to truly foster sustainability of Waste of Electric and Electronic Equipment (WEEE) management. Against this background, the WEEE ID project funded by VINNOVA (Swedish Agency for Innovation Systems) developed an intelligent, automated sorting equipment for used electronics’ segregation and grading. It prevents operators from being exposed to hazardous substances from segregation processes and enables higher recycling rates within downstream processes thanks to increased sorting efficiency and accuracy. This abstract explores how the knowledge and technology developed within the WEEE ID project may have a positive impact on WEEE (or “e-waste”) management sustainability performance.
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| 2. |
- Bengtsson, Kristofer, 1979, et al.
(författare)
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Operation Behavior Modeling using Relation Identification and Visualization Algorithms
- 2013
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; , s. 368 - 373
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Konferensbidrag (refereegranskat)abstract
- The behavior of a system can be described by a set of operations - sometimes called activities or tasks. The process to specify these operation seems to be a real challenge in various situations, for example when designing automation systems or keeping track of the work at an emergency department. In practice, operation behavior specification is often quite inflexible because every possible execution route is explicitly defined. In this paper, a modeling method and a relation identification and visualization algorithm is introduced that does not explicitly specify operation routes, where instead the operation behavior is specified using the execution restrictions in transition conditions for each operation. This enables the possibility to create multiple projections of the operation relations to enable better understanding.
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| 3. |
- Bergagård, Patrik, 1984, et al.
(författare)
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Deadlock avoidance for multi product manufacturing systems modeled as sequences of operations
- 2012
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. - 9781467304290 ; , s. 515 - 520
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Konferensbidrag (refereegranskat)abstract
- This paper demonstrates how industrial models of the sequential order between manufacturing operations may be connected with academic resource deadlock avoidance policies. Given a set of product types each modeled as a sequence of operations, the operations can be adapted to control concurrent manufacturing of multiple product instances, without resource deadlocks and with maximal flexibility. The given sequences of operations may contain routing flexibility, conjunctive and/or disjunctive resource requirements, and product assembly. Using a known deadlock avoidance approach, this paper presents how to transform the given operations into models required for the deadlock avoidance approach and how the calculated policy may be retransformed back into the operations.
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| 4. |
- Bergagård, Patrik, 1984, et al.
(författare)
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On restart of automated manufacturing systems using restart states
- 2015
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. - 9781467381833 ; 2015-October, s. 166-167
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Konferensbidrag (refereegranskat)abstract
- Highly automated manufacturing systems have gained industrial popularity for their ability to combine high product volumes with high product quality. The high cost of investment in combination with many linked manufacturing systems in a factory, requires that the production runs smoothly with high utilization of the resources and that stoppages are avoided. One major reason for stoppages is the occurrence of errors. A wide variety of possible faults, such as badly fixated parts, broken actuators, and teething problems in the system, may cause errors that lead to an unsynchronization between the control system and the physical system that consequently lead to production stoppages [1,2]. The succeeding error recovery is often a complex and thereby time consuming process that typically requires operator involvement [3]. To plan for restart after errors already during the development of the system would therefore greatly support the online restart process and reduce the time the production is undesirably stopped. The common industrial practice to deal with such non-intended progress is to extend the control system with tailor-made solutions to account for foreseen errors [4,5]. This extension is both time consuming and there is no guarantee that all relevant errors are handled.
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| 5. |
- Berlin, Jonas, et al.
(författare)
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Trajectory Generation for Mobile Robots in a Dynamic Environment using Nonlinear Model Predictive Control
- 2021
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2021-August, s. 942-947
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Konferensbidrag (refereegranskat)abstract
- This paper presents an approach to collision-free, long-range trajectory generation for a mobile robot in an industrial environment with static and dynamic obstacles. For the long-range planning a visibility graph together with A is used to find a collision-free path with respect to the static obstacles. This path is used as a reference path to the trajectory planning algorithm that in addition handles dynamic obstacles while complying with the robot dynamics and constraints. A Nonlinear Model Predictive Control (NMPC) solver generates a collision-free trajectory by staying close to the initial path but at the same time obeying all constraints. The NMPC problem is solved efficiently by leveraging the new numerical optimization method Proximal Averaged Newton for Optimal Control (PANOC). The algorithm was evaluated by simulation in various environments and successfully generated feasible trajectories spanning hundreds of meters in a tractable time frame.
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| 6. |
- Bertilsson, Filip, et al.
(författare)
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Centralized versus Distributed Nonlinear Model Predictive Control for Online Robot Fleet Trajectory Planning
- 2022
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2022-August, s. 701-706
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Konferensbidrag (refereegranskat)abstract
- In this paper, we formulate and evaluate a centralized vs. a distributed approach for online trajectory generation for a fleet of mobile robots in the presence of static and dynamic obstacles. Due to dynamic obstacles, the trajectories need to be updated online and this is formulated as a nonlinear model predictive control problem. We show that both centralized and distributed MPC solvers manage to generate smooth collision-free trajectories. The distributed approach is shown to scale to many robots very well. In contrast, the computational cost of the centralized approach increases with the number of robots. However, the trajectories generated by the distributed control approach have larger deviations than those generated by the centralized approach. The experiments suggest that the centralized method should be chosen with sufficient computation resource while the distributed approach is a viable alternative when the number of robots is considerable.
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| 7. |
- Björkenstam, Staffan C, 1981, et al.
(författare)
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Energy Efficient and Collision Free Motion of Industrial Robots using Optimal Control
- 2013
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089.
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Konferensbidrag (refereegranskat)abstract
- In a production plant for complex assembled products there could be up to several hundred of robots used for handling and joining operations. Thus, improvement in robot motions can have a huge impact on equipment utilization and energy consumption. These are two of the most important aspects of sustainability in a production system. Therefore, this paper presents an algorithm for generating efficient and collision free motion of industrial robots using path planning and direct transcription methods for numerical optimal control. As a measure of efficiency for moving between configurations we use a combination of the energy norm of the applied actuator torques and the cycle time. Velocity and torque limits are handled and modeled as hard constraints. However, more general problems can be solved by the same approach. Our novel algorithm solves the problem in three steps; (i) first a path planning algorithm calculates an initial collision free path, (ii) a convex optimal control problem is then formulated to follow this path, and finally (iii) a nonlinear optimal control problem is solved to iteratively improve the trajectory. The resulting trajectory is guaranteed to be collision free by restrictions in the configuration space based on a local sensitivity analysis. The algorithm has been successfully applied to several industrial cases demonstrating that the proposed method can be used effectively in practical applications.
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| 8. |
- Björkenstam, Staffan C, 1981, et al.
(författare)
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Exploiting sparsity in the discrete mechanics and optimal control method with application to human motion planning
- 2015
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. - 9781467381833 ; 2015-October, s. 769-774
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Konferensbidrag (refereegranskat)abstract
- The discrete equations of motion derived using a variational principle are particularly attractive to be used in numerical optimal control methods. This is mainly because: i) they exhibit excellent energy behavior, ii) they extend gracefully to systems with holonomic constraints and iii) they admit compact representation of the discrete state space. In this paper we propose the use of sparse finite differencing techniques for the Discrete Mechanics and Optimal Control method. In particular we show how to efficiently construct estimates of the Jacobian and Hessian matrices when the dynamics of the optimal control problem is discretized using a variational integrator. To demonstrate the effectiveness of this scheme we solve a human motion planning problem of an industrial assembly task, modeled as a multibody system consisting of more than one hundred degrees of freedom.
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| 9. |
- Cronrath, Constantin Christian Justin, 1990, et al.
(författare)
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Energy reduction in paint shops through energy-sensitive on-off control
- 2016
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. - 9781509024094 ; 2016-November, s. 1282-1288
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Konferensbidrag (refereegranskat)abstract
- Energy efficiency is the key for a sustainable manufacturing. However, energy efficiency measures often struggle with barriers, which inhibit their implementation. Environmental discrete event simulation is an approach increasingly discussed in research to overcome such barriers. Paint shops, which are responsible for 50-70% of an assembly plant's energy utilization in vehicular manufacturing, are seldom considered in this research, though. Therefore, the specific requirements on an energy consumption model for painting systems were investigated and implemented in simulation software. In addition, an energy-sensitive algorithm is proposed to reveal energy efficiency potentials based on an on-off control strategy. The result is a comprehensive simulation concept, that contributes to the removal of energy efficiency barriers by enabling a detailed evaluation of improvement measures and by indicating worthwhile saving potentials. A case study for a typical paint shop shows that the total energy saving potential is 7% in total, corresponding to more than 300 MWh of annual savings. © 2016 IEEE.
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| 10. |
- Cronrath, Constantin, 1990, et al.
(författare)
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Enhancing digital twins through reinforcement learning
- 2019
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2019-August, s. 293-298
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Konferensbidrag (refereegranskat)abstract
- Digital Twins are core enablers of smart and autonomous manufacturing systems. Although they strive to represent their physical counterpart as accurately as possible, slight model or data errors will remain. We present an algorithm to compensate for those residual errors through Reinforcement Learning (RL) and data fed back from the manufacturing system. When learning, the Digital Twin acts as teacher and safety policy to ensure minimal performance. We test the algorithm in a sheet metal assembly context, in which locators of the fixture are optimally adjusted for individual assemblies. Our results show a fast adaption and improved performance of the autonomous system.
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