| 1. |
- Bengtsson, Kristofer, 1979, et al.
(author)
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Sequence Planning Using Multiple and Coordinated Sequences of Operations
- 2012
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In: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; 9:2, s. 308-319
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Journal article (peer-reviewed)abstract
- The sequential behavior of a manufacturing system results from several constraints introduced during the product, manufacturing, and control logic development. This paper proposes methods and algorithms for automatically representing and visualizing this behavior from various perspectives throughout the development process. A new sequence planning approach is introduced that uses self-contained operations to model the activities and execution constraints. These operations can be represented and visualized from multiple perspectives using a graphical and formal language called Sequences of Operations (SOPs). The operations in a manufacturing system are related to each other in various ways, due to execution constraints expressed by operation pre- and post-conditions. These operation relations include parallel, sequence, arbitrary order, alternative, and hierarchy relations. Based on the SOP language, these relations are identified and visualized in various SOPs and sequences. A software tool, Sequence Planner, has been developed, for organizing the operations into SOPs that visualize only relevant operations and relations. Note to Practitioners-This paper proposes methods and algorithms for a new sequence planning approach in which sequences are automatically created based on the relations among operations instead of having to be manually constructed. Using various views, the sequences of operations related to, for example, part flow, robot operations, and operator tasks, can be visualized. The use of various views helps the user better understand the relations between cell control and mechanical design, and between product design and total system behavior.
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| 2. |
- Bengtsson, Kristofer, 1979, et al.
(author)
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Relations Identification and Visualization for Sequence Planning and Automation Design
- 2010
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In: In Proc. IEEE Conference on Automation Science and Engineering, Toronto. - 9781424454471 ; , s. 841 - 848
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Conference paper (peer-reviewed)abstract
- The sequential behavior of a manufacturing system results from a number of constraints introduced both in product, manufacturing and control logic development. Sequence planning is therefore an important activity throughout the complete development process. This paper proposes a sequence planning approach using self-contained manufacturing operations that model actions and relevant execution conditions. These operations can have temporal relations with each other, due to execution constraints expressed by operation pre- post- and reset conditions. The operation relations can for example be parallel, sequence, arbitrary order, alternative or hierarchy. Based on a formal operation model, the relations among operations are identified and visualized with a graphical language called Sequences of Operations, SOP.
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| 3. |
- Conway, Richard, 1978-, et al.
(author)
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Realizing Dharavi
- 2017. - 1
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In: Reinventing Dharavi. - Mumbai, India : Urban Design Research Institute. - 9789381444160 ; , s. 34-61
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Book chapter (peer-reviewed)
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| 4. |
- Thorstensson, Carl, 1984, et al.
(author)
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Optimization of Discrete Event Systems Using Extended Finite Automata and Mixed-Integer Nonlinear Programming
- 2011
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In: IFAC Proceedings Volumes (IFAC-PapersOnline). - 2405-8963. - 9783902661937 ; 18:PART 1, s. 6969-6975
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Conference paper (peer-reviewed)abstract
- This paper presents a concept for converting a discrete event model, modeled with Extended Finite Automata (EFA), to mixed-integer linear constraints. The conversion handles the structure of modular EFAs, synchronization of EFAs using shared events and EFA execution order due to logical transition conditions. The paper also presents methods to reduce the number of variables and constraints by automatically analyzing the EFA model and the resulting problem formulation. An example of this is the special case of transition conditions used to model mutual exclusion of shared resources, where the conversion results in a significantly reduced problem formulation. The objective function is then built by summarizing weighted state cost functions and the result is a Mixed-Integer Nonlinear Programming problem. The main contribution of this paper is hence the combination of the simplicity in modeling a system with EFAs and an efficient formulation of the optimization problem that can be solved by standard optimization software.
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| 5. |
- Vergnano, Alberto, et al.
(author)
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Embedding detailed robot energy optimization into high-level scheduling
- 2010
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In: 2010 IEEE International Conference on Automation Science and Engineering, CASE 2010. - 9781424454471 ; , s. 386-392
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Conference paper (peer-reviewed)abstract
- Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modelled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system is presented. It shows that there exists a possibility for a significant reduction of the energy consumption, in comparison to state-of-the-art scheduling approaches. © 2010 IEEE.
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| 6. |
- Vergnano, Alberto, et al.
(author)
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Modeling and Optimization of Energy Consumption in Cooperative Multi-Robot Systems
- 2012
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In: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; 9:2, s. 423-428
-
Journal article (peer-reviewed)abstract
- Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. Note to Practitioners-The motivation for this work is the great interest of companies on energy consumption optimization, looking for cost reduction and sustainability in manufacturing. Existing optimization methods focus on different levels of details. A high-level model would be able to optimize the overall system. Unfortunately, due to the high computational cost, it can hardly consider the deep level of mechanical and electrical parameters, which determine the real energy consumption. This paper presents a novel method to embed detailed energy consumption models into a scheduling optimization problem. An effective parameterization of the time variables reduces the model complexity, allowing the optimizer to reschedule the complete sequence of operations for minimizing the total energy consumption, while keeping a fixed cycle time. The method has been integrated into a commercial tool for robot programming. The optimization is applicable both on new and existing robotic systems, since the required modifications are limited to the operations rescheduling, and no investments on new hardware are expected.
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