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Glorieux, E., Franciosa, P. & Ceglarek, D. (2019). Quality and productivity driven trajectory optimisation for robotic handling of compliant sheet metal parts in multi-press stamping lines. Robotics and Computer-Integrated Manufacturing, 56, 264-275
Open this publication in new window or tab >>Quality and productivity driven trajectory optimisation for robotic handling of compliant sheet metal parts in multi-press stamping lines
2019 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 56, p. 264-275Article in journal (Refereed) Published
Abstract [en]

This paper investigates trajectory generation for multi-robot systems that handle compliant parts in order to minimise deformations during handling, which is important to reduce the risk of affecting the part’s dimensional quality. An optimisation methodology is proposed to generate deformation-minimal multi-robot coordinated trajectories for predefined robot paths and cycle-time. The novelty of the proposed optimisation methodology is that it efficiently estimates part deformations using a precomputed Response Surface Model (RSM), which is based on data samples generated by Finite Element Analysis (FEA) of the handled part and end-effector. The end-effector holding forces, plastic part deformations, collision-avoidance and multi-robot coordination are also considered as constraints in the optimisation model. The optimised trajectories are experimentally validated and the results show that the proposed optimisation methodology is able to significantly reduce the deformations of the part during handling, i.e. up to 12% with the same cycle-time in the case study that involves handling compliant sheet metal parts. This investigation provides insights into generating specialised trajectories for material handling of compliant parts that can systematically minimise part deformations to ensure final dimensional quality. © 2018

Place, publisher, year, edition, pages
Pergamon Press, 2019
Keywords
Aerodynamics, Deformation, Industrial robots, Materials handling, Multipurpose robots, Plastic parts, Robotics, Sheet metal, Trajectories, Compliant parts, Dimensional quality, Material handling, Multi-robot coordination, Multi-robot systems, Response surface modeling, Trajectory generation, Trajectory optimisation, End effectors
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-13114 (URN)10.1016/j.rcim.2018.10.004 (DOI)000451488700023 ()2-s2.0-85055719221 (Scopus ID)
Funder
Region Västra Götaland, PROSAM + RUN 612-0208-16
Note

Available online 29 October 2018.

Funders: UK EPSRC [EP/K019368/1] 

Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2018-12-13Bibliographically approved
Glorieux, E., Franciosa, P. & Ceglarek, D. (2018). End-effector design optimisation and multi-robot motion planning for handling compliant parts. Structural and multidisciplinary optimization (Print), 57(3), 1377-1390
Open this publication in new window or tab >>End-effector design optimisation and multi-robot motion planning for handling compliant parts
2018 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 57, no 3, p. 1377-1390Article in journal (Refereed) Published
Abstract [en]

The deformation of compliant parts during material handling is a critical issue that can significantly affect the productivity and the parts' dimensional quality. There are multiple relevant aspects to consider when designing end-effectors to handle compliant parts, e.g. motion planning, holding force, part deformations, collisions, etc. This paper focuses on multi-robot material handling systems where the end-effector designs influence the coordination of the robots to prevent that these collide in the shared workspace. A multi-disciplinary methodology for end-effector design optimisation and multi-robot motion planning for material handling of compliant parts is proposed. The novelty is the co-adaptive optimisation of the end-effectors' structure with the robot motion planning to obtain the highest productivity and to avoid excessive part deformations. Based on FEA, the dynamic deformations of the parts are modelled in order to consider these during the collision avoidance between the handled parts and obstacles. The proposed methodology is evaluated for a case study that considers the multi-robot material handling of sheet metal parts in a multi-stage tandem press line. The results show that a substantial improvement in productivity can be achieved (up to 1.9%). These also demonstrate the need and contribution of the proposed methodology.

Keywords
End-effector design optimisation, Motion planning, Multi-robot systems, Material handling, Compliant parts
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-11768 (URN)10.1007/s00158-017-1798-x (DOI)000429106000028 ()2-s2.0-85028954453 (Scopus ID)
Funder
Region Västra Götaland, PROSAM+ RUN 612-0208-16
Note

CC-BY http://creativecommons.org/licenses/by/4.0/First Online: 09 September 2017

Available from: 2017-10-20 Created: 2017-10-20 Last updated: 2019-05-27
Glorieux, E., Riazi, S. & Lennartson, B. (2018). Productivity/energy optimisation of trajectories and coordination for cyclic multi-robot systems. Robotics and Computer-Integrated Manufacturing, 49, 152-161
Open this publication in new window or tab >>Productivity/energy optimisation of trajectories and coordination for cyclic multi-robot systems
2018 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 49, p. 152-161Article in journal (Refereed) Published
Abstract [en]

The coordination of cyclic multi-robot systems is a critical issue to avoid collisions but also to obtain the shortest cycle-time. This paper presents a novel methodology for trajectory and coordination optimisation of cyclic multi-robot systems. Both velocity tuning and time delays are used to coordinate the robots that operate in close proximity and avoid collisions. The novel element is the non-linear programming optimisation model that directly co-adjusts the multi-robot coordination during the trajectory optimisation, which allows optimising these as one problem. The methodology is demonstrated for productivity/smoothness optimisation, and for energy efficiency optimisation. An experimental validation is done for a real-world case study that considers the multi-robot material handling system of a multi-stage tandem press line. The results show that the productivity optimisation with the methodology is competitive compared to previous research and that substantial improvements can be achieved, e.g. up to 50% smoother trajectories and 14% reduction in energy consumption for the same productivity. This paper addresses the current lack of systematic methodologies for generating optimal coordinated trajectories for cyclic multi-robot systems to improve the productivity, smoothness, and energy efficiency.

Keywords
Robot systems, Multi-robot coordination, Trajectory optimisation, Energy minimisation
National Category
Robotics
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-11263 (URN)10.1016/j.rcim.2017.06.012 (DOI)000412957500014 ()2-s2.0-85021743164 (Scopus ID)
Funder
Region Västra Götaland, PROSAM+ RUN 612-0208-16Vinnova
Available from: 2017-08-02 Created: 2017-08-02 Last updated: 2019-05-28Bibliographically approved
Glorieux, E., Svensson, B., Danielsson, F. & Lennartson, B. (2017). Constructive cooperative coevolution for large-scale global optimisation. Journal of Heuristics, 23(6), 449-469
Open this publication in new window or tab >>Constructive cooperative coevolution for large-scale global optimisation
2017 (English)In: Journal of Heuristics, ISSN 1381-1231, E-ISSN 1572-9397, Vol. 23, no 6, p. 449-469Article in journal (Refereed) Published
Abstract [en]

This paper presents the Constructive Cooperative Coevolutionary ( C3C3 ) algorithm, applied to continuous large-scale global optimisation problems. The novelty of C3C3 is that it utilises a multi-start architecture and incorporates the Cooperative Coevolutionary algorithm. The considered optimisation problem is decomposed into subproblems. An embedded optimisation algorithm optimises the subproblems separately while exchanging information to co-adapt the solutions for the subproblems. Further, C3C3 includes a novel constructive heuristic that generates different feasible solutions for the entire problem and thereby expedites the search. In this work, two different versions of C3C3 are evaluated on high-dimensional benchmark problems, including the CEC'2013 test suite for large-scale global optimisation. C3C3 is compared with several state-of-the-art algorithms, which shows that C3C3 is among the most competitive algorithms. C3C3 outperforms the other algorithms for most partially separable functions and overlapping functions. This shows that C3C3 is an effective algorithm for large-scale global optimisation. This paper demonstrates the enhanced performance by using constructive heuristics for generating initial feasible solutions for Cooperative Coevolutionary algorithms in a multi-start framework.

Keywords
Evolutionary optimisation, Cooperative coevolution, Algorithm design and analysis, Large-scale optimisation
National Category
Robotics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-11264 (URN)10.1007/s10732-017-9351-z (DOI)000414074300002 ()2-s2.0-85024487069 (Scopus ID)
Funder
Region Västra Götaland, PROSAM 612-0974-14
Available from: 2017-08-02 Created: 2017-08-02 Last updated: 2019-05-23Bibliographically approved
Glorieux, E., Svensson, B., Danielsson, F. & Lennartson, B. (2017). Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending. Engineering optimization (Print), 49(10), 1685-1703
Open this publication in new window or tab >>Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending
2017 (English)In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 49, no 10, p. 1685-1703Article in journal (Refereed) Published
Abstract [en]

This article investigates multi-objective optimization of the robot trajectories and position-based operation-coordination of complex multi-robot systems, such as press lines, to improve the production rate and obtaining smooth motions to avoid excessive wear of the robots’ components. Different functions for handling the multiple objectives are evaluated on realworld press lines, including both scalarizing single-objective functions and Pareto-based multi-objective functions. Additionally, the Multi-Objective Constructive Cooperative Coevolutionary (moC3) algorithm is proposed, for Pareto-based optimization, which uses a novel constructive initialization of the subpopulations in a co-adaptive fashion. It was found that Paretobased optimization performs better than the scalarizing single-objective functions. Furthermore, moC3 gives substantially better results compared to manual online tuning, as currently used in the industry. Optimizing robot trajectories and operation-coordination of complex multi-robot systems using the proposed method with moC3 significantly improves productivity and reduces maintenance. This article hereby addresses the lack of systematic methods for effectively improving the productivity of press lines.

Keywords
Multi-objective optimization, coevolutionary optimization, press tending, multi-robot coordination
National Category
Production Engineering, Human Work Science and Ergonomics Robotics
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-10341 (URN)10.1080/0305215X.2016.1264220 (DOI)000408952800003 ()2-s2.0-85006124128 (Scopus ID)
Note

Kolla upp ScopusID

Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2019-05-23Bibliographically approved
Glorieux, E. (2017). Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts. (Doctoral dissertation). Trollhättan: University West
Open this publication in new window or tab >>Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Motion planning for robot operations is concerned with path planning and trajectory generation. In multi-robot systems, i.e. with multiple robots operating simultaneously in a shared workspace, the motion planning also needs to coordinate the robots' motions to avoid collisions between them. The multi-robot coordination decides the cycle-time for the planned paths and trajectories since it determines to which extend the operations can take place simultaneously without colliding. To obtain the quickest cycle-time, there needs to bean optimal balance between, on the one hand short paths and fast trajectories, and on the other hand possibly longer paths and slower trajectories to allow that the operations take place simultaneously in the shared workspace. Due to the inter-dependencies, it becomes necessary to consider the path planning, trajectory generation and multi-robot coordination together as one optimisation problem in order to find this optimal balance.This thesis focusses on optimising the motion planning for multi-robot material handling systems of sheet metal parts. A methodology to model the relevant aspects of this motion planning problem together as one multi-disciplinary optimisation problem for Simulation based Optimisation (SBO) is proposed. The identified relevant aspects include path planning,trajectory generation, multi-robot coordination, collision-avoidance, motion smoothness, end-effectors' holding force, cycle-time, robot wear, energy efficiency, part deformations, induced stresses in the part, and end-effectors' design. The cycle-time is not always the (only) objective since it is sometimes equally/more important to minimise robot wear, energy consumption, and/or part deformations. Different scenarios for these other objectives are therefore also investigated. Specialised single- and multi-objective algorithms are proposed for optimising the motion planning of these multi-robot systems. This thesis also investigates how to optimise the velocity and acceleration profiles of the coordinated trajectories for multi-robot material handling of sheet metal parts. Another modelling methodology is proposed that is based on a novel mathematical model that parametrises the velocity and acceleration profiles of the trajectories, while including the relevant aspects of the motion planning problem excluding the path planning since the paths are now predefined.This enables generating optimised trajectories that have tailored velocity and acceleration profiles for the specific material handling operations in order to minimise the cycle-time,energy consumption, or deformations of the handled parts.The proposed methodologies are evaluated in different scenarios. This is done for real world industrial case studies that consider the multi-robot material handling of a multi-stage tandem sheet metal press line, which is used in the automotive industry to produce the cars' body panels. The optimisation results show that significant improvements can be obtained compared to the current industrial practice.

Place, publisher, year, edition, pages
Trollhättan: University West, 2017. p. 196
Series
PhD Thesis: University West ; 10
Keywords
Multi-robot systems, motion planning, modelling and simulation, optimisation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-10947 (URN)978-91-87531-58-3 (ISBN)978-91-87531-57-6 (ISBN)
Supervisors
Available from: 2017-05-24 Created: 2017-05-24 Last updated: 2017-05-30Bibliographically approved
Glorieux, E., Svensson, B., Parthasarathy, P. & Danielsson, F. (2016). An energy model for press line tending robots. In: José Evora-Gomez & José Juan Hernandez-Cabrera (Ed.), ESM'2016, the 2016 European simulation and Modelling Conference: Modelling and Simulation '2016. Paper presented at 30th European Simulation and Modelling Conference - ESM'2016, October 26-28, 2016, Las Palmas, Gran Canaria, Spain (pp. 377-383). Eurosis
Open this publication in new window or tab >>An energy model for press line tending robots
2016 (English)In: ESM'2016, the 2016 European simulation and Modelling Conference: Modelling and Simulation '2016 / [ed] José Evora-Gomez & José Juan Hernandez-Cabrera, Eurosis , 2016, p. 377-383Conference paper, Published paper (Refereed)
Abstract [en]

Today most industries aim at reducing energy consumption to become sustainable and environment-friendly. The automotive industry, with mass production and large volumes, is one such example. With many robots working round the clock, there is great potential to save energy. In this climate there is a need for robot simulation models that can be used for motion and task execution optimisation and which are aimed lowering energy consumption. This paper presents an energy consumption model for 2D-belt robots for press line tending in the automotive sector. The energy model is generic for 2D-belt robots and is entirely based on component specifications (e.g., dimensions, masses, inertia). An implementation and validation against a real 2D-belt tending robot used in the automotive industry is performed and presented. The purpose and usefulness of the energy model is also demonstrated by two application cases; the investigation of potential energy reductions achieved by reducing the weight of gripper tools, and by using mechanical brakes when the robot is idle.

Place, publisher, year, edition, pages
Eurosis, 2016
Keywords
Industrial robots, energy model, energy consumption, energy minimisation
National Category
Robotics
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-10133 (URN)2-s2.0-85016052034 (Scopus ID)9789077381953 (ISBN)
Conference
30th European Simulation and Modelling Conference - ESM'2016, October 26-28, 2016, Las Palmas, Gran Canaria, Spain
Note

This work was performed at University West’s Production Technology West research centre and supported in part by Västra Götalandsregionen under the grant PROSAM+ RUN 612-0208-16.

Available from: 2016-11-10 Created: 2016-11-10 Last updated: 2019-02-07Bibliographically approved
Glorieux, E., Parthasarathy, P., Svensson, B. & Danielsson, F. (2016). Energy Consumption Model for 2D-Belt Robots. In: 7th Swedish Production Symposium Conference proceedings: . Paper presented at 7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016 (pp. 1-7). Lund: SPS16
Open this publication in new window or tab >>Energy Consumption Model for 2D-Belt Robots
2016 (English)In: 7th Swedish Production Symposium Conference proceedings, Lund: SPS16 , 2016, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

Production that incorporates robotics consumes energy and the trend today is to reduce consumed energy not only to lower the cost but also to be a more energy efficient entity. Energy models can be used to predict the energy consumed by robot(s) for optimising the input parameters which determine robot motion and task execution. This paper presents an energy model to predict the energy consumption of 2D-belt robots used for press line tending. Based on the components’ specifications and the trajectory, an estimation of the energy consumption is computed. The capabilities of the proposed energy model to predict the energy consumption during the planning-phase (i.e. before installation), avoiding the need for physical experiments, are demonstrated. This includes predicting potential energy reductions achieved by reducing the weight of the gripper tools. Additionally, it is also shown how to investigate the energy saving achieved by using mechanical brakes when the robot is idle. This effectively illustrates the purpose and usefulness of the proposed energy model.

Place, publisher, year, edition, pages
Lund: SPS16, 2016
Keywords
Industrial robots, energy model, energy consumption, energy minimisation
National Category
Robotics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-10131 (URN)
Conference
7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016
Available from: 2016-11-10 Created: 2016-11-10 Last updated: 2018-08-12Bibliographically approved
Glorieux, E., Svensson, B., Danielsson, F. & Lennartson, B. (2016). Improved Constructive Cooperative Coevolutionary Differential Evolution for Large-Scale Optimisation. In: Computational Intelligence, 2015 IEEE Symposium Series on: . Paper presented at 2015 IEEE Symposium on Computational Intelligence SSCI 8-10 December 2015 Cape Town, South Africa (pp. 1703-1710). IEEE, Article ID 7376815.
Open this publication in new window or tab >>Improved Constructive Cooperative Coevolutionary Differential Evolution for Large-Scale Optimisation
2016 (English)In: Computational Intelligence, 2015 IEEE Symposium Series on, IEEE, 2016, p. 1703-1710, article id 7376815Conference paper, Published paper (Refereed)
Abstract [en]

The Differential Evolution (DE) algorithm is widely used for real-world global optimisation problems in many different domains. To improve DE's performance on large-scale optimisation problems, it has been combined with the Cooperative Coevolution (CCDE) algorithm. CCDE adopts a divide-and-conquer strategy to optimise smaller subcomponents separately instead of tackling the large-scale problem at once. DE then evolves a separate subpopulation for each subcomponent but there is cooperation between the subpopulations to co-adapt the individuals of the subpopulations with each other. The Constructive Cooperative Coevolution (C3DE) algorithm, previously proposed by the authors, is an extended version of CCDE that has a better performance on large-scale problems, interestingly also on non-separable problems. This paper proposes a new version, called the Improved Constructive Cooperative Coevolutionary Differential Evolution (C3iDE), which removes several limitations with the previous version. A novel element of C3iDE is the advanced initialisation of the subpopulations. C3iDE initially optimises the subpopulations in a partially co-adaptive fashion. During the initial optimisation of a subpopulation, only a subset of the other subcomponents is considered for the co-adaptation. This subset increases stepwise until all subcomponents are considered. The experimental evaluation of C3iDE on 36 high-dimensional benchmark functions (up to 1000 dimensions) shows an improved solution quality on large-scale global optimisation problems compared to CCDE and DE. The greediness of the co-adaptation with C3iDE is also investigated in this paper.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Benchmark testing Collaboration Complexity theory, Evolutionary computation, Optimization Partitioning, algorithms
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-8900 (URN)10.1109/SSCI.2015.239 (DOI)2-s2.0-84964940225 (Scopus ID)978-1-4799-7560-0 (ISBN)
Conference
2015 IEEE Symposium on Computational Intelligence SSCI 8-10 December 2015 Cape Town, South Africa
Available from: 2016-01-18 Created: 2016-01-18 Last updated: 2019-03-13Bibliographically approved
Glorieux, E. (2015). Constructive cooperative coevolution for optimising interacting production stations. (Licentiate dissertation). Trollhättan: University West
Open this publication in new window or tab >>Constructive cooperative coevolution for optimising interacting production stations
2015 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

Engineering problems have characteristics such as a large number of variables, non-linear, computationally expensive, complex and black-box (i.e. unknown internal structure). These characteristics prompt difficulties for existing optimisation techniques. A consequence of this is that the required optimisation time rapidly increases beyond what is practical. There is a needfor dedicated techniques to exploit the power of mathematical optimisation tosolve engineering problems. The objective of this thesis is to investigate thisneed within the field of automation, specifically for control optimisation ofautomated systems.The thesis proposes an optimisation algorithm for optimising the controlof automated interacting production stations (i.e. independent stations thatinteract by for example material handling robots). The objective of the optimisation is to increase the production rate of such systems. The non-separable nature of these problems due to the interactions, makes them hard to optimise.The proposed algorithm is called the Constructive Cooperative CoevolutionAlgorithm (C3). The thesis presents the experimental evaluation of C3, bothon theoretical and real-world problems. For the theoretical problems, C3 istested on a set of standard benchmark functions. The performance, robustness and convergence speed of C3 is compared with the algorithms. This shows that C3 is a competitive optimisation algorithm for large-scale non-separable problems.C3 is also evaluated on real-world industrial problems, concerning thecontrol of interacting production stations, and compared with other optimisation algorithms on these problems. This shows that C3 is very well-suited for these problems. The importance of considering the energy consumption and equipment wear, next to the production rate, in the objective function is also investigated. This shows that it is crucial that these are considered to optimise the overall performance of interacting production stations.

Place, publisher, year, edition, pages
Trollhättan: University West, 2015. p. 90
Series
Licentiate Thesis: University West ; 2
Keywords
Manufacturing automation, metaheuristic optimasion algorithm, optimised production technology, algorithm design and analysis, interacting production stations, sheet metal press lines
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-7685 (URN)978-91-87531-09-05 (ISBN)978-91-87531-10-1 (ISBN)
Opponent
Supervisors
Available from: 2015-06-04 Created: 2015-06-04 Last updated: 2016-02-08Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0044-2795

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