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  • 1.
    Glorieux, Emile
    University West, Department of Engineering Science, Division of Automation Systems.
    Constructive cooperative coevolution for optimising interacting production stations2015Licentiate 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.

  • 2.
    Glorieux, Emile
    University West, Department of Engineering Science, Division of Production System.
    Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts2017Doctoral 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.

  • 3.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation Systems.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Automation Systems. University West, Department of Engineering Science, Division of Production Systems. Chalmers University of Technology, Department of Signals and Systems, Gothenburg, Sweden.
    Constructive cooperative coevolutionary optimisation for interacting production stations2015In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 78, no 1-4, p. 673-688Article in journal (Refereed)
    Abstract [en]

    Optimisation of the control function for multiple automated interacting production stations is a complex problem, even for skilled and experienced operators or process planners. When using mathematical optimisation techniques, it often becomes necessary to use simulation models to represent the problem because of the high complexity (i.e. simulation-based optimisation). Standard optimisation techniques are likely to either exceed the practical time frame or under-perform compared to the manual tuning by the operators or process planners. This paper presents the Constructive cooperative coevolutionary (C3) algorithm, which objective is to enable effective simulation-based optimisation for the control of automated interacting production stations within a practical time frame. C3 is inspired by an existing cooperative coevolutionary algorithm. Thereby, it embeds an algorithm that optimises subproblems separately. C3 also incorporates a novel constructive heuristic to find good initial solutions and thereby expedite the optimisation. In this work, two industrial optimisation problems, involving interaction production stations, with different sizes are used to evaluate C3. The results illustrate that with C3, it is possible to optimise these problems within a practical time frame and obtain a better solution compared to manual tuning.

  • 4.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation Systems.
    Lennartson, Bengt
    Chalmers University of Technology, Department of Signals and Systems.
    Optimisation of Interacting Production Stations using a Constructive Cooperative Coevolutionary Approach2014In: Proceedings of 2014 IEEE International Conference on Automation Science and Engineering (CASE), IEEE conference proceedings, 2014, p. 322-327Conference paper (Refereed)
    Abstract [en]

    Simulation-based optimisation carries the burden of computationally expensive fitness calculations. It is very often used to tackle large-scale optimisation problems with a relatively high level of complexity. Therefore, it is of interest to have optimisation techniques dedicated to simulation-based optimisation. This paper proposes a simulation-based optimisation approach, called Constructive Cooperative Coevolutionary (C3) search procedure, to optimise the control of interacting production stations. An optimisation algorithm is embedded in the C3 search procedure to optimise subproblems separately. It includes a novel constructive heuristic that creates a feasible solution for the considered problem efficiently. It also incorporates an extended version of the existing cooperative coevolutionary method that can handle large-scale optimisation problems. Furthermore, this paper presents a case study considering a sheet metal press line as an example of interacting production stations. In this case study, the performance of the proposedC3 search procedure is evaluated and compared with other optimisation algorithms. This shows that the C3 search procedure is able to successfully optimise the press line within a given number of fitness calculations, outperforming existing algorithms. Also, it is shown that C3 can be embedded with either stochastic or deterministic optimisation algorithms, without sacrificing performance.

  • 5.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Franciosa, Pasquale
    University of Warwick, Warwick Manufacturing Group, CV4 7AL Coventry, UK.
    Ceglarek, Darek
    Warwick Manufacturing Group, University of Warwick, CV4 7AL Coventry, UK.
    End-effector design optimisation and multi-robot motion planning for handling compliant parts2018In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 57, no 3, p. 1377-1390Article in journal (Refereed)
    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.

  • 6.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production System.
    Franciosa, Pasquale
    University of Warwick, Warwick Manufacturing Group (WMG), Coventry, CV4 7AL, United Kingdom.
    Ceglarek, Dariusz
    University of Warwick, Warwick Manufacturing Group (WMG), Coventry, CV4 7AL, United Kingdom.
    Quality and productivity driven trajectory optimisation for robotic handling of compliant sheet metal parts in multi-press stamping lines2019In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 56, p. 264-275Article in journal (Refereed)
    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

  • 7.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production System.
    Parthasarathy, Prithwick
    University West, Department of Engineering Science, Division of Production System.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Production System.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production System.
    Energy Consumption Model for 2D-Belt Robots2016In: 7th Swedish Production Symposium Conference proceedings, Lund: SPS16 , 2016, p. 1-7Conference 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.

  • 8.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Riazi, Sarmad
    Department of Signals and Systems, Chalmers University of Technology, S-412 96 Gothenburg, Sweden.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Production Systems. Department of Signals and Systems, Chalmers University of Technology, S-412 96 Gothenburg, Sweden.
    Productivity/energy optimisation of trajectories and coordination for cyclic multi-robot systems2018In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 49, p. 152-161Article in journal (Refereed)
    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.

  • 9.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation and Computer Engineering.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation and Computer Engineering.
    Lennartson, Bengt
    University West, Department of Technology, Mathematics and Computer Science, Division for Electrical Engineering and Land Surveying. University West, Department of Engineering Science, Division of Production Systems. Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden.
    A Constructive Cooperative Coevolutionary Algorithm Applied to Press Line Optimisation2014In: Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing: Capturing Competitive Advantage via Advanced Manufacturing and Enterprise Transformation / [ed] F. Frank Chen, Lancaster, PA, USA: DEStech Publications, Inc. , 2014, p. 909-916Conference paper (Refereed)
    Abstract [en]

    Simulation-based optimisation often considers computationally expensive problems. Successfully optimising such large scale and complex problems within a practical time frame is a challenging task. Optimisation techniques to fulfil this need to be developed. A technique to address this involves decomposing the considered problem into smaller subproblems. These subproblems are then optimised separately. In this paper, an efficient algorithm for simulation-based optimisation is proposed. The proposed algorithm extends the cooperative coevolutionary algorithm, which optimises subproblems separately. To optimise the subproblems, the proposed algorithm enables using a deterministic algorithm, next to stochastic genetic algorithms, getting the flexibility of using either type. It also includes a constructive heuristic that creates good initial feasible solutions to reduce the number of fitness calculations. The extension enables solving complex, computationally expensive problems efficiently. The proposed algorithm has been applied on automated sheet metal press lines from the automotive industry. This is a highly complex optimisation problem due to its non-linearity and high dimensionality. The optimisation problem is to find control parameters that maximises the line’s production rate. These control parameters determine velocities, time constants, and cam values for critical interactions between components. A simulation model is used for the fitness calculation during the optimisation. The results show that the proposed algorithm manages to solve the press line optimisation problem efficiently. This is a step forward in press line optimisation since this is to the authors’ knowledge the first time a press line has been optimised efficiently in this way.

  • 10.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Production Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Production Systems. Department of Signals and Systems, Chalmers University of Technology, S-412 96 Gothenburg, Sweden.
    Constructive cooperative coevolution for large-scale global optimisation2017In: Journal of Heuristics, ISSN 1381-1231, E-ISSN 1572-9397, Vol. 23, no 6, p. 449-469Article in journal (Refereed)
    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.

  • 11.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation Systems.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Automation Systems. University West, Department of Engineering Science, Division of Production Systems. Department of Signals and systems, Chalmers University of Technology.
    Improved Constructive Cooperative Coevolutionary Differential Evolution for Large-Scale Optimisation2016In: Computational Intelligence, 2015 IEEE Symposium Series on, IEEE, 2016, p. 1703-1710, article id 7376815Conference 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.

  • 12.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Production Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Production Systems. Department of Signals and Systems, Chalmers University of Technology,Gothenburg, Sweden.
    Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending2017In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 49, no 10, p. 1685-1703Article in journal (Refereed)
    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.

  • 13.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation and Computer Engineering.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Manufacturing Processes. University West, Department of Engineering Science, Division of Production Systems. Chalmers.
    Optimised Control of Sheet Metal Press Lines2014In: Proceedings of the 6th International Swedish Production Symposium 2014 / [ed] Stahre, Johan, Johansson, Björn & Björkman, Mats, 2014, p. 1-9Conference paper (Refereed)
    Abstract [en]

    Determining the control parameters for sheet metal press lines is a large scale and complex optimisation problem. These control parameters determine velocities, time constants, and cam values of critical interactions between the equipment. The complexity of this problem is due to the nonlinearities and high dimensionality. Classical optimisation techniques often underperform in solving this kind of problems within a practical timeframe. Therefore, specialised techniques need to be developed for these problems. An existing approach is simulation-based optimisation, which is to use a simulation model to evaluate the trial solutions during the optimisation. In this paper, an efficient simulation-based optimisation algorithm for large scale and complex problems is proposed. The proposed algorithm extends the cooperative coevolutionary algorithm, which optimises subproblems separately. Hence, the optimisation problem must be decomposed into subproblems that can be evaluated separately. To optimise the subproblems, the proposed algorithm allows using embedded deterministic algorithms, next to stochastic genetic algorithms, getting the flexibility of using either type. It also includes a constructive heuristic that creates good initial feasible solutions to expedite the optimisation. The extension enables solving complex, computationally expensive problems efficiently. The proposed algorithm has been applied on an automated sheet metal press line from the automotive industry. The objective is to find control parameters that maximise the line’s production rate. The results show that the proposed algorithm manages to find optimal control parameters efficiently within the practical timeframe. This is a step forward in press line optimisation since to the authors’ knowledge this is the first time a press line has been optimised efficiently in this way.

  • 14.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Automation Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Automation Systems.
    Lennartson, Bengt
    University West, Department of Engineering Science, Division of Automation Systems. University West, Department of Engineering Science, Division of Production Systems.
    Simulation-based Time and Jerk Optimisation for Robotic Press Tending2015In: Modellling and Simulation: The European simulation and modelling conference 2015, ESM 2015, Ostende: ESM , 2015, p. 377-384Conference paper (Refereed)
    Abstract [en]

    Increased production rate and robot motion smoothness in a sheet metal press line are essential. Smooth robot motions avoid unplanned production interruptions and excessive wear of the robots. Reaching high production rate and smooth motions requires tuning of the tending press robot control to minimise the cycle time and jerk. Doing this for a press line with multiple robots is a complex large-scale problem. To model such problems for the optimisation process, computer simulations become almost essential. This work presents simulation-based optimisation of the time and jerk of robotic press tending operations and investigates the importance of including the robot motion’s smoothness. An optimiser works in concert with a simulation model of a sheet metal press line and its parametrised control system. The effect of including jerk minimisation in the objective function is tested on a real-world problem concerning a sheetmetal press line. The results illustrate the importance of including jerk-minimisation as an objective in the optimisation.Furthermore, the performance of this approach is compared with manual tuning by experienced operators. The results show that the proposed simulation-based optimisation approach outperforms manual tuning.

  • 15.
    Glorieux, Emile
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Svensson, Bo
    University West, Department of Engineering Science, Division of Production Systems.
    Parthasarathy, Prithwick
    University West, Department of Engineering Science, Division of Production Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    An energy model for press line tending robots2016In: 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 (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.

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