Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

An integrated representation scheme for assembly sequence planning and assembly line balancing

In a typical assembly optimisation, Assembly Sequence Planning and Assembly Line Balancing are performed independently. However, competition has compelled the manufacturer to innovate by integrating the optimisation of both problems. To incorporate ASP and ALB optimisations into a single integrated optimisation, a clear prerequisite is the availability of integrated ASP and ALB representation. Although many assembly representation works has been proposed, none of them fully meet the requirements of integrated optimisation because they were developed independently from various needs. In this paper, an integrated representation scheme for ASP and ALB that incorporate essential optimisation information is developed. The proposed representation scheme is built based on assembly tasks and represented using precedence graph and data matrix. The outcome from presented example showed that the information for ASP and ALB optimisation can be integrated and represented using task based precedence graph and data matrix, without discarding important attributes

Intelligent composite layup by the application of low cost tracking and projection technologies

Hand layup is still the dominant forming process for the creation of the widest range of complex geometry and mixed material composite parts. However, this process is still poorly understood and informed, limiting productivity. This paper seeks to address this issue by proposing a novel and low cost system enabling a laminator to be guided in real-time, based on a predetermined instruction set, thus improving the standardisation of produced components. Within this paper the current methodologies are critiqued and future trends are predicted, prior to introducing the required input and outputs, and developing the implemented system. As a demonstrator a U-Shaped component typical of the complex geometry found in many difficult to manufacture composite parts was chosen, and its drapeability assessed by the use of a kinematic drape simulation tool. An experienced laminator's knowledgebase was then used to divide the tool into a finite number of features, with layup conducted by projecting and sequentially highlighting target features while tracking a laminator's hand movements across the ply. The system has been implemented with affordable hardware and demonstrates tangible benefits in comparison to currently employed laser-based systems. It has shown remarkable success to date, with rapid Technology Readiness Level advancement. This is a major stepping stone towards augmenting manual labour, with further benefits including more appropriate automation

Multi-objective discrete particle swarm optimisation algorithm for integrated assembly sequence planning and assembly line balancing

In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set

Comparison of sequential and integrated optimisation approaches for ASP and ALB

Combining Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) is now of increasing interest. The customary approach is the sequential approach, where ASP is optimised before ALB. Recently, interest in the integrated approach has begun to pick up. In an integrated approach, both ASP and ALB are optimised at the same time. Various claims have been made regarding the benefits of integrated optimisation compared with sequential optimisation, such as access to a larger search space that leads to better solution quality, reduced error rate in planning and expedited product time-to-market. These benefits are often cited but no existing work has substantiated the claimed benefits by publishing a quantitative comparison between sequential and integrated approaches. This paper therefore compares the sequential and integrated optimisation approaches for ASP and ALB using 51 test problems. This is done so that the behaviour of each approach in optimising ASP and ALB problems at different difficulty levels can be properly understood. An algorithm named Multi-Objective Discrete Particle Swarm Optimisation (MODPSO) is applied in both approaches. For ASP, the optimisation results indicate that the integrated approach is suitable to be used in small and medium-sized problems, according to the number of non-dominated solution and error ratio indicators. Meanwhile, the sequential approach converges more quickly in large-sized problems. For pure ALB, the integrated approach is preferable in all cases. When both ASP and ALB are considered, the integrated approach is superior to the sequential approach

Impact of model fidelity in factory layout assessment using immersive discrete event simulation

Discrete Event Simulation (DES) can help speed up the layout design process. It offers further benefits when combined with Virtual Reality (VR). The latest technology, Immersive Virtual Reality (IVR), immerses users in virtual prototypes of their manufacturing plants to-be, potentially helping decision-making. This work seeks to evaluate the impact of visual fidelity, which refers to the degree to which objects in VR conforms to the real world, using an IVR visualisation of the DES model of an actual shop floor. User studies are performed using scenarios populated with low- and high-fidelity models. Study participant carried out four tasks representative of layout decision-making. Limitations of existing IVR technology was found to cause motion sickness. The results indicate with the particular group of naïve modellers used that there is no significant difference in benefits between low and high fidelity, suggesting that low fidelity VR models may be more cost-effective for this group

Utilising low cost RGB-D cameras to track the real time progress of a manual assembly sequence

Purpose The purpose of this paper is to explore the role that computer vision can play within new industrial paradigms such as Industry 4.0 and in particular to support production line improvements to achieve flexible manufacturing. As Industry 4.0 requires “big data”, it is accepted that computer vision could be one of the tools for its capture and efficient analysis. RGB-D data gathered from real-time machine vision systems such as Kinect ® can be processed using computer vision techniques. Design/methodology/approach This research exploits RGB-D cameras such as Kinect® to investigate the feasibility of using computer vision techniques to track the progress of a manual assembly task on a production line. Several techniques to track the progress of a manual assembly task are presented. The use of CAD model files to track the manufacturing tasks is also outlined. Findings This research has found that RGB-D cameras can be suitable for object recognition within an industrial environment if a number of constraints are considered or different devices/techniques combined. Furthermore, through the use of a HMM inspired state-based workflow, the algorithm presented in this paper is computationally tractable. Originality/value Processing of data from robust and cheap real-time machine vision systems could bring increased understanding of production line features. In addition, new techniques that enable the progress tracking of manual assembly sequences may be defined through the further analysis of such visual data. The approaches explored within this paper make a contribution to the utilisation of visual information “big data” sets for more efficient and automated production

Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing

In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set

A 3D immersive discrete event simulator for enabling prototyping of factory layouts

There is an increasing need to eliminate wasted time and money during factory layout design and subsequent construction. It is presently difficult for engineers to foresee if a certain layout is optimal for work and material flows. By exploiting modelling, simulation and visualisation techniques, this paper presents a tool concept called immersive WITNESS that combines the modelling strengths of Discrete Event Simulation (DES) with the 3D visualisation strengths of recent 3D low cost gaming technology to enable decision makers make informed design choices for future factories layouts. The tool enables engineers to receive immediate feedback on their design choices. Our results show that this tool has the potential to reduce rework as well as the associated costs of making physical prototypes

Survey on the use of computational optimisation in UK engineering companies

The aim of this work is to capture current practices in the use of computational optimisation in UK engineering companies and identify the current challenges and future needs of the companies. To achieve this aim, a survey was conducted from June 2013 to August 2013 with 17 experts and practitioners from power, aerospace and automotive Original Equipment Manufacturers (OEMs), steel manufacturing sector, small- and medium-sized design, manufacturing and consultancy companies, and optimisation software vendors. By focusing on practitioners in industry, this work complements current surveys in optimisation that have mainly focused on published literature. This survey was carried out using a questionnaire administered through face-to-face interviews lasting around 2 h with each participant. The questionnaire covered 5 main topics: (i) state of optimisation in industry, (ii) optimisation problems, (iii) modelling techniques, (iv) optimisation techniques, and (v) challenges faced and future research areas. This survey identified the following challenges that the participant companies are facing in solving optimisation problems: large number of objectives and variables, availability of computing resources, data management and data mining for optimisation workflow, over-constrained problems, too many algorithms with limited help in selection, and cultural issues including training and mindset. The key areas for future research suggested by the participant companies are as follows: handling large number of variables, objectives and constraints particularly when solution robustness is important, reducing the number of iterations and evaluations, helping the users in algorithm selection and business case for optimisation, sharing data between different disciplines for multi-disciplinary optimisation, and supporting the users in model development and post-processing through design space visualisation and data mining