Browsing by Author "Oyekan, John"

Now showing 1 - 11 of 11
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    A 3D immersive discrete event simulator for enabling prototyping of factory layouts
    (Elsevier, 2015-10-27) Oyekan, John; Hutabarat, Windo; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Ince, Nadir; Gan, Xiao-Peng; Waller, Tony
    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.
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    Adapting petri nets to DES: stochastic modelling of manufacturing systems
    (D A A A M International Vienna, 2018) Simon, E.; Oyekan, John; Hutabarat, Windo; Tiwari, Ashutosh; Turner, Christopher J.
    Discrete-Event Simulation (DES) is commonly used for the simulation of manufacturing systems. In many practical cases, DES practitioners have to make simplifications or to use the software in an unconventional or convoluted fashion to meet their needs. Petri nets enable the development of transparent models which conciseness are a synonym of increased flexibility and control for designers. Furthermore, Petri nets take advantage of a solid mathematical ground and constitute a simple language. However, Petri nets lack the software capabilities to realise their full potential. This study investigates the suitability and relevance of Discrete-Event Simulation (DES) software for Petri net modelling in the context of manufacturing systems. A framework is developed for the modelling of different classes of Petri nets on DES. Analytical models of asynchronous flow lines are developed. Initial results show that the analytical models are without closed-form solution and the explosion of the state space is observed, justifying the use of computational methods and simulation for the analysis of manufacturing systems. This study shows that the gain in flexibility provided by Petri nets provides a new insight into the effects of stochasticity on setup and failure times in manufacturing systems.
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    Bio-inspired vision-based leader-follower formation flying in the presence of delays
    (M D P I AG, 2016-08-18) Oyekan, John
    Flocking starlings at dusk are known for the mesmerizing and intricate shapes they generate, as well as how fluid these shapes change. They seem to do this effortlessly. Real-life vision-based flocking has not been achieved in micro-UAVs (micro Unmanned Aerial Vehicles) to date. Towards this goal, we make three contributions in this paper: (i) we used a computational approach to develop a bio-inspired architecture for vision-based Leader-Follower formation flying on two micro-UAVs. We believe that the minimal computational cost of the resulting algorithm makes it suitable for object detection and tracking during high-speed flocking; (ii) we show that provided delays in the control loop of a micro-UAV are below a critical value, Kalman filter-based estimation algorithms are not required to achieve Leader-Follower formation flying; (iii) unlike previous approaches, we do not use external observers, such as GPS signals or synchronized communication with flock members. These three contributions could be useful in achieving vision-based flocking in GPS-denied environments on computationally-limited agents.
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    Combining virtual reality enabled simulation with 3D scanning technologies towards smart manufacturing
    (Institute of Electrical and Electronics Engineers, 2017-01-19) Hutabarat, Windo; Oyekan, John; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Gan, Xiao-Peng; Waller, Anthony
    Recent introduction of low-cost 3D sensing and affordable immersive virtual reality have lowered the barriers for creating and maintaining 3D virtual worlds. In this paper, we propose a way to combine these technologies with discrete-event simulation to improve the use of simulation in decision making in manufacturing. This work will describe how feedback is possible from real world systems directly into a simulation model to guide smart behaviors. Technologies included in the research include feedback from RGBD images of shop floor motion and human interaction within full immersive virtual reality that includes the latest headset technologies.
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    Discrete event simulation and virtual reality use in industry: new opportunities and future trends
    (Institute of Electrical and Electronics Engineers, 2016-08-18) Turner, Christopher J.; Hutabarat, Windo; Oyekan, John; Tiwari, Ashutosh
    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.
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    Gesture detection towards real-time ergonomic analysis for intelligent automation assistance
    (Springer, 2016-07-10) Mgbemena, Chika Edith; Oyekan, John; Tiwari, Ashutosh; Xu, Yuchun; Fletcher, Sarah R.; Hutabarat, Windo; Prabhu, Vinayak Ashok
    Manual handling involves transporting of load by hand through lifting or lowering and operators on the manufacturing shop floor are daily faced with constant lifting and lowering operations which leads to Work-Related Musculoskeletal Disorders. The trend in data collection on the Shop floor for ergonomic evaluation during manual handling activities has revealed a gap in gesture detection as gesture triggered data collection could facilitate more accurate ergonomic data capture and analysis. This paper presents an application developed to detect gestures towards triggering real-time human motion data capture on the shop floor for ergonomic evaluations and risk assessment using the Microsoft Kinect. The machine learning technology known as the discrete indicator—precisely the AdaBoost Trigger indicator was employed to train the gestures. Our results show that the Kinect can be trained to detect gestures towards real-time ergonomic analysis and possibly offering intelligent automation assistance during human posture detrimental tasks.
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    Impact of model fidelity in factory layout assessment using immersive discrete event simulation
    (Operational Research Society, 2016-04-13) Petti, Alessandro; Hutabarat, Windo; Oyekan, John; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Gan, Xiao-Peng
    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.
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    A model for using self-organized agents to visually map environmental profiles
    (Elsevier, 2014-06-09) Oyekan, John; Gu, Dongbing; Hu, Huosheng
    In this work, we investigate the possibility of using inspiration from the self-organizing property of organisms in nature for providing visual representation of an invisible pollutant profile. We present a novel mathematical model of the bacterium and use it to find pollutants in the environment. This model has the capability of exploring the environment to search for sparsely distributed pollutants or food sources and then subsequently exploiting them upon discovery. We also combine the bacterium model in a bacterium–flock algorithm for the purposes of preventing collisions between robots or organisms in addition to providing coverage to a pollutant. By adjusting the velocity of individuals, we show that we are able to control the coverage provided by the population as a whole. Furthermore, we compare the bacterium–flock algorithm with a novel gradient-ascent-flocking algorithm and the well established Voronoi partition algorithm. Results show that bacterium–flock algorithm and the Voronoi partition algorithm are capable of adapting the distribution of the individuals of a population based upon the underlying pollutant profile while the gradient-ascent-flocking algorithm is not. This shows that the bacterium–flock and the Voronoi partition algorithms can potentially be used to track a spatiotemporal function. On the other hand, the gradient-ascent-flock algorithm has a faster convergence time in some cases with the Voronoi partition algorithm having the slowest convergence time overall.
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    Remote Real-Time Collaboration Platform enabled by the Capture, Digitisation and Transfer of Human-Workpiece Interactions
    (Future Technology Press, 2015-12-01) Prabhu, Vinayak Ashok; Oyekan, John; Tiwari, Ashutosh; Advikolanu, Yohann; Burgess, Mark; Mcnally, Rob
    In this highly globalised manufacturing ecosystem, product design and verification activities, production and inspection processes, and technical support services are spread across global supply chains and customer networks. Therefore, a platform for global teams to collaborate with each other in real-time to perform complex tasks is highly desirable. This work investigates the design and development of a remote real-time collaboration platform by using human motion capture technology powered by infrared light based depth imaging sensors borrowed from the gaming industry. The unique functionality of the proposed platform is the sharing of physical contexts during a collaboration session by not only exchanging human actions but also the effects of those actions on the task environment. This enables teams to remotely work on a common task problem at the same time and also get immediate feedback from each other which is vital for collaborative design, inspection and verifications tasks in the factories of the future.
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    Remote real-time collaboration through synchronous exchange of digitised human-workpiece interactions
    (Elsevier, 2016-08-30) Oyekan, John; Prabhu, Vinayak Ashok; Tiwari, Ashutosh; Baskaran, Vinubha; Burgess, Mark; Mcnally, Rob
    In this highly globalised manufacturing ecosystem, product design and verification activities, production and inspection processes, and technical support services are spread across global supply chains and customer networks. Therefore, collaborative infrastructures that enable global teams to collaborate with each other in real-time in performing complex manufacturing-related tasks is highly desirable. This work demonstrates the design and implementation of a remote real-time collaboration platform by using human motion capture technology powered by infrared light based depth imaging sensors and a synchronous data transfer protocol from computer networks. The unique functionality of the proposed platform is the sharing of physical contexts during a collaboration session by not only exchanging human actions but also the effects of those actions on the workpieces and the task environment. Results show that this platform could enable teams to remotely work on a common engineering problem at the same time and also get immediate feedback from each other making it valuable for collaborative design, inspection and verifications tasks in the factories of the future. An additional benefit of the implemented platform is its use of low cost off the shelf equipment thereby making it accessible to SMEs that are connected to larger organisations via complex supply chains.
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    Tracking and sensor coverage of spatio-temporal quantities using a swarm of artificial foraging agents
    (Elsevier, 2016-11-09) Oyekan, John; Gu, D.; Hu, H.
    Using a network of mobile sensors to track and map a dynamic spatio-temporal process in the environment is one of the current challenges in multi-agent systems. In this work, a distributed probabilistic multi-agent algorithm inspired by the bacterium foraging behavior is presented. The novelty of the algorithm lies in being capable of tracking and mapping a spatio-temporal quantity without the need of machine learning, estimation algorithms or future planning. This is unlike most current techniques that rely heavily on machine learning to estimate the distribution as well as the profile of spatio-temporal quantities. The experimental studies carried out in this work show that the algorithm works well by following the concentration gradient of a dynamic plume created under diffusive conditions. Furthermore, the algorithm is inherently capable of finding the source of a diffusive spatio-temporal quantity as well as performing environmental exploration. It is computationally tractable for simple agents, shown to adapt to its environment and can deal successfully with noise in sensor readings as well as in robot dynamics.