Vu Le

Simulation-based Input Loading Condition Optimisation of Airport Baggage Handling Systems

Scheduling check-in station operations are a challenging problem within airport systems. Prior to determining check-in resource schedules, an important step is to estimate the Baggage Handling System (BHS) operating capacity under non-stationary conditions. This ensures that check-in stations are not overloaded with bags, which would adversely affect the system and cause cascade stops and blockages. Cascading blockages can potentially lead to a poor level of service and in worst scenario a customer may depart without their bags. This paper presents an empirical study of a multiobjective problem within a BHS system. The goal is to estimate near optimal input operating conditions, such that no blockages occurs at check-in stations, while minimising the baggage travel time and maximising the throughput performance measures. We provide a practical hybrid simulation and binary search technique to determine a near optimal input throughput operating condition. The algorithm generates capacity constraint information that may be used by a scheduler to plan check-in operations based on flight arrival schedules.

A generalised data analysis approach for baggage handling systems simulation

Airport baggage handling systems are a critical infrastructure component within major airports, and essential to ensure smooth luggage transfer while preventing dangerous material being loaded onto aircraft. This paper proposes a standard set of measures to assess the expected performance of a baggage handling system through discrete event simulation. These evaluation methods also have application in the study of general network systems. Results from the application of these methods reveal operational characteristics of the studied BHS, in terms of metrics such as peak throughput, in-system time and system recovery time.

Discrete Event Simulation Enabled High Level Emulation of a Distribution Centre

Emulation facilitates the testing of control systems through the use of a simulation model. Typically emulation has focused on low level control, to ensure that resources within a system are commissioned correctly. Higher level control that deals with complex issues such as throughput, in-system time and stacking, has not received as much attention. In this paper, a higher level agent-based emulation framework was proposed. Then an emulation model for a distribution centre is described that can test distribution centre level algorithms directly. This methodology also allows playback of real world operations, making it an ideal tool to analyse problems with performance of commissioned systems.

A haptic training environment for the heart myoblast cell injection procedure

The heart muscle of a cardiac arrest victim continues to accumulate damage throughout its lifetime. This reduces the hearts ability to pump sufficient oxygen and nutrient blood to meet the bodys needs. Medical researchers have shown that direct injection of pre-harvested skeletal myoblast cells into the heart can restore some muscle function [1]. This operative procedure usually necessitates the surgeon to open a patients chest. The open chest procedure is usually a lengthy process and often extends the recovery time of the patient. Alternatively, a high accuracy surgical aid robotic system can be used to assist the thoracoscopic surgery [2][3]. While the robotic surgical method aids faster patient recovery, a less experienced surgeon can potentially cause damage to surrounding tissue. This paper presents a study into the development of a virtual haptically-enabled heart myoblast injection simulation environment, which can be used to train new surgeons to get hands on experience with the process. The paper also discusses the development of a generic constraint motion technique for needle insertion. Experiments on human performance measures and efficacy, while interacting with haptic feedback training models, are also presented. The experiment involved 10 operators, with each person repeating the needle insertion and injection 10 times. A notable improvement in the task execution time with the number of repetitions was observed. Operators improved their time by up to 300% compared to their first training attempt for a static heart scenario. Under a dynamic heart motion, operators performance was slightly lower, with the successful rate of completing the experiment reduced from 84% to 75%.

A dynamic architecture for increased passenger queue model fidelity

This study presents a dynamic queue controller to generate realistic queue formation and behaviour within a discrete event environment and a new data set to define passenger walking speeds. This new controller provides a detailed visual reference of the queue behaviour and provides information on important metrics, such as queue size. The controller, combined with the walking speed data, is validated against CCTV footage of airport passenger screening points, and the simulation outputs are compared to results obtained from queueing theory. A simulation approach provides superior results over the averaged results from queuing theory and a more useful insight into the behaviour of the system.

Future Integrated Factories: A System of Systems Engineering Perspective

The manufacturing sector has gone through tremendous change in the last decade. We have witnessed the transformation from stand alone, manual processes to smart and integrated systems, from hand written reports to interactive computer-based dashboards.

Simulation-Based Knowledge Management in Airport Operations

Capturing and retaining knowledge in any organization is a major challenge. This talk describes how these challenges have been addressed through simulation and modeling techniques for complex engineered systems. A series of case studies that focus on airport processes are used to demonstrate the concepts. Furthermore, the additional benefits that a simulation model can bring, through online control and decision-making support, are discussed.

A dynamic time warped clustering technique for discrete event simulation-based system analysis

A novel method for discrete event simulation output analysis is proposed.The proposed method combines dynamic time warping and clustering to identify system behaviour.A case study of a baggage handling system is presented to demonstrate the proposed approach. This paper introduces a novel approach for discrete event simulation output analysis. The approach combines dynamic time warping and clustering to enable the identification of system behaviours contributing to overall system performance, by linking the clustering cases to specific causal events within the system. Simulation model event logs have been analysed to group entity flows based on the path taken and travel time through the system. The proposed approach is investigated for a discrete event simulation of an international airport baggage handling system. Results show that the method is able to automatically identify key factors that influence the overall dwell time of system entities, such as bags that fail primary screening. The novel analysis methodology provides insight into system performance, beyond that achievable through traditional analysis techniques. This technique also has potential application to agent-based modelling paradigms and also business event logs traditionally studied using process mining techniques.

Dynamic control of skilled and unskilled labour task assignments

Efficient allocation of skilled and non-skilled workers allow a company to improve productivity and usually requires an understanding of personnel capability, operating conditions and resource availability. This paper examines a labour control strategy that optimises labour skill level, utilisation, task execution time and processing error. The proposed controller manages different labour groups in a multiple work cell environment, providing real-time job assignment, as well as guiding and navigation features. These features can be used to enhance the performance of existing MRP-based or Just-In-Time production systems. A discrete event simulation-based manufacturing model has been developed to assess the performance of the labour controller. Experiments conducted for the selected production scenarios have demonstrated a productivity improvement when using the proposed control. A second experiment has shown that when a skilled labour uses the labour controller to guide them through the job, their utilisation also increases. The proposed controller also has potential application in other domains, such as minimising the shopping time at a supermarket.

Complex simulation of stockyard mining operations

Conflicts between resources in stockyards cause mining companies millions of dollars a year. An effective planning strategy needs to be established in order to reduce these operational conflicts. In this research a stockyard simulation model of a mining operation is proposed. The simulation uses discrete event and continuous strategies to create a high detail level of visualization and animation that closely resemble actual stockyard operation. The proposed simulation model is tightly integrated with a stockpile planner and it is used to evaluate the feasibility of a given production plan. The high detail visualization of the simulation model allows planner to determine the source of conflict, which can be used to guide the elimination of these conflicts.