There has never been as keen a spotlight on health service performance and efficiency as there is now. Waiting lists, along with patient choice, are policy areas whose measurement - and the ability to study the effects of change on waiting times, for example - is of critical importance. Discrete event simulation models, developed at Lancaster University using Micro Saint® Sharp from Adept Scientific, are providing health service managers with the tools to increase efficiency and reduce costs around patient flows.
The field element of the U.S. Army Research Lab (ARL) at For Hauchuca, Arizona is concerned with the manning required to operate the close-range Tactical Unmanned Aerial Vehicle (TUAV). The operational requirements of the TUAV operators may include extended duty days, reduced crew size and varying shift schedules. These conditions are likely to reduce operator effectiveness due to fatigue. The objective of this study was to analyze how fatigue, crew size, and rotation schedule affect operator workload and performance during the control of a TUAV. The conclusions from executing the models indicate that reducing the number of operators currently recommended for the control of TUAVs resulted in
- 33% more aerial vehicle (AV) mishaps during emergencies
- 13% increase in the time it takes to search for targets
- 11% decrease in the number of targets detected
Over 400 mission scenario replications of the model were executed allowing statistically reliable predictions to be made of the effect of operator fatigue on performance. Discrete Event Simuation (DES) models may provide a cost effective means to estimate the impact of human limitations on military systems and highlight performance areas needing attention.
Healthcare is a rapidly chaning industry, and facilities are stuggling to find tools to enhance their ability to keep up with the change. Healthcare staff have generally adapted well, however are rarely in agreement as to how to migrate to a new environment, whether physical, functional or both. Simuation allow significant exploration of multiple options, without spending enormous amounts of money on staff, training, equipment, and most importantly, without risking possible degradation in the level of healthcare. This paper will describe the use of simulation in pre-op prodedures, space utilisation and outpatient studies.
Human performance is a critical aspect of system performance. Recently, tools and methods for modelling the human in systems have begun to receive widespread attention. These tools and methods are consistent with other types of models and simulations that are used to model other system components. In this paper, the basic approaches to modelling human performance are discussed along with a brief case study.
System performance is often determined by the performance of the humans in the system. Yet, system models often leave out any significant representation of the humans that are operating and maintaining them. Recently, tools and methods for modelling the human in systems have begun to receive widespread attention. Thses tools and methods are consistent with other types of models and simulations that are used to model other system components. In this paper, the basic approaches to modelling human performance are discussed along with a brien case study.
With new technologies emergin daily, one of the largest problems companies currently face is the challenge of upgrading slow, outdated systems. While it is common consider things like cost efficiency and automation in new systems, companies often overlook the humna elemtn their system redesign. By factoring in the humna element, companies can avoid having to make costly adjustments their system because of unexpected human error. Task network modelling is one approach to modelling environment that supports task network modelling and human performance modelling. This paper will discuss how to model the human element using Micro Saint along with a brief case study.
For the past nineteen years, Micro Saint simulation software has been helping the military and other commercial companies answer questions on how to improve performance and utilization fro their various processes. Recently, Micro Saint has been redesigned to be faster, modular more powerful. Because these represent such major change from the original Micro Saint, we are releasing a brand new tool called Micro Saint Sharp. Micro Saint Sharp is still a generlal purpose tool that can be used to provide solutions ranging from queuing problems involving hospital waiting rooms to complex human decision processes involving future command and control systems. This paper will provide an overview of Micro Saint Sharp and present some of its new modelling capabilities.
The Physiological Stress Index (PSI) was developed to provide a rational means for estimating the physiological and behavioural impact of exposure to physical stressors, in this case extreme temperatures and fatigue related to insufficient sleep. Stress can be life threatening and certainly threatens mission effectiveness. It is often derived from combinations of sources such as overheating and lack of sleep, particularly on individuals involved in physically demanding activities such as shipboard firefighting. The PSI was used as a performance modifying adjunct to existing discrete event simulation models designed to estimate shipboard manning requirements given various operational scnearios. Additionally, the PSI was used to estimate the most effective work rest cycles and recovery time required before selected crewmembers could be retured to duties involving significant levels of physical exertion.
Micro Saint is a discrete-event simulation software package for building models that simulate real-life processes. With Micro Saint models, users can gain useful information about processes that might be too expensive or time-consuming to test in the real world. Some common application areas for simulation modeling include the following:
- Modeling manufacturing processes, such as production lines, to examine resource utilization, efficiency, and cost.
- Modeling transportation systems to examine issues such as scheduling and resource requirements.
- Modeling service systems to optimize procedures, staffing and other logistical considerations.
- Modeling training systems and their effectiveness over time.
- Modeling human operator performance and interaction under changing conditions.
- Simulation is a cost-effective way to help show decision-makers the most cost-efficient alternatives to any problem.
The limitations that human operators impose on task execution are rarely integrated into simulations of complex systems, resulting in considerable loss of outcome fidelity. A discrete-event simulation tool, Micro Saint, was used to stochastically model the impact of human interactions in a comprehensive model of the next generation US Navy destroyer, DD21, to support the Blue contract competitor team. Mission essential tasks performed by a 3-operator and a 4-operator configurations were modeled during a demanding 2.5 hour land attack scenario. Estimates of utilization rate for the two configurations revealed that two of the operators were tasked more frequently during the 3-operator configuration compared to a 4-operator configuration. Workload estimates showed that Operator 2 was working with significantly increased workload for the smaller watchteam configuration. The workload for Operator 2 dropped 36% when Operator 4 was added to the mission. This over tasking likely contributed to the finding that the smaller configuration could not respond to a call for fire in support of ground forces before 179 seconds whereas the 4 operator team responded within 61 seconds. The DD21 model suggests that the small watchteam configuration might not be acceptable, particularly during missions lasting over several days.
Supply Chain management, the management of the flow of goods or services from materials stage to the end user, is a complex process because of the level of uncertainty at each stage of the supply chain. Computer simulation, because it can be applied to operational problems that are too difficult to model and solve analytically, is an especially effective tool to help analyze supply chain logistical issues. While most engineers have had some exposure to the tools and technology of computer modeling and simulation, the use of simulation for supply chain analysis has not been prevalent until recently. The software tool, Supply Solver, was developed in an effort to provide supply chain solutions using simulation as the foundation. In this paper, the goal will be to show how discrete-event simulation is used to analyze supply chain processes. This paper will also demonstrate what some of the considerations are in using Supply Solver to help solve supply chain design problems.
This tutorial will present a methodology for modeling of human performance using multiple resource theory within a discrete event simulation. Participants will gain an understanding of why modeling human performance can be important and how workload models can be used to support system design. This presentation will include the theoretical background as well as detailed the techniques for modeling workload. The techniques will be demonstrated through the development of a model to assess the workload associated with driving a car while talking on a cell phone. Finally, two case studies of how these techniques have been used to model human performance during the design of new military systems will be presented.
For the past twenty years, Micro Saint simulation software has been helping the military and other commercial companies answer human performance related questions. Micro Saint Sharp, the next generation Micro Saint simulation tool, includes the ability to allow the user to add built-in parameters and reports that are specifically related to human performance modeling. With a well-designed model, users can easily represent who the operators are, what functions and tasks they perform, what visual, auditory, cognitive, and psychomotor demands are placed on them, and what their utilization is. There are a number of user-defined reports that can be generated based on the simulation execution. This demonstration will provide an overview of Micro Saint Sharp and present some of its new human performance modeling capabilities.
The Future Combat Systems (FCS) program goal is to develop the next generation of vehicles and networks for the Army. Eight configurations of Manned Ground Vehicles (MGV) are being designed as part of this effort. Requirements state that each MGV must weight less than 20 Tons to be C-130 transportable. To achieve this weight limitation the armor will be removed before flight. The armor will be flown in on a separate aircraft and installed at the destination. A specific challenge for the manufacturer of the MGVs is determining how best to utilize human resources in the installation process. This poster will describe the use of discrete event simulation to develop a human performance model that helps determine an optimal combination of manpower, armor panels, and installation equipment. Four different “up-armor” scenarios were simulated each with different manpower, number of armor pieces, size of armor pieces, and material handling equipment requirements.
The certification of transport category aircraft requires an emergency evacuation demonstration mandated by both FAR Part(s) 25 and 121. There are many constraints on the demonstration, including gender, age, exit availability, and time. There are no provisions in the regulations concerning use of simulation for emergency egress; yet, simulation is widely used in design considerations for buildings, roads, manufacturing processes etc. Muir et. al. (1989, 1994, 1996, 2004) have written extensively on emergency evacuation of transport category aircraft and suggested the use of simulation, as an alternative to demonstrations, in order to better understanding the influence of variability in emergency egress situations. The simulation approach adopted here involved the development of models with varying levels of detail, such as movement durations through the sequential evacuation stages – from the seat and aisle, to the door and use of the exit slide. These times were modeled by the Gamma and Lognormal statistical distributions with parameters estimated from observations and data related to human movement in constrained evacuation situations. Constraints were placed on the activities to simulate blockages at various stages of the evacuation. These constraints were intended to represent handicapped passengers or “kin” behaviors in which groups of passengers attempt to stick together. The results of the preliminary simulations indicated the viability and validity of the approach and showed the expected effects of passenger movements and delays. More extensive investigations, planned over the coming months, will focus on the cause and effect of blockages and passenger behavioral variability.
The future military command and control (C2) process will be altered because of impacts of new information technology and organizational changes. To predict how these changes will impact soldier performance, the Human Research and Engineering Directorate of the U.S. Army Research Laboratory developed models to analyze human performance under current and proposed future operational conditions. C2 soldier task performance and workload was modeled for a “typical” maneuver battalion task force configuration and in a future technology-based configuration.
Health care is a complex adaptive system that is difficult to analyze for the purpose of improving work performance. This paper discusses complex systems architecture and an agent based modeling framework to study health care system improvements and their impact on patient safety, economics and workloads. Here we demonstrate the application of a safety dynamics model proposed by Cook and Rasmussen, to study a health care system using a hypothetical simulation of an emergency department as a representative unit of a health care system and its dynamic behavior. By means of simulation, this paper demonstrates the nonlinear behaviors of a health service unit and its complexities; and how the safety dynamic model may be used to evaluate various aspects of health care. Further work is required to apply this concept in a ‘real life environment’ and its consequence to societal, organizational and operational levels of health care.