Session Guide

Arena—The Path Forward

Come learn about the new and exciting enhancements coming to Arena as we move the product forward. Users are encouraged to come and offer feedback and suggestions to help define the further advancement of the Arena application.

This session conducted by Arena Product Management will include a presentation of upcoming enhancements as well as an open forum to discuss feature requests.

ACT Solutions

Understanding business process complexities and their related problems for decision makers and using optimization techniques to solve these issues.

Managing a business requires an alignment of corporate objectives and daily activities with company processes to meet overall financial and production style goals. Strategic, tactical and operative decisions must be consistent with, synchronized with and structured so as to resist disruptions or unexpected events (example - Supply Chain broken by hurricane, stock out, etc.) and exploit the resources available at best to overcome the disruptions.

Researches show that Analytical Decision making definitely enhances and improves the company competitiveness. The introduction and usage of simulation tools such as Arena and custom optimization tools to support corporate Decision Makers, is an incremental path which first has to involve all managerial levels and departments and then has to also include the company technologies.

This speech will address this topic with real-life examples.

American Express

Call Center Use and Expansion Planning

For American Express to ensure adequate service performance for the web-based applications its call centers and card members rely on, capacity planners for the technology infrastructure must provide for adequate application server capacity. If too few data processing and memory resources are made available, performance deteriorates leading to response delays and outages, yet the large number of servers required for heavily loaded applications have a high cost of ownership. To improve the planning for this critical service infrastructure, a team of OR and IT experts analyzed application server resource consumption patterns driven by two key factors affecting service performance and capacity: 1) the dynamically varying user loads on the system, and 2) the variable delays that occur when the application server makes external query and transaction calls that the applications require. Both factors must be considered because application servers consume and hold computing resources both when customer requests arrive and also while requesting and waiting for transaction responses and data from the external services needed to fulfill customer requests. The analysis framework uses a two-step, emulation-simulation approach that first characterizes consumption patterns for a single server by emulation testing under controlled load and latency conditions, and then uses data from the emulation to define a scaled-up discrete event simulation. In about 6 months the team developed and tested the approach and converted it into a planning process that is being used to plan for expansion of an application to thousands of call center users. The approach has contributed to American Express’ leadership in providing high quality service to its customers while eliminating unnecessary spend on excess capacity, resulting in significant cost savings.

Boeing

Integrated Production System Modeling Method

This presentation is to share some of the simulation modeling methods that were developed along the journey of the integrated production of the most advanced commercial airplanes ever: The Boeing 787. The Boeing 787 outsold all commercial airplanes during the period between program announcement and the initial flight. One of the most common challenges of launching a large scale program is to ramp up production speeds among all partners globally. Simulation modeling methods for such production system consider synchronization of production schedules, randomness in the system, learn curve effect, resource utilization, verification, and validation. The scope of the simulation covers from the overall system to cell by cell level in individual production site.

Learning curves can be charted by using slide rules manually on a log-log scaled paper for one scenario at a time without random number generator. Spreadsheets have the random number capability in modeling the learning curve related production scenarios but not very practical in managing time sequence of stochastic and dynamic events. In order to mimic the asynchronous stochastic production system in motion over time, one of the most powerful and practical modeling method is to use the discrete event simulation modeling method.

This presentation describes some fundamental theories and with examples in various scales in modeling an integrated large scale production system.

DRS Technologies

Consolidation of Multi-facility Manufacturing Into Single Facility

The consolidation of multiple manufacturing facilities into a single location presented DRS Technologies with the opportunity and challenge of redesigning stockroom processes and layouts while meeting specific square footage reduction, safety improvement, and manpower staffing goals. ARENA simulation was used to ensure new processes and layouts would meet these goals.

The simulation was built in stages. The first stage compared using mechanical lift devices versus the current practice of using ladders for picking parts off of high stockroom shelves. Although the use of mechanical lift devices was initially thought of as being a safety-only initiative, the simulation results showed that they would save time as well. Furthermore, the simulation was used to determine the number of devices needed.

The following stages expanded the simulation model to include other tasks performed by the stockroom employees:
* Receiving
* Packaging
* Shipping
* Computer transactions

This allowed for comparisons of various cross-training and shift staffing scenarios to determine optimal staffing levels which meet manpower staffing targets without sacrificing performance and customer satisfaction.

GHD

Simulation modeling was used to aid in the design of a new coal terminal capable of exporting up to thirty million tonnes annually. Given the multi-billion dollar capital investment required and the value of potential revenue lost even for relatively small reductions in throughput, it is critical that each design decision be properly verified. The areas of coordinating supply and demand signals and allocation of storage space often pose a high degree of difficulty for simulation analysts, but their exclusion or sub-optimal implementation could result in either overdesign or oversimplification. Simulation analysts from different industries will gain from the discussions of how these modelling challenges, also encountered in non-mining supply-chains, were effectively addressed in Arena.

Johnsonville Sausage

Material Re-supply Network and Automated Retrieval System Simulations

Johnsonville, a leading producer of sausage products, will present two case studies on the application of ARENA within its Supply Chain. The first case study is on the material re-supply network which includes movement of raw material and finished goods between processing and distribution center facilities. ARENA was used to simulate the activity on multiple combinations of routes to determine the optimum number, and optimum starting locations, of trucks and trailers. The second case study is an application of the ARENA software to model the throughput of the automated retrieval systems within a 160,000 square foot, six story high, distribution center.

Norwegian Cruise Line

On-board Passenger Traffic Simulation

As NCL moves further ahead as an innovative leader within the cruising industry, their newest ship – the Norwegian Epic - is critical to the future success of the company. NCL is currently utilizing the Arena Simulation Software on a project hoping to optimize guest traffic flow on the Epic, prior to the official release of the vessel. Rather than potentially impacting their newest, flagship product with trial and error, NCL has chosen to utilize simulation as a way to proactively identify and resolve problematic areas. The Epic will offer a brand new concept to the cruising industry: "Freestyle Entertainment"; with this new concept comes many potential traffic problems for the company. The simulation will test schedules, hours of operation, sequence of service, and table configurations as a means to avoid impacting the final product. The model is currently of a very large scale, containing 17 independent venues (each a sub-model), and a parent model ties all the venues together. Collectively, the model reflects a holistic view of the vessel and operation, and provides detailed information for analysis at varying periods throughout the cruise.

OCP

Strategy for Changing Business Processes at an Oil Company

Use of Arena simulation model with financial variables to support business decisions in the distribution and processing plants for oil products for a major Mexican Oil company.

Paragon Technologia

Complex Mining Projects: Simulation, Visualization, Optimization and Templates

Open pit or underground mining operations can be described as complex systems, with major capital investments and decision problems involving risk and uncertainty. In order to minimize risks, simulation models are used to analyze operations and extreme conditions.

A major pitfall for modeling these systems is to have the correct balance level of detail of supply chain (mine, mills, trucks, trains, terminals, ports) and modeling decisions while maintaining accuracy.

This presentation will explain a successful approach combining intelligent mining object/templates with concurrent optimization that allows an Arena user to analyze mining systems with extreme detail.

Posten Meddelande Sverige

A Simulation Study of the Configuration and Throughput of Small Parcel Sorting Machines

One problem with the procurement of new sorting equipment is comparing different machines with each other. Usually there are a number of different suppliers, each having a different solution, but the basic principle behind each solution is the same.
We have created a general simulation model to compare and analyze the capacities and configurations of small parcel sorting machines from different suppliers.

To do this comparison we have chosen to only take into account the parameters that are common for all the machines we have analyzed.
We will present the model and the results with the help of animation in Arena along with charts in Excel. We will also show how the user can easily change parameters and settings in the model by using a VBA form in Arena and how we have used a few smart features in Arena to make a relatively small model for a fairly large problem.

Systems Navigator

Generic Simulation Models for Operational Decision Support to Hospitals: Hospital Navigator

The A&E Simulator is a planning tool. It shows how patients flow through the A&E department; how they occupy the different treatment spaces; and when they are treated by the medical and nursing staff. The A&E Simulator can be fed with a patient arrivals file that has been downloaded from the A&E computer system, replaying patients' arrivals as they actually happened. Repeated simulation experiments with different "what if" scenarios that explore different space and staffing configurations show what needs to be done to reach the NHS 4 hour waiting time standard in a consistent manner.

The National Institutes of Health

Evacuation Plan Simulation

The National Institutes of Health (NIH) is the steward of medical and behavioral research for the Nation. The NIH main campus is in Bethesda, Maryland and occupies 75 buildings on more than 300 acres. As part of its continuous improvement effort, the Security and Emergency Response division is analyzing the process for evacuating the campus. The idea is to better understand how resources can be best utilized to evacuate the campus safely and expeditiously in case of an emergency. To be able to conduct the analysis efficiently and with minimum disruption, the Office of Research Services’ Quality Management Office developed a campus evacuation simulation using Arena software. This initial model is currently undergoing sensitivity analysis and will serve as the main building block for more complex analysis in the near future.

Trellisys

Modeling Human Flow in a Hospital/Healthcare Environment

This presentation describes an approach to simulating human flow in a hospital. The objective of this study was to determine the number of elevators required as well as to define their roles in the context of a hospital expansion project. Acquisition costs and maintenance costs are considered, but primarily space constraints and wait times make the decisions surrounding the use of elevators in hospitals of strategic importance. Our approach to modeling has permitted us to evaluate different elevator configurations within a single model. Decision makers were able to quantify and test different scenarios in a risk free environment.

U.S. Department of Veterans Affairs

Operating Room Simulation Model Abstract

Currently, the operating room efficiency is constrained by many factors such as personnel delays, case length prediction deviation, turnover time, and instrument/equipment availability. Our team was tasked with improving operating room efficiency through increasing room utilization by optimizing staff scheduling, preventing personnel delays and reducing instrument related case delays. The overall aim is to increase the number of cancer-related case throughput in the OR. Wayne State University (Detroit, MI) along with several other universities have partnered with the Department of Veteran Affairs to provide industrial engineering solutions such as using simulation for operating room scheduling efficiency. We modeled patient flow from patient check in through discharge from post ambulatory service areas. Going forward, we will include information and instrument flow that affect operating room operations through other departments within the hospital. Our model interfaces with Excel which affords operating room schedulers the opportunity to use familiar GUI interfaces and black box use of the model. This model will be used to monitor utilization levels and potential bottle necks due to scheduling constraints as well as resource management for added-on emergency cases and cancelled cases. In the near future, we look to integrate our model of the central inventory processing and control department with our OR model. Our simulation model will be presented to other VA facilities and deployed to all as a part of our clinical informatics system.

Universal Studios Orlando

Using Simulation for Attraction Design

Arena is primarily used for the ride-design process. After a ride has been designed a simulation model is built to mimic the behavior of the attraction and to understand its operation. This model helps also to identify potential problems in the different sections of the ride, for this, all waiting times, stops, delays, etc are monitored and decisions are made based on these parameters. These decisions can be from the number of vehicles needed to the number of load, unload, and parking positions that help the attraction reach certain target capacity (guests per hour). The simulation also helps to test different scenarios with different # of vehicles, different vehicle length, etc.