WSC 2004 Final Abstracts
Monday 10:30:00 AM 12:00:00 PM
Chair: Eleazer Martin (Key Solutions AS)
Multi-Period Robust Capacity Planning Based on Product and Process Simulations
Emre Kazancioglu and Kazuhiro Saitou (University of Michigan)
This paper presents a method for allocating production capacity among flexible and dedicated machines based on uncertain demand forecasts of products in a production portfolio. Given multiple scenarios of future demands with the associated probabilities, the method provides al-ternative capacity allocations by quantifying the expected values of the product quality and cost. The product quality is estimated as the total performance variations from the nominal design for each product in a portfolio. The pro-duction cost is estimated as the total annual equivalent of investment and operation costs for each production pe-riod. A multi-objective genetic algorithm is utilized to compute the Pareto-optimal capacity allocations that quantify the trade-offs between the expected product quality and cost. Case studies on an automotive valvetrain production are presented, where, under the de-mand forecasts with low uncertainty, the allocation of flexible machines is encouraged only at production steps critical to quality and cost.
Air Cargo Operations Evaluation and Analysis through Simulation
Aaron Luntala Nsakanda (Carleton University), Michel Turcotte (Air Canada Operations Research Group) and Moustapha Diaby (University of Connecticut)
This paper illustrates the use of simulation for evaluating and analyzing air cargo operations at one of the new state-of-the art cargo facilities at Toronto Pearson Airport. The establishment of a facility equipped with some of the latest in modern material handling systems available today and a computerized-based inventory control system that interfaces with all aspects of its cargo operations, has driven the airline company involved in this study to developing new processes to ensure that products and services are aligned with cus-tomers’ needs. One of the challenges faced is a lack of an evaluation tool that can be used to quantitatively evaluate and compare different policies, business practices and proc-esses within a given set of operational and business con-straints. This work aims in developing such an evaluation tool. We describe the modeling approach, the challenges in-volved and the potential use of the simulation tool. Prelimi-nary results are also reported.
Analysis and Enhancement of Planning and Scheduling Applications in a Distributed Simulation Testbed
Nirupam Julka, Peter Lendermann, Chin Soon Chong, and Long-Foong Mike Liow (Singapore Institute of Manufacturing Technology)
Planning and scheduling applications and operations simu-lation models jointly represent the manufacturing activities of an enterprise. This paper relates to a framework that en-ables integration of both into a unified model and allows improvement of their performance with discrete event simulation (DES) technology. The High Level Architec-ture, which is the IEEE standard for interoperability of simulations, forms the backbone of this framework in which business applications can be re-used with operations simulation models to generate an integrated simulation model. This enables a company to optimise not only opera-tional processes such as shop floor or warehouse opera-tions but also business processes such as planning, order management and scheduling through simulation using the same software infrastructure. A case study to demonstrate the feasibility of this framework is included and ongoing work on implementation of this framework in an industrial environment is presented.
Monday 1:30:00 PM 3:00:00 PM
Simulation of Customer-focused Business Processes
Chair: Jihong Jin (Wells Fargo)
There is a general understanding in the simulation community that simulation is not reaching its full potential and is not widely used despite its well-known (among simulationists) benefits. This article's primarily intent is to discuss this belief, applying a marketing model whereby simula-tion is viewed as a product.
Analyzing Skill-Based Routing Call Centers Using Discrete-Event Simulation and Design Experiment
Thomas A. Mazzuchi (The George Washington University) and Rodney B. Wallace (IBM Global Services)
Call center customer service representatives (CSRs) or agents tend to have different skills. Some CSRs can handle one type of call, while other CSRs can handle other types of calls. Advances in automatic call distributors (ACDs) have made it possible to have skill-based routing (SBR) which is the protocol for online routing of incoming calls to the appropriate CSRs. At present, very little is known about SBR. We develop a discrete-event simulation model to analyze the performance of a M(n)/M(n)/C/K SBR environment in which incoming calls are handled in priority order and in a non-preemptive manner. We use the design of experiment framework to conduct our analysis. We show empirically that the scenario in which agents have 2 skills is almost as efficient as the scenario where agents have all skills (resource pooling). Also, we discover that no interaction exists between call rate factors when resource pooling exists.
Modeling and Simulation of Consumer Credit Originations Processes
Hung-Nan Chen, Jihong Jin, Geetha Rajavelu, and Charles Reichenbach (Wells Fargo Bank)
Staffing decisions in a consumer credit origination environment have a significant impact on the financial institution’s costs as well as customer service levels. Staff resources account for a substantial portion of the expenses in processing and servicing home equity or consumer loans. This paper describes a staffing model, known as the Capacity Planning Simulation Model (CPSM), used in the Originations Division of Wells Fargo Bank’s Consumer Credit Group. The CPSM utilizes process mapping, spreadsheet modeling, and Monte Carlo simulation to model demand uncertainty and process variation, observed during the course of processing a consumer credit loan. We review the model formulation, verification, validation, and application.
Simulation CT-Scan: A Marketing Perspective
Leonardo Chwif and Marcos Ribeiro Pereira Barretto (Unifieo)
Monday 3:30:00 PM 5:00:00 PM
Modeling and Simulation of Complex Problems
Chair: Lev Virine (Schlumberger )
On Building an Organizationally Realistic Agent-Based Model of Local Interaction and Emergent Network Structure
James K. Hazy and Brian F. Tivnan (The George Washington University)
We describe research intended to build an agent-based model that is “organizationally realistic.” By this we mean that the attributes of the artificial organization of agents conform to empirical results for human organizational sys-tems. We build upon the definitional structure of computa-tional organization theory (Carley and Prietula 1994b) and represent an organization as a network of agents, tasks, re-sources, and knowledge (Krackhardt and Carley 1998). We do not assume an a priori design requirement. Rather, or-ganizational structures are posited to emerge endoge-nously, the particulars being a key area of study. Agent in-teractions are governed by local network dynamics, agent-specific rules, and explicit universal constraints (Hazy and Tivnan 2003).
Simulating the Panama Canal: Present and Future
Luiz Augusto G. Franzese and Luiz Otávio Abdenur (Paragon Consulting Solutions), Rui Carlos Botter (University of São Paulo), Arnoldo R. Cano (Autoridad del Canal de Panamá - ACP) and Darrel W. Starks (Rockwell Software)
This paper presents the methodologies and preliminary re-sults of the project to develop a simulation model of the Panama Canal, one of the most famous waterway and locks system of the world. The case is based on the project con-ducted by Rockwell Software and Paragon Consulting So-lutions, helping Panama Canal Authority design a strategic planning tool, based on Arena Simulation Software.
Visual Modeling of Business Problems: Workflow and Patterns
Lev Virine and Jason McVean (Schlumberger Ltd.)
Computer-based business analysis relies on models, or algorithmic representations of the business process. Real-life business problems can become very complex, which creates difficulties in generation, analysis, testing, and the actual use of the models. The paper discusses a proposed solution: the visual modeling workflow. A diagram or a group of diagrams represent each step within this workflow. The visual modeling process can be simplified by applying patterns or problem-solution formulas. Such modeling patterns include decoupling, encapsulation, visualization of user workflow, multi-layer visual representation of the calculation logic, and early identification and visualization of uncertainties. The patterns are applied to the visual modeling workflow, which include high level conceptual modeling, using Domain Models and Calculation Diagrams to visualize the calculation logic, visualization of testing and consolidations, and visualization of results of probabilistic analysis and simulation. The described methodology is used in a number of Schlumberger’s software application.