Discrete-Event Simulation: Simulation Practices and Trends

Discrete-event computer simulation is one of industry’s most used operations research techniques. Its uses range from answering questions about work-in-process and production feasibility to comparing alternative plans for system routing and scheduling. This presentation offers a brief overview of practices and trends

How do you interpret a confidence interval?

A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating the parameter by a single value, a point estimate, an interval likely to cover the parameter is developed. Many student incorrectly interpret the meaning of a confidence interval. This paper offers a quick overview of how to correctly interpret a confidence interval

A Robust Aggregation Approach To Simplification Of Manufacturing Flow Line Models

One of the more difficult tasks facing a modeler in developing a simulation model of a discrete part manufacturing system is deciding at what level of abstraction to represent the resources of the system. For example, questions about plant capacity can be modeled with a simple model, whereas questions regarding the efficiency of different part scheduling rules can only be answered with a more detailed model. In developing a simulation model, most of the actual features of the system under study must be ignored and an abstraction must be developed. If done correctly, this idealization provides a useful approximation of the real system. Unfortunately, many individuals claim that the process of building a simulation model is an “intuitive art.” The objective of this research is to introduce aspects of “science” to model development by defining quantitative techniques for developing an aggregate simulation model for estimating part cycle time of a manufacturing flow line. The methodology integrates aspects of queueing theory, a recursive algorithm, and simulation to develop the specifications necessary for combining resources of a flow line into a reduced set of aggregation resources. Experimentation shows that developing a simulation model with the aggregation resources results in accurate interval estimates of the average part cycle time

Strategic Plan For Industrial and Management Systems Engineering

The role of this strategic plan is to map out a range of department goals, offer objectives for achieving each goal, and list potential strategies for meeting an objective. It also lists performance metrics for measuring progress for each goal. Each year, a subset of goals and objectives will be identified by the IMSE department as a priority for the coming year. Detailed metrics for measuring improvement for the department’s priorities areas will then be defined. The department committee to develop the plan consisted of Dr. Paul Savory (committee chair), Dr. Susan Hallbeck, and Dr. Erick Jones

A Web-Based Interface For Storing and Executing Simulation Models

The dominance of the Internet in the development of information and communication technology has made Web-based distributed solutions increasingly attractive. Apart from providing other services, the World Wide Web is being looked upon as an environment for hosting modeling and simulation applications. SIMAN is a simulation language that allows users to simulate discrete and continuous systems. In this research, a web-based interface or toolkit has been developed for storing and executing SIMAN simulation models over the Internet. This toolkit consists of a World Wide Web interface to SIMAN and a web-accessible database for storing user models. It provides users an easy-to-use environment for developing text-based simulation models using the SIMAN simulation language. It also allows users to test the functionality of a SIMAN model using the SIMAN debugger/run controller

Introduction to Industrial Engineering: Bad Human Factor Designs

Classroom exercise for IMSE 150 at the University of Nebraska-Lincoln. This goal is to introduce freshman industrial engineering students to various aspects of industrial engineering and being an engineer. Ergonomics or human factors does not only encompass product design, but safety, and product use. A simple definition is “to make the work place safe and less stressful on the worker.” Human factors or ergonomics impacts all aspects of our lives. Let\u27s consider each of the following examples of bad human factor designs

Introduction to IntelliSIM 1.0

IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with IntelliSIM is one which will offer substantial savings over currently available simulation tools. This document is Version 1 (1992) of the user manual for the IntelliSIM software

Discrete-Event Simulation: Simulation Practices and Trends

Discrete-event computer simulation is one of industry’s most used operations research techniques. Its uses range from answering questions about work-in-process and production feasibility to comparing alternative plans for system routing and scheduling. This presentation offers a brief overview of practices and trends

Introduction to IntelliSIM 1.0

IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with IntelliSIM is one which will offer substantial savings over currently available simulation tools. This document is Version 1 (1992) of the user manual for the IntelliSIM software

Course Notes: Engineering Entrepreneurship

This special-topic class will focus on starting and managing a successful business. Topics will include: marketing, finance, human resources, operations, legal issues, initial public offering, and succession and estate planning. Due to the engineering background of the students, special emphasis will be on exploring the legal issues involved in the process of applying for a patent. The course will enable a student to evaluate his or her own desires and prospects for a career as an entrepreneur. In so doing, it will provide the aspiring entrepreneur with a framework for selecting, funding, and starting his or her own business. While this might not seem relevant to some students, there is a lot of commonality in starting a business to that of managing a large department, developing a new product in a company, and/or being a division manager. At a minimum, students will come out of the course with a more complete understanding of the complexities and issues involved in being an engineering manager