As an engineer, you know that some level of variability exists in all processes and projects. When variability increases, the results can include missed deadlines, escalating costs, and disappearing profits. An important part of your job is to identify the sources of variability, whether technical or financial, and to manage and reduce the variability as best you can.

That's why you need Crystal Ball.

Crystal Ball is a Microsoft® Excel®-based suite of analytical tools that includes Monte Carlo simulation, optimization, and forecasting. With little effort, you can apply these advanced analytical techniques to your new or existing engineering and cost spreadsheets to create more accurate predictions and better informed business decisions.

Today, Crystal Ball is the tool chosen by more than 85% of the Fortune 500. Engineers from companies like BAE Systems, Battelle, Motorola, Chevron, Siemens AG, and Xerox all rely on Crystal Ball to manage risk, assess alternatives, reduce variability, and make more informed and confident business and strategic decisions.

With increased competition, globalization, reduced resources, and staff cutbacks, this is a challenging time for businesses. Whether you're a design, quality, electrical, mechanical, petroleum or other engineer, your knowledge and your toolset will make the difference between whether your project succeeds or fails

Crystal Ball is for anyone who uses spreadsheets and needs to forecast uncertain results. Engineers in nearly every industry, from construction to manufacturing to government to consulting, rely on Crystal Ball to improve the quality of their decision-making processes.

Key features of interest to your industry include sensitivity and tornado analysis, correlation, and historical data fitting. The sensitivity analysis and tornado analysis are two separate methods that help you to understand which of the uncertain inputs drive the uncertainty in your engineering model. Correlation lets you link uncertain inputs and account for their positive or negative dependencies. If historical data does exist, the data fitting feature will compare the data to the distribution algorithms and calculate the best possible fit and parameters for your data.

LEARN MORE ABOUT CRYSTAL BALL FOR ENGINEERING

This page offers links to a growing number of resources, including recorded Web seminars, articles, white papers, case studies, and example models. Additionally, you can view a list of common uses and examples reported directly from customers using Crystal Ball. You can also download a free trial version of Crystal Ball to see how it can help improve your business forecasts and decisions!

RECORDED WEB SEMINARS

Cost and Risk Modelling - The Challenging Business Driver Organisations today are increasingly challenged with cost and risk modelling. The seminar will provide case study examples and discuss the major issues in industry both from customer and supplier perspectives. Presented by Professor Rajkumar Roy with Cost Engineering research at Cranfield University Recorded July 5, 2007	View recording Download files
Minitab and Crystal Ball Synergy for Multiple Response Optimization Learn how Minitab and Crystal Ball can be used in combination to explore design tradeoffs (i.e. improving one response might unfavorably impact another response) and find the optimum in the presence of variability. Presented by Eric Maass, Motorola's Director for SSPD / DFSS Methods and Technology Recorded July 6, 2006	View recording Download files
DFSS Approach: Using Monte Carlo Simulation for Probabilistic Design Learn how to integrate probabilistic modeling, Monte Carlo analysis and Filtered Monte Carlo optimization into a process map of sequential analytic experimentation and design optimization. Presented by Martha Gardner, Ph.D., Global Quality Leader, GE Global Research Recorded June 28, 2006	View recording Download files
Monte Carlo Simulation in Chemical Process Design This seminar presents a case study demonstrating the use of Monte Carlo simulation in assessing and managing project financial risk (NPV), capital engineering budget risk and design technical risk. Presented by Randy Perry, Master Consultant with Sigma Breakthrough Technologies, Inc. (SBTI) Recorded February 22, 2007	View recording Download files
Como resolver problemas complexos nas áreas de engenharia, finanças, marketing e planejamento por meio do Crystal Ball Neste seminário mostraremos como solucionar alguns problemas complexos utilizando-se planilhas eletrônicas juntamente com simulação de Monte Carlo. A simulação é realizada por meio das facilidades do Crystal Ball®. Estes exemplos são associados a quatro áreas distintas: mercado financeiro, engenharia, orçamento de capital e marketing. Recorded August 29, 2007	View recording No downloads

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WHITE PAPERS & ARTICLES

Basic Techniques for Analyzing and Presentation of Cost Risk Analysis By Randy Lorance & Robert Wendling	Download
Crystal Ball® Implementation in Engineering: Engineering Design Under Uncertainty By Yosef Amir, General Electric	Download
Formulating Risk into Research and Engineering Projects By Bryan L. McKinney and David R. Engfer, Fusfeld Group, Inc.	Download
Monte Carlo Simulation Process in Reliability and Maintenance By Alberto G Landeaux, ISC Gerencia de Activos, Venezuela	Download
Project Cost Risk Analysis Using Crystal Ball By David Hulett	Download

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CASE STUDIES

Analyzing Engineering Projects Analyzing Engineering Projects Using Real Options -- Intelligent Investments in the Face of Uncertainty	Download
Designing Portable Products Motorola Labs Engineers Apply Crystal Ball Pro to Improve the Design of Portable Products	Download
Tolerance Analysis on Printed Wiring Boards Crystal Ball Provides Quality Insights to Six Sigma Consultant Andell Associates	Download

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EXAMPLE MODELS

Hardware Cost Estimation for Aerospace Project From: Ralph Geiger, Operational Concept Analyst, The Boeing Company Detail: This engineering cost assessment model uses a competitive price estimate risk analysis for an avionics upgrade. The systems engineers have developed a preliminary design configuration that includes estimates for hardware, software, and systems engineering. The model uses cell referencing and a correlation matrix.	Download For: Crystal Ball Level: Simple- Moderate
Machine Reliability and Maintenance From: James Evans and David Olson, from their latest textbook: INTRODUCTION TO SIMULATION AND RISK ANALYSIS, 2/E, Copyright 2001. Detail: This model is an example of an operations management application, where the owners of a plant are attempting to determine the most cost-effective way in which to maintain the operation of machines that constantly need bearings replaced. The purpose of the model is to determine whether a proposed maintenance process would save money over the current process given the uncertainty of the bearing reliability. Electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.	Download For: Crystal Ball Level: Simple
Power Budgeting Tool Detail: This Tool is a special template of Crystal Ball Standard Edition that has been adapted for analyzing computer system power budgets. The software works with Windows 95, 98,  Me, NT 4.0, and 2000, and with Excel 95 , 97, and 2000 . This template was developed for Crystal Ball 2000 (version 5.0), and  it is not compatible with more recent versions of Crystal Ball such as Crystal Ball 2000.5 (5.5) . The Power Budgeting tool is fully functional, but you must already own a licensed version of Crystal Ball.	Download For: Crystal Ball Level: Moderate
Reliability of a Helical Spring Detail: In this example, a design engineer is given the task of choosing the best material to use for a helical spring.	Download For: Crystal Ball Level: Simple
Tolerance Analysis Detail: An engineer at an automobile design center needs to specify components for piston and cylinder assemblies that work well together. To do this, he needs the dimensions of the components to be within certain tolerance limits, while still choosing the most cost-efficient methods. Includes optimizations setting file and uses final value and range-width statistics.	Download For: Crystal Ball & OptQuest Level: Simple

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COMMON USES & EXAMPLES

The following examples were provided by our customers and represent only some of the potential engineering applications for Crystal Ball.

• Analysis of contingency provisions for construction project capital estimates
• Analysis of DC circuit designs
• Analysis of pavement management options
• Analyze schedule probability and risk analysis for project management
• Assessment of the relative impact of conflicting design requirements or design tradeoffs
• Cost risk estimation tool for engineering projects
• Building a tolerance model (Design for Six Sigma).
• Characterization of assembly equipment
• Cost benefit analyses of environmentally-preferred processes/technologies
• Cost risk analysis associated with complex communications systems
• Customer usage modeling and reliability forecasts
• Definition of product design objectives and forecast of ROI
• Designing new manufacturing process
• Economic evaluation of oil and gas exploration prospects and exploration portfolios
• Environmental cost calculations for remediation projects
• Exposure modeling research
• Identify the significant parameters in mathematical models
• Life cycle cost analysis
• Monte Carlo simulation of a thermal-hydraulics problem
• Monte Carlo simulation of signal processing applications
• Monte Carlo simulation of stress calculation
• Monte Carlo simulation on communications systems models
• Monte Carlo simulation to determine probability of detection when test signals ar subjected to different levels of signal noise
• Monthly performance measurement analysis
• Network sizing forecasting
• Operation and maintenance analysis of offshore wind turbines
• Operations planning and analysis
• Optimize processes early in the development cycle based on DOE (transfer function) results
• Optimizing Designs within DFSS-based methodology
• Performance forecasting analysis
• Power plant project appraisal
• Reliability analysis and proposals
• Research projects in water and sanitation services
• Risk analysis of oil and gas exploration projects
• Safety analysis and process engineering
• Seismic analysis
• Simulation of oil reserve analysis
• Statistical tolerance analysis (e.g., fiber optic models, electrical connectors, printed wiring boards)
• Thermal control system modelling
• Uncertainty Analysis in the area of Biomechanics
• Uncertainty evaluation of engineering calculation and design
• Verification of appropriation studies

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TEXTBOOKS

Tolerance Design : A Handbook for Developing Optimal Specifications

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