Data Analysis Consulting : SPC Training: Reliability Training : Statistical Consultant : Statistician :

** NEW ** Online Statistical Process Control and Process Capability Course.



Integral Concepts specializes in the application of quantitative methods to understand, predict, and optimize product designs, manufacturing operations, and product reliability.

We assist researchers and engineers in developing new technologies and superior products with greater speed and lower costs.

By developing predictive models based on physical data, our clients can predict product performance and prevent poor performance and waste.

We also provide expert testimony and litigation support in the areas of Manufacturing, Quality, Reliability, Warranty Forecasting, and Statistics.  Please click here for more details on our Expert Testimony practice.



Integral Concepts offers on-site and public training courses in Quality, Reliability, and Statistical Methods.

The education, experience, communication skills, and passion that our instructors possess provide an extraordinary learning experience.

Our seminars are rated as “outstanding” by 98% of the attendees. Scroll down the page or click on the Training tab for more information.

Services overview

  • Fast Problem Resolution
  • Reduced Product Development Time & Cost
  • Reduced R&D Time & Cost
  • Optimized Product Reliability & Quality
  • Optimized Manufacturing Processes
  • Problem Prevention
  • Minimized Warranty Costs
  • Minimized Scrap & Variation
  • Statistical Analysis & Modeling
  • Expert Testimony


Consulting and Training Services

Consulting Services

Our staff is highly experienced in the fields of Statistics, Engineering, and Manufacturing. We frequently serve as a statistical consultant on difficult engineering or manufacturing problems. We also serve as an expert statistician in litigation cases, often involving product liability or manufacturing issues. We provide an array of data analysis consulting services in many industries. In addition to solving many complex problems, we work with clients to prevent product and process failures by deploying robust design, design for reliability, and statistical process control methods effectively.

SPC / Process Capability Training

Our Statistical Process Control Training seminars stress the key fundamentals necessary for successful implementation of SPC in any facility. Important topics such as determining appropriate sampling plans and sample sizes are covered in detail. Charts for handling multiple sources of variation (e.g. within cavity and between cavity variation) are not covered in most other SPC training courses, but are vital for efficient process control in many processes. Proper handling of non-normal data is also covered for situations where utilizing methods for normal data will result in significant error (e.g. Individuals Charts and Process Capability Assessment). Short Run SPC is becoming increasingly important with product specialization and flexible manufacturing and our courses cover methods for handling Short Production Runs.

Our Statistical Process Control Training classes leverage the many years of consulting in the proper application of SPC in a wide array of industries. Click Here for more information regarding our Statistical and Quality Methods Training seminars.

DOE Training

Our Design of Experiments Training seminars cover basic through advanced classical experimental designs. We teach participants to follow an efficient and logical experimental methodology. We start with very efficient screening experiments (fractional factorials) and migrate toward response surface methods to optimize designs or processes by accurately modeling non-linear relationships. Specialized DOE Training topics such as DOE for mixtures and formulations are also available. While DOE software allows anyone to generate designs and analyze data, many experiments are unsuccessful due to a failure to consider logistical constraints, uncontrollable sources of variation, and important techniques such as blocking, use of center points, etc. Our instructors leverage their vast experience applying DOE in countless applications to provide participants with a unique learning experience that goes well beyond the typical Design of Experiments Training class. Click Here for more information regarding our Statistical and Quality Methods Training seminars.

Reliability Training

Our Reliability Training classes focus on the use of statistical methods for predicting and improving product reliability. Important aspects of handling reliability data (such as censored data) are described in detail. The use of Weibull and other distributions to effectively model time-to-failure data is covered. Limitations of some popular reliability statistics (such as Mean Time to Failure) are illustrated and superior methods of estimating and comparing reliability of different populations are presented. Participants learn how to apply reliability test planning methods so that appropriate numbers of units may be tested resulting in estimates with adequate precision. Demonstration testing, including zero-failure test plans are also covered. Our Reliability Training courses also provide exposure to many advanced topics. These include:

  • Analysis of Warranty Data
  • Regression Modeling for predicting reliability as function of predictors (in addition to time)
  • The Design and Analysis of Accelerated Life Tests for predicting product performance in compressed testing timeframes
  • Modeling with Binary (Pass/Fail) Reliability Data
  • Modeling of Repairable Systems Data

Click Here for more information regarding our Statistical and Quality Methods Training seminars

Problem Solving Training

Our Problem Solving Training integrates the use of structured methodologies such as D-M-A-I-C or 8-D with important qualitative and quantitative methods for solving problems quickly. Companies do not have the luxury of spending months resolving important design or manufacturing challenges. We emphasize methods that allow speedy determination of root causes, potential fixes, and optimal solutions. Most complex problems have causes that involve multiple factors and interactions so efficient quantitative methods (rather than brainstorming based techniques) are usually required to develop a thorough understanding of the factors causing the problem and validate solutions. Most Problem Solving courses focus on methodology alone and leave the hard part to team brainstorming of potential solutions. The end result is that most problems solving teams wander along a path of trial and error, without ever converging on a solution let alone an optimal one.

Effective problem solving must leverage quantitative methods and this course introduces many of these methods and how they are used to understand and solve problems quickly. More in-depth treatment of the tools are included in our SPC Training, Design of Experiments Training, Reliability Training, Measurement Systems Assessment Training, and Statistics, Hypothesis Testing, & Regression Training courses.

Click Here for more information regarding our Statistical and Quality Methods Training seminars.

Statistics, Hypothesis Testing, & Regression Training

We offer basic and advanced levels of training in Basic Statistics, Hypothesis Testing, & Regression modeling. Hypothesis Testing is crucial for making decisions in the face of variation and uncertainty. We often want to compare groups of data (e.g. 2 machines, Multiple suppliers, Multiple Production Periods, competing designs) and determine whether significant differences exist with respect to averages, variability, proportions, or other characteristics. Hypothesis Testing is required to correctly make such comparisons while considering the inherent variability within each group. Hypothesis Testing always involves risks of making incorrect decisions which are based on random data, so understanding and controlling these risks is crucial. Our courses teach participants the ins and outs of analyzing data with hypothesis tests as well as key elements of planning comparative studies, such as selecting appropriate sample sizes.

Regression modeling is very useful technique for understanding relationships between variables and important responses. Regression models may be used to predict process performance, understand drivers of process variability, or correlate multiple measurement systems, just to name a few common applications. Our training classes teach participants how to develop predictive models from data and handle multiple types of data such as continuous, binary, and categorical responses and predictors. Participants in this course benefit from our vast Data Analysis Consulting experience.

Click Here for more information regarding our Statistical and Quality Methods Training seminars.

Measurement Systems Assessment Training

Data accuracy and precision are vital to any quantitative analysis method. Before using any methods that are based on data (such as Design of Experiments or SPC), the measurement systems being used to obtain the data should be verified objectively. Otherwise, we are unlikely to obtain much benefit from our analyses and we will probably be misled.

Our Measurement Systems Assessment Training teaches important techniques for verifying the adequacy of measurement systems before using the data for analyses and decision making. Gage Repeatability and Reproducibility Studies are covered in detail and we highlight many problems with common practices and analysis methods while teaching superior methods. In addition to verifying precision (Gage R&R), we present methods for understanding gage accuracy/bias as well as the use of Statistical Process Control techniques for assessing long-term stability of measurement systems. We also present techniques that may be used when testing is destructive.

Click Here for more information regarding our Statistical and Quality Methods Training seminars.