ONSITE TRAINING

Develop a multi-day training program tailored to your company’s needs. In addition to the topics taught in the core classes, we can add advanced topics of your choice.

Let us Develop a Price and Schedule Quote for you.

HOW TRAINING WORKS

Our five-day core competency program covers big data management and graphical analysis, statistical analysis, quality control tools and design of experiments. Even though the complete program is recommended, each of the five days is an independent class that can be taken on its own. The five-day core competency program is offered in nine cities in the 1^nd half of 2023. The full program can be taken in any date and city combination that best meets your schedule. This provides flexibility for those earning the Industrial Data Analyst Certification, but also allows others to select only the courses of greatest interest to them.

For scheduling and price information please contact us.

UPCOMING CLASSES

Big Data Management and Analysis

Every manufacturer has electronic databases on the performance of their processes and products, but very few leverage this information to improve their success. This training shows you the data manipulation and statistical analysis tools you need to uncover hidden relationships, identify opportunities for improvement and troubleshoot process problems. In this first course to becoming a Certified Industrial Data Analyst, you’ll be doing not watching, as we analyze historical data from Owens-Illinois, St Mary’s Carbon, Boeing, Hallmark Cards, Intuitive Surgical, Black & Decker and more.

Click HERE for all Big Data Management and Analysis Classes.

Statistical Analysis for Data-Based Decision Making

The principles of confidence intervals and hypothesis testing are the foundation of statistical analyses assuring the accuracy of all data-based decisions. In this training you will learn to apply statistical tests to compare processes, performance to target and paired populations. Compare variability or defect levels for two or more designs, machines, raw materials or processes using variance and proportion tests. Determine the right sample size for each study using power analysis. Finally, apply regression techniques to establish statistically significant relationships, y = f (x1, x2, x3 …….), between input and output variables, then use these models to optimize your process. In this 2nd course to becoming a Certified Industrial Data Analyst, you’ll be doing not watching, as we analyze examples from Gore-Tex, DepoMed, Quantum Silicone, Merek Millipore, Apple, Corning Inc., 3M, Keurig and more.

Click HERE for all Statistical Analysis for Data-Based Decision Making Classes.

Quality Analysis for Process and Product Validation

This course demonstrates how to meet FDA, automotive and medical device requirements for product and process validation. Discover the techniques that your suppliers should implement to ensure incoming materials and components meet your Quality requirements. Provide customers with proof of process capability for both normal and non-normal data.  Use Gage Repeatability & Reproducibility studies to determine if your measurement systems are capable, including Attribute Agreement Analysis for visual inspection. Based on Statistical Process Control (SPC) principles, implement the correct control chart and sampling plan for your manufacturing process. In this 3rd course to becoming a Certified Industrial Data Analyst, you’ll be doing not watching, as we work through Quality systems from DuPont, Kraft Foods, Restek, Bayer, Goodyear Tire, Smith & Nephew, Harley Davidson, and more.

Click HERE for all Quality Analysis for Process and Product Validation Classes.

Design of Experiments for Process Improvement

This experimental design (DOE) course demonstrates how to optimize process and product performance.  Master the 5 design characteristics that make factorial experimentation more efficient and successful than any other approach. Apply the 7 step method to execute the sampling plan to determine cause and effect relationships in your process.  Discover main and interaction effects, quantify them, then leverage the experimental results to model the input-output relationships.  Use data visualization graphics and numerical response optimization methods to achieve optimal performance. In this 4th course to becoming a Certified Industrial Data Analyst, you’ll be doing not watching, as we analyze experiments from Tarkett Flooring, Valspar, Corning, Inc., Merek, Ethicon, Sigma Millipore, Dow Chemical and more.

Click HERE for all Design of Experiments for Process Improvement Classes.

Advanced Design of Experiments and Gage R&R

In this second course on design of experiments, learn to optimize the settings of operational variables using the Central Composite to develop higher order response models. Or reduce your run count using the Box-Behnken design. Determine the run replication and repeat sampling plan to improve power and decrease error variation. Compare Plackett-Burman, Definitive Screening and Fractional Factorial screening designs to find your best approach to reduce a long list of input variables to the vital few. Finally, design and analyze a Gage R&R study for any non-standard conditions such as gage comparisons, destructive tests, round-robin and multivariate experiments. As we finalize your mastery of DOE, you’ll be doing not watching, recreating and analyzing experiments from the University of California, Stryker, Arconic, American Minerals , Ethicon, DuPont, Lonza Biotechnology, Caterpillar, Synflex American and more.

Click HERE for all Advanced Design of Experiments and Gage R&R Classes.