In this 5 part webinar we will provide details of how JMP is used in manufacturing and quality control.
Journals and materials used in these seminars including links to additional learning resources are available for download on this page.
1. Introduction to JMP for Manufacturing and Quality
In this introductory session, you will learn how to:
- Import data from Excel, with the option to update the data in JMP with just one click
- Understand the structure of JMP data tables, including the data type, model type, and basic options in the side panels
- Analyze the distribution of variables and customize a statistical summary
- Perform a capability analysis, to understand the ability of a process to meet customer expectations
- Visualize data with the chart builder, dragging and dropping variables to assign them to different roles on the chart
- Fit basic models with two variables at once, such as 1-way ANOVA and simple linear regression
- Use the column changer, which allows you to change the variable used in a report dynamically
- Add a local data filter in a report, to stratify the results based on one or more variables in the data table
- Share results with other JMP users, and options to share fixed and dynamic results with people who do not have JMP
2. JMP For Quality Analysis
In this session, you will learn how to:
- Import data from an SQL database, including options to filter the data to import, update the data in JMP with just one click, or modify the query
- Generate control charts using the Control Chart Builder platform, which allows you to drag variables to generate the chart, modify the type of control chart, and add tests for special causes
- Manage specification limits for multiple variables at once, and display specifications as reference lines on charts
- Analyze the capacity of multiple processes at once, to quickly identify the processes that most need attention
- Perform an MSA study of the measurement system, to identify the main sources of variability, following AIAG guidelines, and ensure that the measurements taken with the system are reliable
- A brief introduction to reliability analyses, which allow a distribution to be fitted to failure data over time to predict the probability of failure
3. JMP for Root Cause Analysis in Manufacturing
In this session, you will learn how to:
- Generate and modify Pareto charts with flexible options in JMP, to visualize the most common defects in a manufacturing process
- Perform root cause analysis using the Partition platform, which uses a machine learning method to generate decision trees
- Quickly identify the most important variables to control in a process, using the Predictor Screening platform, which is an advanced machine learning method that uses a resampling method along with multiple decision trees generated in parallel
- Fit a multiple regression model, and use the Prediction Profiler to find settings for controllable variables that will help improve process performance
- Use the Design Space Profiler which helps find specification ranges for controllable variables that will result in a reduction in the proportion of out-of-specification batches
4. JMP for Design of Experiments in Manufacturing
Custom designs use a state-of-the-art algorithm to find the best data collection plan that will allow you to estimate the terms you need as a researcher, while taking into account constraints and budget for the experiment.
In this session you will learn:
- Generate a design of experiments for one or more response variables
- Add different types of factors
- Specify constraints on factor combinations
- Understand optimality criteria, and when to use them
- Use the design explorer to generate multiple designs, compare them, and find the best fit for your situation
- Visually analyze design results, including predictive profiler, contour profiler, and contour plots
- Explore the impact of variability on long-term factors using a Monte Carlo Simulation
- Save the prediction formula in the data table
5. Introduction to JMP Pro for Manufacturing and Reliability
As the professional version of JMP's statistical discovery software, JMP Pro takes it to the next level by offering all the capabilities of JMP, plus advanced features for more sophisticated analysis.
The purpose of this session is to show what is possible with some of the functionality of JMP Pro.
In this video you will see the following features of JMP Pro:
- Predictive modeling and validation
- Screening and comparison of models
- Formula store and how to get the open source code of punctuation
- Functional data explorer, with an example of a milling process, in which you want to find a configuration of controllable factors that will allow you to reduce the size of particles to reach specifications in the shortest possible time
- Reliability block diagrams, to study the reliability of a non-repairable system from the reliability of individual components
- Simulation of repairable systems, to study a system in which individual components are repairable or replaceable to estimate the frequency with which failures can occur, downtimes during failures, and which parts to stock
