Design of Experiments with JMP for Manufacturing Engineers
Master the art of experimental design with our specialized training program designed for manufacturing engineers. Gain expertise in leveraging JMP software to optimize processes and improve product quality. Enroll now to transform your approach to manufacturing challenges with cutting-edge DOE techniques.
- Available in:
- Malaysia
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Target Audience
Methodologies
Classification
Focus Area Course
- Addresses skill gaps across industries
- Emphasizes emerging technologies and practices
- Enhances workforce capabilities
- Verified by industry experts
- Broadly applicable across sectors
Subsidies

What you'll learn
- Design full factorial experiments and analyze results using ANOVA.
- Understand fundamental principles and terminology of DOE in manufacturing contexts.
- Apply statistical concepts to interpret variability and significance in process data.
- Create fractional factorial designs considering aliasing and resolution implications.
- Implement response surface methodology for process optimization.
- Optimize multiple responses simultaneously using desirability functions.
- Navigate JMP's DOE platform for designing and analyzing experiments.
- Execute a comprehensive DOE project from design through implementation.
Why should you attend?
This course provides a comprehensive exploration of the design of experiments (DOE) tailored for manufacturing engineers, utilizing the powerful JMP software platform. Participants will begin by understanding the fundamental principles and terminology of DOE, emphasizing its advantages over traditional one-factor-at-a-time experimentation. Through hands-on sessions, learners will navigate the JMP interface and explore sample datasets to solidify their understanding. Building on this foundation, the course delves into essential statistical concepts necessary for effective experimental design. Students will learn to interpret variability in manufacturing processes and apply hypothesis testing and confidence intervals using JMP. The course further explores factorial designs, both full and fractional, teaching participants how to create, analyze, and interpret these experiments within a manufacturing context. The curriculum also covers advanced topics such as response surface methodology (RSM) and mixture designs for formulation optimization. Learners will engage in practical exercises to design RSM experiments and optimize multiple responses simultaneously. Robust design methods are introduced to enhance process robustness through Taguchi methods and signal-to-noise ratios. Finally, participants will apply their knowledge in a capstone project that simulates real-world manufacturing challenges. This project emphasizes team-based experimental design and execution, culminating in results presentation and implementation planning. By the end of the course, students will be equipped with the skills to effectively implement DOE strategies in manufacturing settings.
Course Syllabus
Day 1 - DOE Fundamentals and Factorial Designs
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Screening Methods and Case Studies
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Ratings and Reviews
Instructor
Instructor
Instructor Reviews
Tasmeea Rahman
Data Analytics & Engineering Training Specialist"Tasmeea was an excellent teacher. Very pleasant, willing to assist and answer concerns, and continuously asked how she could assist more. She made the course enjoyable as well as informative."
"Thank you so much for your invaluable guidance. I really enjoyed it and appreciated how much fun you made it! I feel much more equipped to cope with difficult challenges."
"The training was both fascinating and beneficial. Many members of the staff commented on how useful it was. Tasmeea delivers the topic with authority, wit, and passion."
FAQ
Frequently Asked Questions About This Course
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
We will keep you updated on the status of the intake after you enroll.
Courses you may like
Why should you attend?
This course provides a comprehensive exploration of the design of experiments (DOE) tailored for manufacturing engineers, utilizing the powerful JMP software platform. Participants will begin by understanding the fundamental principles and terminology of DOE, emphasizing its advantages over traditional one-factor-at-a-time experimentation. Through hands-on sessions, learners will navigate the JMP interface and explore sample datasets to solidify their understanding. Building on this foundation, the course delves into essential statistical concepts necessary for effective experimental design. Students will learn to interpret variability in manufacturing processes and apply hypothesis testing and confidence intervals using JMP. The course further explores factorial designs, both full and fractional, teaching participants how to create, analyze, and interpret these experiments within a manufacturing context. The curriculum also covers advanced topics such as response surface methodology (RSM) and mixture designs for formulation optimization. Learners will engage in practical exercises to design RSM experiments and optimize multiple responses simultaneously. Robust design methods are introduced to enhance process robustness through Taguchi methods and signal-to-noise ratios. Finally, participants will apply their knowledge in a capstone project that simulates real-world manufacturing challenges. This project emphasizes team-based experimental design and execution, culminating in results presentation and implementation planning. By the end of the course, students will be equipped with the skills to effectively implement DOE strategies in manufacturing settings.
What you'll learn
- Design full factorial experiments and analyze results using ANOVA.
- Understand fundamental principles and terminology of DOE in manufacturing contexts.
- Apply statistical concepts to interpret variability and significance in process data.
- Create fractional factorial designs considering aliasing and resolution implications.
- Implement response surface methodology for process optimization.
- Optimize multiple responses simultaneously using desirability functions.
- Navigate JMP's DOE platform for designing and analyzing experiments.
- Execute a comprehensive DOE project from design through implementation.
Course Syllabus
Day 1 - DOE Fundamentals and Factorial Designs
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Screening Methods and Case Studies
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Instructor Reviews
Tasmeea Rahman
Data Analytics & Engineering Training Specialist"Tasmeea was an excellent teacher. Very pleasant, willing to assist and answer concerns, and continuously asked how she could assist more. She made the course enjoyable as well as informative."
"Thank you so much for your invaluable guidance. I really enjoyed it and appreciated how much fun you made it! I feel much more equipped to cope with difficult challenges."
"The training was both fascinating and beneficial. Many members of the staff commented on how useful it was. Tasmeea delivers the topic with authority, wit, and passion."
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Target Audience
Methodologies
Classification
Focus Area Course
- Addresses skill gaps across industries
- Emphasizes emerging technologies and practices
- Enhances workforce capabilities
- Verified by industry experts
- Broadly applicable across sectors
Subsidies

Ratings and Reviews
Instructors
Courses you may like
FAQ
Frequently Asked Questions About This Course
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
We will keep you updated on the status of the intake after you enroll.
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