Resource Center
Quality Engineering, Reliability and Six Sigma
- Tracking and Trending Metrics in the Pharma and Biotech IndustryIn this on-demand webinar, you'll learn how to use process monitoring to know when to react to variation and how to differentiate the signals from the noise.
- Quality Engineering Tools in Bio/PharmaIn this on-demand webinar, Jeff Upton showcases tools that are utilized for Statistical Process Control and Six Sigma workflows.
- Quality Tools for Process Improvement MethodologiesAlisa Hunt-Lowery discusses how understanding and acting on factors influencing quality can result in reduced cost, faster time to market, better quality, and other benefits to your organization.
- AdociaStatistical approaches boost reproducibility and knowledge continuity in process transfer.
- VishayA customized analytics workflow in JMP reduces unutilized engineering talent and saves money.
- HeliatekAn automated dashboard helps establish statistical process control in a pilot production environment.
- LonzaA customized design of experiments approach optimizes yield in bioreactors.
- SeagateJMP and JMP Pro are an integral part of wide-ranging data analysis techniques, statistical process control, reliability analysis, experimental design and modeling.
- NVIDIAManagement helps up-skill the workforce by integrating a free statistical analysis online learning resource.
- Why quality improvement is imperative in the big data eraXaar, NNE and IT&M Stats increase efficiency and effectiveness with modern quality engineering
- Mission-Oriented Analytics: New Methods for the Intelligence CommunityAlyson Wilson explains her work developing new analytic technologies for the intelligence community.
- Evaluating the Measurement Process: A Better Way to Do Repeatability & Reproducibility StudiesStatistician, author and quality expert Donald J. Wheeler, explains data collection strategy in the context of a basic EMP and gage R&D study.
- Bridging Statistics and Chemical Engineering for Biotech and PharmaJulia O'Neill on accelerating the availability of critical new medicines and modernizing drug manufacturing.
- A Case for Sophisticated Data Analytics in Process-Enabling IndustriesStan Higgins, former CEO of the North East of England Process Industries Cluster, discusses the Industry 4.0 movement and how analytics can help companies demonstrate value capture.
- Beyond Lean Six SigmaTwo leading quality engineers discuss the importance of adopting a holistic improvement strategy, while acknowledging no one methodology is best for all.
- Bill Meeker and Chris Gotwalt: Improving Product Reliability Thought leaders Bill Meeker and Chris Gotwalt lead an insightful technical demonstration highlighting trends in the statistical assessment of product reliability that can help you reach maximum productivity in your analyses.
- Reliability Engineering: Modern Methods for Achieving High ReliabilityJoin Dr. Bill Meeker as he briefly reviews the history of the field of reliability engineering, outlines where it’s headed, and discusses both basic and emerging methods to help you achieve high reliability.
- Using Reliability Block Diagrams in System DesignThrough examples based on personal computers and automobile brakes, Dr. Bill Meeker explains how reliability block diagrams can be used to achieve reliability goals for complex, multi-component systems.
- Bayesian Inference in ReliabilityThe data available to make inferences about reliability is often very limited. Bayesian methods provide a formal way to deal with these situations. Learn how in this webinar with Dr. Bill Meeker.
- Accelerated Destructive Degradation AnalysisSometimes product failures don’t occur until after a long period of performance degradation. Learn how degradation analysis lets you make predictions about failure times across a variety of use conditions.
- Probability Plots in Life DistributionFind out how to select the appropriate distribution-specific plotting scale (i.e., normal, Weibull, lognormal) and apply maximum likelihood estimation to extrapolate failure rates into the future.
- Accelerated Life TestingIn what situations can accelerated life testing be useful? How can data transformations simplify the modeling process? What common pitfalls need to be avoided? Find out in this webinar with Dr. Bill Meeker.
- How Industrial Statistics Has (and Hasn’t) ChangedSTATCON CEO says the expectation has changed, but the work hasn’t.
- Exploring Capability AnalysisAll processes are variable to some degree, but how can you be sure your processes are functioning within acceptable parameters?
- How to Add Structure to Your Decision MakingLos Alamos National Lab scientist shares research on objectively considering tradeoffs.
- The Elements of Sophisticated Reliability AnalysisDavid Trindade of Bloom Energy makes big process improvements with reliability and DOE.
- Using Statistical Process Controls to Improve and Monitor Your ProcessDiscover how to use one-way analysis, histogram distributions and more. This case study showcases how one ethanol manufacturing plant successfully implemented Statistical Process Control to limit batch-to-batch variance.
- What It Takes to Be an Effective Industrial StatisticianHear from award-winning reliability expert William Q. Meeker.
- Advantages of Bootstrap Forest for Yield Analysis: A Semiconductor Case StudyLearn how semiconductor manufacturers are reducing time to market while keeping quality high.
- Visual Six Sigma: A Case StudySee how three Visual Six Sigma strategies are put in practice to better understand the reasons behind the failure of a pill production line.
- Explaining Reliability GrowthLearn about statistical techniques used to improve product and process reliability over time, and see specific examples using JMP software.
- Estimating the Degradation Rate of Photovoltaic Arrays Using a Two-Component Nonlinear ModelBased on only one year of data, Chris Gotwalt, Director of Statistical R&D, predicts the relative power output of solar cells for five years into the future.
- Visual Six Sigma: Making Data Analysis LeanThis paper introduces the idea of "Visual Six Sigma," a practical, pragmatic and yes, visual approach to data analysis and process improvement.
- ASM InternationalASM utilizes statistical methods companywide to be more effective and efficient.
- Johnson Matthey Fine ChemicalsAt Johnson Matthey, JMP is the ‘active ingredient’ in process optimization
- Chalmers University of TechnologyStudents jump-start their careers in industry with coursework in data methods and Six Sigma.
- MurataEngineers apply JMP on-site to improve objective analysis results.
- Daewoong PharmaceuticalA quality control team uses JMP to identify the root cause of a critical manufacturing issue.
- Cal Poly Department of Industrial and Manufacturing EngineeringStudents prepare for competitive industry careers by using JMP to learn manufacturing engineering.
- University of New HampshireFaculty integrate a free online learning resource into science and engineering course curriculum to better prepare students for industry careers.
- CoherentAt Coherent, lean manufacturing principles and comprehensive data analysis allow the company to compete in a crowded industry.
- De Montfort UniversityIndustry experts partner with the university to provide instruction on QbD best practices.
- KodakKodak gets a boost from JMP in its drive for zero-defect performance.
- PerrigoPerrigo reduces product variability and other inefficiencies by growing the use of statistical analysis in experimentation and testing
- Beijing AquariumWater quality engineers cut energy expenditure while furthering the Aquarium's conservation efforts.
- City of DurhamEngineers from the City of Durham use JMP to monitor water quality at Falls Lake.
- US Department of Energy National Renewable Energy LaboratoryUS Department of Energy optimizes solar energy systems with JMP.
- CelltrionQuality by Design advances safety, affordability and regulatory accountability.
- SyngentaSyngenta brings science to the art of agronomy with cutting-edge statistical methods and sustainable technologies
- ColoplastProcess specialists use Six Sigma and DOE to ensure a high quality product.
- NXPJMP Pro improves solution design and manufacturing, Six Sigma training and process improvement.
- Polar SemiconductorA quality control team uses JMP to identify the root cause of a critical manufacturing issue.
- Roche SwitzerlandRoche provides biosensors that allow health care professionals to get bedside readings of the quality of a patient’s blood.
- Tsukuba Medical CenterTsukuba Medical Center Hospital established a model for predicting the economic life of portable medical devices (infusion pumps) using the statistical analysis tool "JMP".
- Siemens HealthineersQuality engineers optimize manufacturing, testing and performance of an innovative blood-analysis system.
- Daeduck ElectronicsEngineers work to reduce the scrap budget, shorten experimentation times and extending the benefits of automation.
- USoundEngineers use JMP to build process knowledge, assess and monitor performance and refine production quality.
- Fujifilm Diosynth BiotechnologiesScientists use the Functional Data Explorer platform in JMP Pro to develop a cost-effective means to advance process knowledge in less time.
- MerckBiostatisticians use interactive features in JMP to perform robust statistical analyses in less time.
- SynbiCITEStatistical analysis brings discipline to state-of-the-art synthetic biology research.
- CreeCree uses JMP to pinpoint and eliminate defects in the manufacturing process.