A full-service consulting firm for statistical methods applied to R&D and Production
Consulting
We specialize in statistical and analytical methods applied to R&D and Production work. This includes design of experiment, model building, process optimization, measurement systems analysis, and process control systems.
Training
We offer a full suite of statistical methods trainings, aimed at scientist and engineers who work with data. We teach efficient and effective characterization as well as techniques for understanding and controlling production and measurement processes.
Analysis as a Service
Repeated analysis work (such as batch potency) can be contracted out to us. You send us the data and we will generate the report you need, with constant quality.
Change
Interested in embedding a data driven culture into your organization? We can develop your strategy to embed statistical methods into the way you work. Ten times the understanding at a quarter of the cost is a realistic expectation!
Paul A. Deen
Paul has 12 years of experience in developing and deploying statistical methods in biotech, semiconductor industry, and food. I approach work as an engineer first and a statistician second, which completely changes the way we achieve results! Experience includes hardware, chemistry, production, and advanced R&D.
Paul has an MSc from Delft University of Technology in the field of Production Engineering and Logistics and an MSc from University of Florida in the field of Biostatistics.
ESDA is specifically designed to meet the analytical needs of those individuals working within a variety of industries. Areas of focus include: JMP basics, analysis of data for basic engineering and scientific applications including statistics, distribution analysis, capability assessment, variation analysis, comparison tests, sample size selection, hypothesis testing, confidence intervals and multiple factor modeling. Presentation of the course material is designed for 24 hours of instruction.
Attendees
ESDA is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Use data to solve engineering and scientific problems
Understand the ideas associated with sampling and data collection
Demonstrate the ability to evaluate distributions
Select appropriate sample sizes for performance evaluation
Conduct comparative tests using data
Use regression techniques in order to analyze data and make process/product improvement
Select appropriate analysis technique based on type of data
Apply JMP to data analysis problems
Design of Experiments is specifically designed to meet the analytical needs of those individuals working within a variety of industries. Instruction covers both basic and advanced concepts for the design and analysis of experiments. Presentation of the course material is designed for 16 hours of instruction.
Attendees
Design of Experiments is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Select factors and responses for experiments
Design experiments appropriate for the information of interest
Use and apply the structures of orthogonal arrays for product and process development and problem solving
Ensure the experimental design is efficient
Use regression techniques in order to analyze the results and make process/product improvements
Use JMP software to design and analyze experiments
ROTD is specifically designed to meet the analytical needs of those individuals working within a variety of industries. Robust Optimization and Tolerance Design presents the methods and practices associated with designing and optimizing products and processes and to discuss tolerance design methods to protect product quality and clinical benefits. Presentation of the course material is designed for 16 hours of instruction.
Attendees
Robust Optimization and Tolerance Design is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Learn and apply the principles of robust product design
Design experiments appropriate for the information of interest
Use and apply the structures of orthogonal arrays for product and process development and problem solving
Ensure the experimental design is efficient
Use regression techniques in order to analyze the results and make process/product improvements
Optimize the response at its most robust condition
Tolerance the factors and responses
Use JMP software to design and analyze experiments
ADOE contains Mixture Design of Experiments & Augment Design and non linear modeling. It is specifically designed to meet the analytical needs of those individuals working within a variety of industries. Instruction covers all aspects of mixture design including pre-DOE, simplex lattice, centroid, screening and custom mixture designs. Presentation of the course material is designed for 8 hours of instruction.
Attendees
Advanced Design of Experiments is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Apply the principles of robust design to Mixture Experiments
Design experiments appropriate for the information of interest
Design mixture experiments appropriate for the information of interest
Ensure the experimental design is efficient
Use regression techniques in order to analyze the results and make process/product improvements
Efficient staging of experimental runs
Modeling curve parameters to build dynamic curves
Measurement Systems Analysis is designed for Engineers, Scientists and Managers who have direct responsibility for measurement evaluation, selection and control. This course covers the basic concepts associated with measurement systems analysis, repeatability, reproducibility, accuracy, linearity, stability, standards selection and use, calibration and compensation and measurement control.
Attendees
This course is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Determine gage capability
Assess accuracy, linearity, stability, repeatability and reproducibility in test equipment
Design and deploy SPC for measurement control
Select and establish standards
Describe proper methods for instrument calibration and compensation
Conduct gage capability for inspection activities
Discuss how MSA impacts customer satisfaction
This course is specifically designed to meet the analytical needs of those individuals working within a variety of industries. Course covers the basic concepts and methodologies associated with designing closed loop process controls using statistical process control for variables and attributes data. Variation assessment, subgroup formation, sample size selection, SPC control chart selection, out of control action plan generation are presented along with measures of process capability. The course requires 16 hours of instruction.
Attendees
This course is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Course Objectives
Understand the language and compute the basic statistics associated with SPC
Apply the ten process control requirements to achieve process control
Determine rational subgroup formation, sample size and frequency
Select appropriate control chart for process control requirements
Compute appropriate control limits
Develop appropriate SPC Charts and associated OCAPs
Determine process capability
Describe the roles and responsibilities for using SPC
Use JMP to analyze process variation patterns, generate SPC charts and determine process capability
Sustainability
We are committed to a sustainable business and planet
Energy
Our offices run completely on solar power and do not use any air conditioning system.
Travel
We minimize travel where we can and use carbon offsetting where we must. Carbon offsetting is done through forrest rebuilding via Trees for all
Reduction
Through the work we do, we help companies be more efficient and this reduces resource consumption.
