Statistical Methods
Product parameters and process parameters are set optimal to costs and quality based on statistically verified and quantifiable coherences. The Six Sigma approach essentially makes use of a similar strategy.
Benefits
- Determination of conclusive causalities
- Design of robust products and processes
- Identification of significant and critical characteristics with substantial influence on functionality, safety and/or product reliability
Which variables do have considerable impact on x, y and z and how are they to be adjusted? Which variables show interactions that affect x, y and z?
CONTEXT services
- Creating a resource-efficient experimental design
- Determining the significant influencing factors
- Deviating optimal parameter values
What kind of failure characteristics do the recent test objects have? Which minimum reliability does the current design have considering the tolerable error probability?
CONTEXT services
- Detecting the stress profile (Mission Profile)
- Evaluating field data and endurance test data in order to analyze the failure behaviour
- Planning test programmes for the reliability proof (life test)
Which dimensions affect the resulting dimension and how do they have to be limited? What is the failure percentage expected to be in the mass production stage?
CONTEXT services
- Ascertaining the distribution of the resulting dimension
- Calculating the expected proportion of defective parts
- Determining component tolerances optimal for production
