Course content

1. Introduction

• Statistics as a mathematical method
• Processing a large amount of data (the concept of population, sampling)
• Randomness, chance

2. Basic distribution of data, outputs from measurement and assessment

• Data types: binary, nominal, ordinal, countable, continuous
• Process and data: inputs, process parameters, outputs
• Methods of data collection, selection of an appropriate amount of data
• Data collection tools: checksheet, sampling, automatic data collection
   

3. Graphical data analysis

• Static display of data: dot diagram, histogram, box-plot, Pareto diagram
• Viewing the time course of data: Progress diagram
   

4. Basic statistical parameters

• Typical data set value: mean, median, mode
• Range of values: range, variance, standard deviation
• Distribution of values: distribution of probability of occurrence
• Gaussian distribution

5. Process control using statistical methods

• History of SPC, creation of control diagrams
• Fluctuations: random and special causes
• Construction of control diagrams
• Types of control diagrams for measurable signs: I-mR, Xbar-R, Xbar-S
• Types of control diagrams for the number of mismatched units: p-diagram, np-diagram
• Types of control diagrams for the number of mismatches: c-diagram, u-diagram
• Determination of signals for statistically uncontrolled processes: rules of interpretation of control diagrams

6. Process capability and process performance

• Process suitability for quantitative features: Cp, Pp, Cpk, Ppk
• Loss function: Cpm
• Eligibility of the machine: Cmk
• Eligibility of the process for the number of disagreements: DPO, DPMO, Yeld

7. Process improvement using SPC

• Prevention vs. detection
• Process capability and performance
• Process improvement cycle: DMAIC
• Resources required to deploy SPC: time, human resources, software costs

8. Problems and errors when using SPC

• Unpreparedness of the organization for the deployment of SPC: the necessity of MSA
• Incorrect data collection, incorrect interpretation of data

 

Designed for

• Internal Auditor
• Quality Manager
• IMS Manager
• Quality Engineer
• Process Engineer
• Production Manager
• LEAN Manager
• Development and Manufacturing Technologist
• Metrologist

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Additional information

Training Schedule - Open Public Online Term
Testing the training connection	from 07:45 *
Training program	08:00 - 12:00
Lunch break	12:00 - 12:30
Training program	12:30 - 14:00
Processing a case study / test	after 14:00

* UTC +1 time zone (DE, BE, DK, NL, NO, SE, AT, ES, FR, IT, SI, SK, CZ, PL, HU, ...)