Statistical Quality & Optimization

At Modulus Metal Company, we utilize Statistical Process Control (SPC) to monitor and control our processes, using statistical analysis to identify trends and make necessary adjustments to improve quality and consistency. We also perform Measurement System Analysis (MSA) to evaluate the accuracy and precision of our measurement systems, using statistical tools such as gauge repeatability and reproducibility (Gage R&R) studies. Statistical analysis is a key part of our quality control efforts, and we use it to identify patterns and trends in our data to make informed decisions. In addition, we utilize optimization techniques to find the best solutions to problems and improve process efficiency. We also use Design of Experiments (DOE) to identify relationships between variables and their effect on our processes and products. Finally, we believe in clear and effective communication, and strive to present data and information in a logical and understandable format through comprehensive reporting.

SPC (Statistical Process Control): Statistical Process Control (SPC) is a quality control method that uses statistical analysis to monitor and control a process. It involves collecting data on the process and using statistical tools, such as control charts, to analyze the data and identify any trends or patterns. This allows manufacturers to identify problems in the process and make necessary adjustments to improve quality and consistency.

MSA (Measurement System Analysis): Measurement System Analysis (MSA) is a statistical method used to evaluate the accuracy and precision of a measurement system. It involves collecting data on the measurement system and using statistical tools, such as gauge repeatability and reproducibility (R&R) studies, to analyze the data and determine the measurement system’s performance.

Gage R&R (Gauge Repeatability and Reproducibility): Gauge Repeatability and Reproducibility (Gage R&R) is a statistical method used to evaluate the precision of a measurement system. It involves collecting data on the measurement system by measuring the same sample multiple times under the same conditions and then analyzing the data to determine the measurement system’s performance.

Statistical Analysis: Statistical analysis is the process of collecting, analyzing, and interpreting data using statistical methods. It involves using statistical tools, such as statistical software, to analyze the data and identify patterns or trends. Statistical analysis is used in a variety of fields, including business, engineering, and the social sciences, to make informed decisions based on data.

Optimization: Optimization is the process of finding the best solution to a problem by maximizing or minimizing a specific objective function. It involves using mathematical and statistical techniques to identify the optimal solution given a set of constraints. Optimization is used in a variety of fields, including engineering, finance, and operations research, to solve complex problems and make informed decisions.

DOE (Design of Experiments): Design of Experiments (DOE) is a statistical method used to identify the relationships between variables and the effect that they have on a process or product. It involves systematically manipulating and measuring the variables of interest and then analyzing the data to identify patterns or trends. DOE is often used in manufacturing and product development to optimize processes and improve product performance.

Reporting: Reporting is the process of presenting data and information in a clear and concise manner. It involves organizing and presenting the data in a logical and understandable format, such as a report or presentation, and providing context and interpretation of the data. Reporting is used in a variety of fields, including business, government, and research, to communicate findings and make informed decisions.

USEFUL INFO

List of ISO Standards for the Applications of Statistical Methods

Show the Standards

ISO TC 69

ISO 2602:1980 Statistical interpretation of test results — Estimation of the mean — Confidence interval

ISO 2854:1976 Statistical interpretation of data — Techniques of estimation and tests relating to means and variances

ISO 3301:1975 Statistical interpretation of data — Comparison of two means in the case of paired observations

ISO 3494:1976 Statistical interpretation of data — Power of tests relating to means and variances

ISO 5479:1997 Statistical interpretation of data — Tests for departure from the normal distribution

ISO 11453:1996 Statistical interpretation of data — Tests and confidence intervals relating to proportions

ISO 11453:1996/Cor 1:1999 Statistical interpretation of data — Tests and confidence intervals relating to proportions

ISO/TR 13519:2012 Guidance on the development and use of ISO statistical publications supported by software

ISO 16269-4:2010 Statistical interpretation of data — Part 4: Detection and treatment of outliers

ISO 16269-6:2014 Statistical interpretation of data — Part 6: Determination of statistical tolerance intervals

ISO 16269-7:2001 Statistical interpretation of data — Part 7: Median — Estimation and confidence intervals

ISO 16269-8:2004 Statistical interpretation of data — Part 8: Determination of prediction intervals

ISO/TR 18532:2009 Guidance on the application of statistical methods to quality and to industrial standardization

ISO 28640:2010 Random variate generation methods

Terminology & Symbols

ISO 3534-1:2006 Statistics — Vocabulary and symbols — Part 1: General statistical terms and terms used in probability

ISO 3534-2:2006 Statistics — Vocabulary and symbols — Part 2: Applied statistics

ISO 3534-3:2013 Statistics — Vocabulary and symbols — Part 3: Design of experiments

ISO 3534-4:2014 Statistics — Vocabulary and symbols — Part 4: Survey sampling

Product & Process Management

ISO 7870-1:2014 Control charts — Part 1: General guidelines

ISO 7870-2:2013 Control charts — Part 2: Shewhart control charts

ISO 7870-3:2012 Control charts — Part 3: Acceptance control charts

ISO 7870-4:2011 Control charts — Part 4: Cumulative sum charts

ISO 7870-5:2014 Control charts — Part 5: Specialized control charts

ISO 7870-6:2016 Control charts — Part 6: EWMA control charts

ISO 7870-8:2017 Control charts — Part 8: Charting techniques for short runs and small mixed batches

ISO 11462-1:2001 Guidelines for implementation of statistical process control (SPC) — Part 1: Elements of SPC

ISO 11462-2:2010 Guidelines for implementation of statistical process control (SPC) — Part 2: Catalogue of tools and techniques

ISO 22514-1:2014 Statistical methods in process management — Capability and performance — Part 1: General principles and concepts

ISO 22514-2:2017 Statistical methods in process management — Capability and performance — Part 2: Process capability and performance of time-dependent process models

ISO 22514-3:2008 Statistical methods in process management — Capability and performance — Part 3: Machine performance studies for measured data on discrete parts

ISO 22514-4:2016 Statistical methods in process management — Capability and performance — Part 4: Process capability estimates and performance measures

ISO 22514-6:2013 Statistical methods in process management — Capability and performance — Part 6: Process capability statistics for characteristics following a multivariate normal distribution

ISO 22514-7:2012 Statistical methods in process management — Capability and performance — Part 7: Capability of measurement processes

ISO 22514-8:2014 Statistical methods in process management — Capability and performance — Part 8: Machine performance of a multi-state production process

Acceptance Sampling

ISO 2859-1:1999 Sampling procedures for inspection by attributes — Part 1: Sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection

ISO 2859-1:1999/Amd 1:2011 Sampling procedures for inspection by attributes — Part 1: Sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection

ISO 2859-1:1999/Cor 1:2001 Sampling procedures for inspection by attributes — Part 1: Sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection

ISO 2859-2:1985 Sampling procedures for inspection by attributes — Part 2: Sampling plans indexed by limiting quality (LQ) for isolated lot inspection

ISO 2859-3:2005 Sampling procedures for inspection by attributes — Part 3: Skip-lot sampling procedures

ISO 2859-4:2002 Sampling procedures for inspection by attributes — Part 4: Procedures for assessment of declared quality levels

ISO 2859-5:2005 Sampling procedures for inspection by attributes — Part 5: System of sequential sampling plans indexed by acceptance quality limit (AQL) for lot-by-lot inspection

ISO 2859-10:2006 Sampling procedures for inspection by attributes — Part 10: Introduction to the

ISO 2859 series of standards for sampling for inspection by attributes

ISO 3951-1:2013 Sampling procedures for inspection by variables — Part 1: Specification for single sampling plans indexed by acceptance quality limit (AQL) for lot-by-lot inspection for a single quality characteristic and a single AQL

ISO 3951-2:2013 Sampling procedures for inspection by variables — Part 2: General specification for single sampling plans indexed by acceptance quality limit (AQL) for lot-by-lot inspection of independent quality characteristics

ISO 3951-3:2007 Sampling procedures for inspection by variables — Part 3: Double sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection

ISO 3951-4:2011 Sampling procedures for inspection by variables — Part 4: Procedures for assessment of declared quality levels

ISO 3951-5:2006 Sampling procedures for inspection by variables — Part 5: Sequential sampling plans indexed by acceptance quality limit (AQL) for inspection by variables (known standard deviation)

ISO 8422:2006 Sequential sampling plans for inspection by attributes

ISO 8423:2008 Sequential sampling plans for inspection by variables for percent nonconforming (known standard deviation)

ISO/TR 8550-1:2007 Guidance on the selection and usage of acceptance sampling systems for inspection of discrete items in lots — Part 1: Acceptance sampling

ISO/TR 8550-2:2007 Guidance on the selection and usage of acceptance sampling systems for inspection of discrete items in lots — Part 2: Sampling by attributes

ISO/TR 8550-3:2007 Guidance on the selection and usage of acceptance sampling systems for inspection of discrete items in lots — Part 3: Sampling by variables

ISO 13448-1:2005 Acceptance sampling procedures based on the allocation of priorities principle (APP) — Part 1: Guidelines for the APP approach

ISO 13448-2:2004 Acceptance sampling procedures based on the allocation of priorities principle (APP) — Part 2: Coordinated single sampling plans for acceptance sampling by attributes

ISO 14560:2004 Acceptance sampling procedures by attributes — Specified quality levels in nonconforming items per million

ISO 18414:2006 Acceptance sampling procedures by attributes — Accept-zero sampling system based on credit principle for controlling outgoing quality

ISO 21247:2005 Combined accept-zero sampling systems and process control procedures for product acceptance ,

ISO 24153:2009 Random sampling and randomization procedures

ISO 28801:2011 Double sampling plans by attributes with minimal sample sizes, indexed by producer’s risk quality (PRQ) and consumer’s risk quality (CRQ)

Measurement Methods

ISO 11843-1:1997/Cor 1:2003 Capability of detection — Part 1: Terms and definitions

ISO 11843-2:2000 Capability of detection — Part 2: Methodology in the linear calibration case

ISO 11843-2:2000/Cor 1:2007 Capability of detection — Part 2: Methodology in the linear calibration case

ISO 11843-3:2003 Capability of detection — Part 3: Methodology for determination of the critical value for the response variable when no calibration data are used

ISO 11843-4:2003 Capability of detection — Part 4: Methodology for comparing the minimum detectable value with a given value

ISO 11843-5:2008 Capability of detection — Part 5: Methodology in the linear and non-linear calibration cases

ISO 11843-5:2008 /AMD 1:2017 Capability of detection — Part 5: Methodology in the linear and non-linear calibration cases

ISO 11843-6:2013 Capability of detection — Part 6: Methodology for the determination of the critical value and the minimum detectable value in Poisson distributed measurements by normal approximations

ISO 11843-7:2012 Capability of detection — Part 7: Methodology based on stochastic properties of instrumental noise

ISO 13528:2015 Statistical methods for use in proficiency testing by interlaboratory comparison

ISO/TR 13587:2012 Three statistical approaches for the assessment and interpretation of measurement uncertainty

ISO/TS 17503:2015 Statistical methods of uncertainty evaluation — Guidance on evaluation of uncertainty using two-factor crossed designs

ISO 21748:2017 Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty evaluation

ISO/TS 21749:2005 Measurement uncertainty for metrological applications — Repeated measurements and nested experiments

ISO/TR 22971:2005 Accuracy (trueness and precision) of measurement methods and results — Practical guidance for the use of

ISO 5725-2:1994 in designing, implementing and statistically analysing interlaboratory repeatability and reproducibility results

ISO/TS 28037:2010 Determination and use of straight-line calibration functions

Six Sigma (6σ)

ISO/TR 12845:2010 Selected illustrations of fractional factorial screening experiments

ISO/TR 12888:2011 Selected illustrations of gauge repeatability and reproducibility studies

ISO 13053-1:2011 Quantitative methods in process improvement — Six Sigma — Part 1: DMAIC methodology

ISO 13053-2:2011 Quantitative methods in process improvement — Six Sigma — Part 2: Tools and techniques

ISO/TR 13195:2015 Selected illustrations of response surface method — Central composite design

ISO/TR 14468:2010 Selected illustrations of attribute agreement analysis

ISO/TR 16705:2016 Statistical methods for implementation of Six Sigma — Selected illustrations of contingency table analysis

ISO 17258:2015 Statistical methods — Six Sigma — Basic criteria underlying benchmarking for Six Sigma in organisations

ISO 18404:2015 Quantitative methods in process improvement — Six Sigma — Competencies for key personnel and their organizations in relation to Six Sigma and Lean implementation

ISO/TR 29901:2007 Selected illustrations of full factorial experiments with four factors

ISO/TR 29901:2007/Cor 1:2009 Selected illustrations of full factorial experiments with four factors

New Technology

ISO 16336:2014 Applications of statistical and related methods to new technology and product development process — Robust parameter design (RPD)

ISO 16355-1:2015 Application of statistical and related methods to new technology and product development process — Part 1: General principles and perspectives of Quality Function Deployment (QFD)

ISO 16355-2:2017 Applications of statistical and related methods to new technology and product development process — Part 2: Non-quantitative approaches for the acquisition of voice of customer and voice of stakeholder

ISO 16355-4:2017 Applications of statistical and related methods to new technology and product development process — Part 4: Analysis of non-quantitative and quantitative Voice of Customer and Voice of Stakeholder

ISO 16355-5:2017 Applications of statistical and related methods to new technology and product development process — Part 5: Solution strategy

ISO/TR 16355-8:2017 Applications of statistical and related methods to new technology and product development process — Part 8: Guidelines for commercialization and life cycle