ISO 9001:2015

The new revised version of ISO 9001: 2015, the world’s most popular standard for quality management, has already been published. This is the first major revision of the standard since 2000 and has been written taking into account current business challenges and organizations of any size in many different industries.

Since the last major revision that was made in the year 2000, the way of doing business has changed enormously. Today we all have instant access to information and higher expectations of the organizations we work with, while dealing with more complex supply chains and a competitive global economy, so the ISO 9001:2015 standard has been revised with this in mind. The changes made make the standard flexible enough to offer multiple benefits to organizations, being not only a tool for quality management, but an important framework for business improvement, providing greater efficiency and improving customer satisfaction.

This review also incorporates suggested changes according to the feedback received from users and experts from around the world and represents the latest best practices in how to manage and control quality in all operations. The ISO 9001 standard has benefited millions of organizations around the world, having user reports with increased growth and productivity as well as significantly higher retention and customer satisfaction.

The crucial terms for the understanding of the ISO 9001 standard are defined in the ISO 9000 standard, which has also been revised, both standards being published on last September 23.

Some of the main changes are the following:

  • Greater emphasis on the construction of a management system suited to the particular needs of each organization.
  • It is added as a requirement that the highest levels of an organization must be involved and accountable for their participation, aligning quality with a broader business strategy.
  • Thinking based on the risk contained throughout the standard, makes the entire management system a preventive tool and encourages continuous improvement..
  • Less mandatory requirements for documentation: the organization can now decide what information needs to be documented and in what format it should be.
  • Alignment with other fundamental rules of the management system through the use of a common structure and a central text.

Structure IATF 16949

In this space you can find articles of interest, news and updates on quality systems, tools and continuous improvement methodologies.

On the last October 1st, the new IATF 16949 standard was published, which will apply exclusively to the automotive industry. Among other changes, it fully resumes the structure of ISO9001:2015, as well as at the time did ISO14001: 2015.

The new structure of the requirements is as follows:

  1. Object and field of application
  2. Normative references
  3. Terms and definition
  4. Context of the organization
  5. Leadership
  6. Planning
  7. Support
  8. Operation
  9. Performance evaluation
  10.  Improvement

An important difference with respect to the previous ISO / TS 16949: 2009 is that in this new version the requirements corresponding to ISO9001: 2015 are not included, but reference is made to them, so the new IATF 16949 can not be understood: 2016 if you do not have the new ISO9001: 2015 on hand.

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MSA Measurement Systems Analysis

The purpose of the MSA Manual is to provide a guide to assess the quality of a measurement system. This tool, like the APQP, PPAP, AMEF and SPC is considered part of the Core Tools of the automotive sector and is a requirement of the IATF 16949 technical specification.

Measurement systems
The MSA Manual developed by the AIAG, deals with measurement systems, understood as the set of instruments or gages, patterns, operations, methods, devices, software, personnel, environment and assumptions used to quantify a unit of measurement or prepare the evaluation of a property or property to be measured. It is the complete process used to obtain measurements.

Quality of measurements
The basic concept of the MSA is the quality of the measurements, which are the statistical properties of multiple measurements obtained from a measurement system operating under stable conditions.

Bias and variance.
They are the statistical properties most commonly used to characterize the quality of the data. Bias refers to the location of the data in relation to the reference value (master). The variance refers to the dispersion of the data.

One of the most common reasons for the low quality of the data is the excessive variation of the measurement system.

A significant proportion of this variation may be due to the interaction of the measurement system and its environment. For example, a system used to measure the volume of liquid in a tank may be sensitive to changes in ambient temperature. Then, the changes in volume detected may be due to changes in the ambient temperature and volume changes.

If the variation due to environmental factors is very large, it can mask the variation in the process, and in that case the data from the measurement system is not useful. One of the most important parts of the study of measurement systems is aimed at monitoring and controlling their variation.

This means, among other things, that you must learn how the measurement system interacts with your environment so that only data of acceptable quality are generated. This is very similar to the approach applied to understand and control the variation of a manufacturing process.

Therefore, a measurement process can be seen as a manufacturing process that produces numbers (data) as results.

Seeing a measurement system in this way is useful because it allows us to bring all the concepts, philosophy and tools that have already been proven to be useful in the area of statistical process control.

During the measurement process the variation of the process is detected, in order to have knowledge of:

  • What the process should be doing
  • What may be wrong
  • What the process is doing

CONCEPTS

Measurement
Assigning values to material objects to represent the relationships between them with respect to a particular property.

Gage
Any device used to obtain measurements. It is often used to refer specifically to flooring devices. Includes devices pass / fail.

Standard

  • Base accepted for comparison
  • Acceptance requirements
  • Reference value
  • Known value accepted as true value, under established uncertainty limits.

Discrimination, readability, resolution
The smallest readable unit or limit of detection. It is the smallest scale of a measuring instrument.

Effective resolution
Sensitivity of a measurement system with respect to the variation of the process for a particular application.

Reference value
Accepted value of an artifact. It requires an operational definition. It is used as a substitute for true value.

True value
Real value of an artifact. It is unknown and can not be known.

Accuracy
“Proximity” to the true value or to an accepted reference value.

Bias
Difference between the observed average of measurements and the reference value. It is a component of the systematic error of the measurement system.

Stability
Change of bias over time. A stable measurement process is in statistical control with respect to location.

Linearity
Change in the bias over the normal operating range.

Precision
Closeness to each other of repeated readings.

Repeatability
Variation in the measurements obtained with a measuring instrument when it is used several times by the same evaluator, measuring the same characteristic in the same part. It is referred to as the equipment variation, capacity or potential of the instrument or system’s own variation.

Reproducibility
Variation in the average of measurements made by different evaluators using the same measurement equipment, in the same characteristic and in the same part. For qualification of products and processes, the error may come from the evaluator, the environment or the method. It is referred to as a variation of the evaluator.

Repeatability and Reproducibility Studies (Gage R & R – GRR).
Combined estimation of the repeatability and reproducibility of the measurement system. It is a measurement of the capacity of the system. Depending on the method used, it may or may not include the effects of time.

Three methods are accepted to develop the GRR:

  • Rank
  • Averages and rank
  • ANOVA

Measuring system capacity
Short-term estimation of the variation of the measurement system. For example, GRR, including graphics.

Performance of the measurement system
Long-term estimation of the variation of the measurement system. For example, method of control letter. Consider the total variation.

Sensitivity
The smallest input that results in a detectable output signal. Response of a measurement system to changes in the measured characteristic. It is determined by the design of the gage (discrimination), by the inherent quality of the equipment (manufacturer), maintenance and operating conditions.

Consistency
The degree of change in repeatability over time. A consistent measurement process is within statistical control with respect to width (variability).

Uniformity
It is the change in repeatability over the normal range of operation. It is the homogeneity of repeatability.

Measurement uncertainty
It is an estimate of the range of values in which the true value is believed to be contained. It is used to describe the quality of the measured value.

Standards and traceability
Most industrialized countries maintain an institution that represents the highest level of authority in metrology. They usually provide measurement services and maintain measurement standards to support the industry in having traceable measurements. These national institutions maintain relations between them and establish Mutual Recognition Arrangements (MRAs).

Traceability
Definition of ISO: It is the property of a measurement or the value of a standard by which it can be related to established references, usually national or international standards through an uninterrupted chain of comparisons, all of which have established uncertainties.

Traceability can be linked to reference values or “agreed standards” between the client and the supplier.

Not all organizations have metrology laboratories within their facilities, and depend on independent laboratories for traceability calibration services. In these cases, it must be ensured that the external laboratory is accredited. According to ISO / IEC 17025.

Calibration systems
It is a set of operations that establish, under specific conditions, the relationship between a measurement device and a traceable standard of known reference value and uncertainty. The calibration may also include steps to detect, correlate, report or eliminate by adjustments any discrepancy in the accuracy of the compared measuring device.

Each calibration event includes all the necessary elements, including: standards, measurement equipment to be verified, calibration methods and procedures, records and qualified personnel. The calibration system is part of the quality management system of an organization and must be included in the requirements of internal audits.

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SPC Statistical Process Control

SPC by its acronym Statistical Process Control, are control charts, which allow objective criteria to be used to distinguish background variations of important events. Almost all its power is in the ability to monitor the center of the process and its variation. This tool is also considered as the APQP, PPAP, FMEA and MSA part of the Core Tools of the automotive sector and is a requirement of the IATF 16949 technical specification.

Fundamental Concepts of SPC

The management philosophy for total quality is based on the constant improvement of the process, with the purpose of preventing the production of defective products or services. Therefore, a fundamental element in this philosophy is the control of the process. This control is indispensable, because in any process the phenomenon of variability is latent.

Variability

The factors that cause this phenomenon are among others:

  • The machinery or tool used, which does not always work in the same way.
  • Raw material, which does not have the same characteristics at all times.
  • The human factor, whose work depends on many external and internal circumstances.

Controlling the process is not about suppressing variability but about reducing it.

SPC in the Automotive Industry

The SPC has a wide application in the automotive industry, focused on the following aspects:

  • Obtain and process data that allow establishing the behavior of the processes for their control.
  • Customer satisfaction as the main business goal.
  • The organization must comply with its commitment to improvement
  • Basic statistical methods can be used to make the improvement effort effective.
  • Prevent rather than correct.
  • Improve the performance of processes.

Basic Points of the SPC Manual

  1. The collection of data and the use of statistical methods to interpret them is not ends in themselves. The intention is to understand the process as a basis of the actions to be taken.
  2. The measurement systems are critical for the proper analysis of the data, and should be well understood before the data collection of the process. When such systems lack statistical control or their variation consumes a substantial portion of the total variation in the process data, inappropriate decisions can be made.
  3. The basic concepts of the study of variation and the use of statistical techniques to improve their performance can be applied to any area. However, the material in the SPC Manual is focused on applications in manufacturing processes.
  4. The application of statistical techniques to the output of the process (parts) should be only the initial step. The process is what generates this output, so you have to focus efforts to know their performance and improve it.
  5. The application of the SPC with examples is illustrated in the manual. It is recommended that participants apply it in real cases of their organization.
  6. The SPC manual is a first step towards the use of statistical methods and does not replace the users’ need to increase their knowledge of statistical methods and their theory. Readers should be encouraged to aspire to a formal statistical education. In those fields in which the coverage of this manual is exceeded, the reader should seek the person with the required knowledge and consult it to learn the appropriate technique.

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FMEA Failure Mode and Effects Analysis

FMEA Failure Mode and Effects Analysis, is a methodology used during the development of the product and the process, to ensure that the problems that could potentially occur have been considered and that may affect the quality of the product and / or its performance. As such, there is a need to elaborate the FMEAs during the Advanced Quality Planning process (APQP), and provide input for the development of the Control Plan. This tool is also known to be part of the Core Tools of the automotive sector and a requirement of the technical specification IATF 16949. It should be mentioned that this tool is also known by its acronym in English as FMEA Failure Mode and Effects Analysis.

There are two types of FMEA: Design and Process. The FMEA is a tool to improve the reliability of the product, and can be described generally as a method to identify the severity of the potential effects of failures and to estimate the probability of occurrence of the causes of the failures. It provides a basis for implementing measures that reduce risks.

The changes from the third edition to the fourth of the AMEF are the following:

  • The format is intended to offer an easier reading.
  • An index is included.
  • Icons are used to indicate key paragraphs and visual inputs
  • Additional examples and text are offered to improve the usefulness of the manual and provide more tight control within the FMEAs process as it develops.
  • The need for support and support from the administration is reinforced.
  • The understanding of the links between FMEA of design and FMEA of the process is defined and emphasized, as well as the definition of links with other tools.
  • Improvements in the tables of ranges of severity, occurrence and detection, so that they are of more sense in the analysis and use in the real world.
  • Alternative methods are introduced that are currently applied in the industry.
  • Appendices are added, which have example formats and applications of more special cases of FMEAs.
  • The “standard format” approach has been replaced with several options representing current applications of AMEFs in the industry.
  • The suggestion that the NPR is not used as the primary means to assess risks.
  • The need for improvement has been revised to include an additional method, and the use of the threshold for NPRs is clarified as a practice that is not recommended.

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PPAP Production Part Approval Process

PPAP abbreviation of Production Part Approval Process, is one of the tools also known as Core Tools and is used in the supply chain to establish the confidence of the components and production processes of the suppliers mainly of the automotive sector, this is a requirement of the IATF 16949 technical specification.

Although many companies have their own specific requirements, the AIAG has developed a common PPAP standard as part of the advanced product quality planning better known as APQP; this encourages the use of standard forms and terminology for project documentation.

The PPAP process is designed to demonstrate that the component supplier has developed its design and production process to meet the client’s needs, minimizing the risk of non-compliance by effective use of APQP.

The 18 elements of PPAP:

  1. Design Records: a copy of the drawing. If the customer is responsible for this design it is a copy of the customer’s plan that is sent along with the purchase order (PO). If the provider is responsible for the design, it is a drawing published in the supplier’s release system.
  2. Engineering change authorization: a document that shows the detailed description of the change. Generally, this document is called “Notification of engineering changes”
  3. Engineering approval: this approval is generally the engineering judgment with production pieces made at the customer’s plant.
  4. DFMEA: a copy of the DFMEA analysis and design failure mode, reviewed and signed by the supplier and the client.
  5. Process Flow Diagram: a copy of the process flow, indicating all steps and sequence in the manufacturing process, including the incoming components.
  6. PFMEA: a copy of the PFMEA analysis and production failure mode, reviewed and signed by the supplier and the customer. The PFMEA follows the steps of process flow, and indicates “what could go wrong” during the manufacture and assembly of each component.
  7. Control Plan: a copy of the Control Plan, reviewed and signed by the supplier and the client. The Control Plan follows the PFMEA steps, and provides more details on how the “potential problems” are verified in the input quality assembly process, or in the inspections of finished products.
  8. Measurement Analysis System (MSA): generally contains the R & R study of the critical characteristics, and a confirmation that the indicators used to measure these characteristics are calibrated.
  9. Dimensional Results: a list of all the dimensions recorded in the drawing. This list shows the product characteristic, the specification, the results of the measurement and the evaluation of the sample if this dimension is “good” or “bad”.
  10. Records of Materials / Tests: a summary of each test performed in the part. This summary is usually found in the DVP & R (Design Verification Plan and Report) form, which lists each individual test, when it was carried out, the specification, the results and the assessment of aptitude / failure. If there is an engineering specification, it is usually observed in the print.
  11. Initial Studies of the Process: in general, this section shows all the statistical graphs of process control that affect the most important characteristics of the product.
  12. Qualified Laboratory Documentation: copy of all laboratory certifications where the tests reported in section 10 are performed.
  13. Appearance Approval Report: a copy of the AAI (approval of the Appearance Inspection), signed by the client. Applicable for components that affect appearance only.
  14. Sample pieces: a sample of the initial production lot.
  15. Masterpiece: a sample signed by the client and the supplier, which is usually used to train the operators of the inspections.
  16. Verification aids: when there are special tools to verify the parts, this section shows an image of the tool records and the calibration, including the dimensional report of the tool.
  17. Specific customer requirements: Each customer may have specific requirements that are included in the PPAP package.
  18. Part Submission Warrant (PSW): This is the form that summarizes the entire PPAP package. This form shows the reason for the submission (design change, annual revalidation, etc.) and the level of the documents presented to the client. If there is any deviation, the provider must write it down in the PSW or inform that PPAP can not be presented.

There are 5 levels of PPAP, these are the following:

APQP Advanced Product Quality Planning

APQP as well as the PPAP, FMEA, SPC and MSA are considered the Core Tools of the automotive sector and is a requirement of the IATF 16949: 2016 technical specification.

This is a defined process for a product development system for General Motors, Ford, Chrysler and its suppliers. According to AIAG (Automotive Industry Action Group), the purpose of the APQP is to produce a product quality plan that supports the development of a product or service that meets the needs of the customer.

The APQP is a process developed in the late 80s by a commission put together by Ford, GM and Chrysler. This tool is used today by these three companies, their suppliers and some subsidiaries. APQP serves as a guide in the development process and is also a standard way to share results between suppliers and automotive companies.

This process focuses on the development, industrialization and launch of new products. During these phases, 23 items are monitored; these should be completed before serial production starts. Some items that are monitored are: robustness of design, design tests and compliance with specifications, production process design, quality inspection standard, process capability, production capacity, product packaging, product testing and training of operators plan, among others.

The APQP has 5 phases, these are:

  1. Planning and definition of the program
  2. Design and development of the product
  3. Design and development of the process
  4. Validation of product and process
  5. Feedback, evaluation and corrective actions

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Core Tools

Core Tools is a set of tools mainly used in the automotive sector also known as PPAP, APQP, FMEA, SPC and MSA. These tools are jointly developed by Chrysler, Ford and General Motors to design, develop, prevent, measure, control, record, analyze and approve quality products and services that meet customer needs and expectations. These tools are a requirement of the IATF 16949: 2016 technical specification.

APQP Advanced Product Quality Planning

Advanced product planning is a methodology that must be kept by a manufacturer or supplier to reach a finished product. It is very important in complex projects since the methodology facilitates a lot the communication between the involved parties, whether internal departments of a corporate or clients and suppliers.

PPAP Product Part Approval Process

The purpose of PPAP is to ensure that all customer engineering records and specifications are clearly understood. Although similar to the APQP, its focus is on approving a product that has already gone through the APQP process.

FMEA Failure Mode and Effects Analysis

Provides the tools for the risk analysis in new products or processes, major changes in processes or specifications, changes in the location of functional processes

In principle, the FMEA is in charge of analyzing the possible risks of failure in products and processes. The approach is methodological, based on cause and effect diagrams, evaluation criteria, etc.

SPC Statistical Process Control

SPC is simply statistical process control with a well-defined orientation towards automotive processes. It is related to MSA especially in the long-term stability studies.

In fact, this one can be replaced by any statistical quality control but its high status issued by the AIAG makes it practically normative.

MSA Measurement Systems Analysis

The analysis of measurement systems is basically divided in two parts: the one that covers the methodological part of a measurements and calibrations laboratory and the one that is in charge of the statistical tools to assure the quality in the measurements results. MSA unifies criteria on the way in which a measurement system is accepted or presents a new measurement system, it concentrates mainly on the study and control of the variability of the measurement systems and its relation with the production processes. Among the most common MSA terms is the one of GR & R, which is basically a statistical tool that quantifies the variability of the measurement system, its sources, and its relation with the variability of the production process.

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