The Automotive Quality Core Tools are the building blocks of an effective quality management system. They include Advanced Product Quality Planning & Control Plan (APQP), Production Part Approval Process (PPAP), Failure Mode and Effects Analysis (FMEA), Statistical Process Control (SPC) and Measurement System Analysis (MSA).

Over 30 years ago, AIAG collaborated with the domestic automotive manufacturers to develop common quality methods and tools, which became known as the Quality Core Tools to enhance the effectiveness of the IATF 16949based QMS, provide highquality products, produce the required quantities, and deliver on time.. The tools proved so useful that they were adopted by other manufacturing sectors, including aerospace, defense, medical, and pharmaceutical.

Today, most automotive manufacturers and suppliers require use of one or more of the Core Tools. . When applied properly, the Quality Core Tools are the valueadded methods and techniques that make it possible for an organization to achieve all three goals. Integrated supply chains use the 5 core tools to streamline communication throughout the design and manufacturing processes across suppliers and customers.

Advanced Product Quality Planning (APQP) and Control Plans reduce the complexity of product quality planning for customers and suppliers by allowing customers to easily communicate their product quality planning requirements to their suppliers. APQP is a structured approach to product and process design which facilitates communication between suppliers, design communities and customers. It helps in identifying critical to quality of systems from the customer point of view.

Control Plans summarize the identified process and product parameters required to maintain product conformity. These tools are applicable throughout the supply base in all customer/supplier relationships.
Now the standard across many manufacturing sectors, APQP defines the required inputs and outputs of each stage of the product development process.

Production Part Approval Process (PPAP) is the industry standard that ensures engineering design and product specification requirements are met. Through the PPAP guideline, suppliers and customers understand the requirements to obtain part approval of supplier manufactured parts.

It provides understanding of information required to obtain part approval and standardizes the part approval process
How to obtain approval of parts/processes after part design changes and/or process changes
Ensures part submissions are submitted with proper information and enough data to sustain product conformance
Provides a record of part conformance at launch (allows for measurement of drift from origin)
Details pertinent design records to ensure traceability of part design status at origin
Controls product and process change process, providing an approval outlet for all changes to ensure conformance to the next level assembly/process

Failure Mode and Effects Analysis (FMEA) FMEA is an analytical methodology used to ensure that potential problems have been considered and addressed throughout the product and process development process.
It is a Disciplines approach to analysis of the problems.
Through this approach one can anticipates failure. It prevents the re occurrence of the problem. It can be used everywhere and does necessarily required data.
There are various factors takes into account for analysis like Severity of the failure or Effect, Occurrence of the cause, Detection of the Cause & Prevention from occur & RPM risk priority number is product of all to judge the high priority.

(SPC) Statistical Process Control is the use of statistical techniques such as control charts to analyze a process or its output so as to take appropriate actions to achieve and maintain a state of statistical control and to improve the process capability & Performance. It is a type of feedback system that warns organizations to implement a strategy of prevention to control manufacturing process quality outputs.
There are two phases in statistical process control studies.
The first is identifying and eliminating the special causes of variation in the process. The objective is to stabilize the process. A stable, predictable process is said to be in statistical control.
The second phase is concerned with predicting future measurements thus verifying ongoing process stability..
In SPC there are 2 weapons 1 Norma distribution & 2nd is Control Charts.

Measurement Systems Analysis (MSA) connects to measurement data that is used in nearly every manufacturing process. In simple words MSA is a systematic study of the various aspects of the measurement system & its variation. Where Gauge R & R Studies concentrates on Repeatability & Reproducible, MSA Extent to dealing with other aspects like bias Linearity & Stability
For More Details: https://www.aiag.org/
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