Automotive Core Tools

Production Part Approval Process (PPAP) is the only industry standard that ensures engineering design and product specification requirements are met without hindrance. It provides a guideline through which suppliers and customers understand the requirements to obtain part approval of supplier manufactured parts.

It is applicable to all parts and commodities. Further, it reduces delays and non-conformances during part approval. It addresses details pertinent to design records to ensure traceability of part design status at origin; and control the predict an process change process thus providing an approval outlet for all changes to ensure conformance for the next level assembly.

Failure Mode and Effects Analysis (FMEA) is a tool used to identify and address failure modes in products and processes. It is an analytical methodology used to ensure that issues are identified and addressed throughout the product and process development process.

It is an important part of automotive core tools that encompasses risk assessment as a part of its evaluation. The analysis is conducted regarding the designs (of either the product or process), and the functions are reviewed thoroughly. Eventually, it aims at reducing the risk of potential failure.

It is used before developing a control plan for a new or modified process, while improving goals that are planned over the existing process, product or service and when the failures are analysed about the existing process.

Statistical Process Control (SPC) describes several basic and advanced statistical methods to ensure your process improvements are more effective. Statistical techniques such as control charts to analyze a process or its output are utilised. It helps in taking appropriate actions to achieve and maintain a state of statistical control and to improve the process capability.

It helps in controlling quality by closely monitoring manufacturing process. Further, it provides solid ground for organisations to move from detection based to prevention based quality controls.

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. During this phase, data analysis and reaction to special causes is done in real time. Once stable, the process can be analyzed to determine if it is capable of producing what the customer desires.

MSA stands for Measurement System Analysis. It is the measurement data that monitors nearly every process. It is a collection of many statistical analysis methods for evaluating variability in the measurement process. This is a major part of automotive core tools as it helps in data quality improvement and decision making.

It is a guide that helps organisations asses the quality of their measurement systems, by basically identifying areas of improvement. It eventually provides knowledge based on data that can be used to improve measurement process, in turn improving repeatable product quality.