The automotive industry has to meet increasing quality demands. To achieve that, AIAG (Automotive Industry Action Group) has established the so-called Automotive Core Tools, methods that are essential for planning and control purposes during the product development processes. These quality methods, based on IATF 16949, support employees in improving procedures and are fundamental for an effective quality management system, in accordance with the current requirements of the automotive industry. Over 30 years ago, AIAG (Automotive Industry Action Group) and ASQ (American Society of Quality) in collaboration with the automotive manufacturers Ford, GM, and Chrysler (now FCA) established these quality methods and tools to enhance the effectiveness of the IATF 16949-based QMS in order to provide high-quality products, delivered on time.
The Automotive Quality Core Tools are quality management methods used to ensure high process and product quality along the entire supply chain. 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). Below, we will go through these five core tools, which are the keystone of a quality system that aim to achieve successful manufacturing.
What is APQP?
APQP is a systematic Approach to Advance Quality Planning that describes the steps and activities have to be carried out in order to guarantee a high-quality product for the end customer. APQP is a structured process with standardized methods such as Design & Process FMEA, the PPAP process, as well as various documentation and commercial requirements.
The main objective of the APQP process is the production control plan, which serves as the basis for series production and establishes a clear path for planning, implementing and verifying a process. The goal of APQP is to facilitate communication between the design team and the rest of the organization. The APQP process is cross-functional, so teams can work together to design a product that meets the customer requirements, and it is produced with minimal costs and labor. When there are problems, they can be early identified early in the process, while the cost to change or fix them is still low. This will reduce the overall lifecycle costs of designing, manufacturing and supporting a product. Often the design costs are higher earlier on, but the manufacturing and support costs are much less, therefore, you can save money during these processes and customers get satisfied as they get their product on-time with higher quality.
APQP uses a five-phase process:
1- Product planning and quality program definition
This phase is about understanding the customer’s needs and product expectations. Planning activities include gathering relevant data to define what the customer wants and use the information to hash out product characteristics. The output of this work includes product design, reliability, and quality goals.
2- Product design and development
This phase include tasks such as:
- Design reviews.
- Material specifications and equipment requirements.
- Design failure mode and effect analysis to assess failure probabilities.
- Setting up control plans for product prototype creation.
3- Process design and development
This phase focuses on planning the manufacturing process and the main objective is to design and develop the production process whilst keeping product specifications, product quality, and production costs in mind. This process must be able to produce the quantities needed to meet consumer demand while maintaining efficiency. You should also identify risks and the way to deal with them.
4- Validation of product and process
This is the test phase for validating the manufacturing process and the final product and include the following steps:
- Checking reliability of the manufacturing process and product quality.
- Performing production trial runs
- Testing product output to confirm the effectiveness of the manufacturing process.
5- Launch, assessments, and continual improvement
This phase focuses on evaluating and improving processes. It includes the following processes: reducing process variations, identifying issues, and starting corrective actions to support continual improvement, as well as collecting and assessing customer feedback and data related to process efficiency and quality planning effectiveness.
What is PPAP?
Production Part Approval Process (PPAP) is an important part of the comprehensive Advanced Product Quality Planning (APQP) that was developed by the Automotive Industry Action Group (AIAG). PPAP is an output of APQP that can help you to get a clearer understanding of the requirements of manufacturers and suppliers. PPAP helps ensure that the manufacturing processes can consistently reproduce the parts during routine production runs.
What is included in a PPAP?
The PPAP manual contains a checklist, which includes all the requirements for a complete PPAP package. The checklists identify different PPAP levels (from 1 to 5). This tool involves gathering all the data and information that was generated throughout the APQP stage that should be presented to the customer for review and approval.
The elements of PPAP are:
- Design documentation
- Engineering change documentation
- Customer engineering approval
- Design failure mode and effects analysis
- Process flow diagram
- Process failure mode and effects analysis
- Control plan
- Measurement system analysis studies
- Dimensional results
- Records of material / performance tests
- Initial process studies
- Qualified laboratory documentation
- Appearance approval report
- Sample production parts
- Master sample
- Checking aids
- Customer specific requirements
- Part submission warrant
What is Failure Mode and Effects Analysis (FMEA)?
Failure Mode and Effects Analysis (FMEA) is a structured approach to discover potential failures within the process of design a product.
Failure modes are the ways in which a process can fail and the effects are the ways that these failures can lead to waste or harmful outcomes for the customer. FMEA is one of many tools used to discover failure at its earliest possible point in products or in processes. Discovering a failure early in Product Development (PD) using FMEA can bring the following benefits:
- Several choices to reduce risks.
- Higher capability of verification and validation of changes.
- Collaboration between different processes and stages.
- Improved design for manufacturing and assembly (DFM/A)
- Lower cost solutions
- Legacy, tribal knowledge, and standard work utilization
Ultimately, this methodology is effective at identifying and correcting process failures early on so that you can identify and avoid harmful consequences while prioritizing and limiting failure modes.
These are the steps involved in FMEA:
- Decide which FMEA you will perform and gather the necessary information
- Identify potential failure modes
- Do a failure effect and cause analysis
- Assign severity rankings
- Assign occurrence rankings
- Evaluate and assign failure detection rankings
- Take action
- Recalculate RPN
What is Statistical Process Control (SPC)?
SPC is a method used to control quality by monitoring the manufacturing process. Quality data is collected in the form of product or process measurements or readings from various machines or tools. By monitoring and controlling a process, we can assure that it run at its fullest potential.
Why Use Statistical Process Control (SPC)
In general, companies aim for continuous improvement in quality, efficiency and cost reduction. The SPC process can help you with that. By monitoring the performance of a process in real time, the operator can detect trends or changes in the process before they result in non-compliant product and discard.
How to Use Statistical Process Control (SPC)
Before implementing SPC or any new quality system, the manufacturing process should be evaluated to determine the main areas of waste. Some examples of manufacturing process waste are rework, scrap and excessive inspection time. It would be most beneficial to apply the SPC tools to these areas first. During SPC, not all dimensions are monitored due to expenses, time and production delays that might cause. Prior to SPC implementation, a Cross Functional Team (CFT) should identify the most relevant characteristics during a Design Failure Mode and Effects Analysis (DFMEA) exercise. After that, data should be collected and monitored. Quality data in the form of Product or Process measurements are obtained in real-time during manufacturing. This data is plotted on a graph with pre-determined control limits that are determined by the capability of the process, whereas specification limits are decided by the client’s needs.
With real-time SPC you can:
- Reduce costs
- Scientifically improve productivity
- Reduce variability and scrap
- React faster to process changes
- Make real-time decisions on the shop floor
What is a Measurement System Analysis (MSA)?
A measurement system has been described as a system of related measures that enables the quantification of particular characteristics. It can also include a collection of gages, fixtures, software and personnel required to validate a particular unit of measure or make an assessment of the feature or characteristic being measured. The sources of variation in a measurement process include the following:
- Process – test method, specification
- Personnel – the operators, their skill level, training, etc.
- Tools / Equipment – gages, fixtures, test equipment used and their associated calibration systems
- Items to be measured – the part or material samples measured, the sampling plan, etc.
- Environmental factors – temperature, humidity, etc.
All of these possible sources of variation should be considered during Measurement System Analysis. Evaluation of a measurement system should include the use of specific quality tools to identify the most likely source of variation. Most MSA activities examine two primary sources of variation, the parts and the measurement of those parts. The sum of these two values represents the total variation in a measurement system.
Why use core quality tools?
The goal of the core tools is to provide high-quality products meeting or exceeding the automotive industry’s requirement and customer expectations. The Automotive Quality Core Tools are key pillars of an effective quality management system. These tools can not only assure compliance with the industry standards, but also a continual improvement of the production and delivery processes throughout the entire supply chain.