Failure Mode and Effects Analysis (FMEA) is a structured approach to discovering potential failures that may exist within the design of a product or process.

Failure modes are the ways in which a process can fail. Effects are the ways that these failures can lead to waste, defects or harmful outcomes for the customer. Failure Mode and Effects Analysis is designed to identify, prioritize and limit these failure modes.

FMEA is not a substitute for good engineering. Rather, it enhances good engineering by applying the knowledge and experience of a Cross Functional Team (CFT) to review the design progress of a product or process by assessing its risk of failure.

There are two broad categories of FMEA, DFMEA and PFMEA.
Design FMEA

Design FMEA (DFMEA) explores the possibility of product malfunctions, reduced product life, and safety and regulatory concerns derived from:

• Material Properties
• Geometry
• Tolerances
• Interfaces with other components and/or systems
• Engineering Noise: environments, user profile, degradation, systems interactions
Process FMEA

Process FMEA (PFMEA) discovers failure that impacts product quality, reduced reliability of the process, customer dissatisfaction, and safety or environmental hazards derived from:
• Human Factors
• Methods followed while processing
• Materials used
• Machines utilized
• Measurement systems impact on acceptance
• Environment Factors on process performance

A Control Plan is a method for documenting the functional elements of quality control that are to be implemented in order to assure that quality standards are met for a particular product or service. The intent of the control plan is to formalize and document the system of control that will be utilized.

Seven attributes to consider when creating a control plan are:

• 1.1 Measurements and Specifications. …
• 1.2 Input/Output to a Process. …
• 1.3 Processes Involved. …
• 1.4 Frequency of Reporting and Sampling Methodology. …
• 1.5 Recording of Information. …
• 1.6 Corrective Actions. …
• 1.7 The Process Owner. …
• 1.8 Summary.

How to Develop a Control Plan
1. Process Flow Diagram.
2. Design Failure Mode and Effects Analysis (DFMEA)
3. Process Failure Mode and Effects Analysis (PFMEA)
4. Special Characteristics Matrix.
5. Lessons Learned from similar parts.
6. Design Reviews.
7. Team knowledge about the process.
8. Field or warranty issues.

Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method. SPC tools and procedures can help you monitor process behavior, discover issues in internal systems, and find solutions for production issues.

SPC is method of measuring and controlling quality by monitoring the manufacturing process. Quality data is collected in the form of product or process measurements or readings from various machines or instrumentation. The data is collected and used to evaluate, monitor and control a process. SPC is an effective method to drive continuous improvement. By monitoring and controlling a process, we can assure that it operates at its fullest potential. One of the most comprehensive and valuable resources of information regarding SPC is the manual published by the Automotive Industry Action Group (AIAG).

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 the expense, time and production delays that would incur. Prior to SPC implementation the key or critical characteristics of the design or process should be identified by a Cross Functional Team (CFT) during a print review or Design Failure Mode Effect Analysis- DFMEA exercise. Data would then be collected and monitored on these key or critical characteristics.

MSA is defined as an experimental and mathematical method of determining the amount of variation that exists within a measurement process. Variation in the measurement process can directly contribute to our overall process variability. MSA is used to certify the measurement system for use by evaluating the system’s accuracy, precision and stability.

What is a Measurement System?

Before we dive further into MSA, we should review the definition of a measurement system and some of the common sources of variation. 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 can 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.

Complex products and supply chains present plenty of possibilities for failure, especially when new products are being launched. Advanced Product Quality Planning (APQP) is a structured process aimed at ensuring customer satisfaction with new products or processes.

APQP has existed for decades in many forms and practices. Originally referred to as Advanced Quality Planning (AQP), APQP is used by progressive companies to assure quality and performance through planning. Ford Motor Company published the first Advanced Quality Planning handbook for suppliers in the early 1980’s. APQP helped Ford suppliers develop appropriate prevention and detection controls for new products supporting the corporate quality effort.

5 Phases of APQP: The Nuts and Bolts

• Product Planning and Quality Program Definition.
• Product Design and Development.
• Process Design and Development.
• Validation of Product and Process.
• Production Launch, Assessment, and Improvement.

Production Part Approval Process (PPAP) is a valuable tool for establishing confidence in component suppliers and their production processes. In today’s competitive manufacturing environment controlling cost and maintaining a high level of quality have become vital to a company’s success.

PPAP defines the approval process for new or revised parts, or parts produced from new or significantly revised production methods. The PPAP process consists of 18 elements that may be required for approval of production level parts. Not all of the elements are required for every submission. There are five generally accepted PPAP submission levels. The PPAP manual contains detailed information, guidelines and sample documents useful for completing the process requirements. The resulting PPAP submission provides the evidence that the supplier has met or exceeded the customer’s requirements and the process is capable of consistently reproducing quality parts.

A PPAP is required for any new part submission as well as for approval of any change to an existing part or process. The customer may request a PPAP at any time during the product life. This demands that the supplier must maintain a quality system that develops and documents all of the requirements of a PPAP submission at any time.

PPAP Levels of Submission

The PPAP submission requirements are normally divided into five classifications or levels, as follows:

• Level 1 – Part Submission Warrant (PSW) only submitted to the customer
• Level 2 – PSW with product samples and limited supporting data
• Level 3 – PSW with product samples and complete supporting data
• Level 4 – PSW and other requirements as defined by the customer
• Level 5 – PSW with product samples and complete supporting data available for review at the supplier’s manufacturing location