Quality core Tools
Introduction to?Quality Core Tools
In the highly competitive environments of Automotive / Manufacturing, organizations are challenged with three simultaneous and equally momentous goals:
To succeed in all three, the Quality Management System (QMS) standard IATF 16949 has evolved to guide these industries. The specific expectations of IATF 16949 are supported by the Quality Core Tools. When applied properly, the Quality Core Tools are the value-added methods and techniques that make it possible for an organization to achieve all three goals.
What are the Quality Core Tools
The Quality Core Tools are five supplemental techniques and/or methods that support the expectations of IATF 16949. These tools are documented separately through the publication of five manuals available through the Automotive Industry Action Group (AIAG). The traditional five core tools are listed in their order of use when designing products or processes:
An additional core process included in Quality Core Tools discussions by Quality-One is:
What is Advanced Product Quality Planning
Advanced Product Quality Planning (APQP) is a toolbox of methods and techniques which are used to assure product quality by communicating requirements, specifications, and risks. APQP is a structured approach to product and process design that facilitates communication between suppliers, design communities, and customers.?APQP supports the never-ending and relentless continuous improvement intent of IATF 16949. There are five sections or phases of APQP with an additional Input phase:
What is Failure Mode and Effects Analysis (FMEA)
Failure Mode and Effects Analysis (FMEA) is a structured approach that identifies potential failure modes and effects, coupling them with potential causes of failure. A technical risk level is assigned to each combination. When the risk is deemed to be too great for the product or process being studied, actions are identified to mitigate the risk. FMEA also reviews the testing and evaluation techniques that can determine product design integrity and reliability (Design FMEA) or product quality (Process FMEA).
Evaluating risk and taking mitigating action is beneficial by preventing a failure before it is ever experienced. Several factors are utilized in the development of FMEA:
The use of FMEA permits other team members to review the work of the Design or Manufacturing / Process Engineer. Subject Matter Experts (SMEs) use their experience to judge the potential for failure at a time in the product/process development where changes can still be performed without much impact on program cost or timing.
What is Measurement Systems Analysis (MSA)
Measurement Systems Analysis (MSA) is an experimental process that determines the viability of an evaluation/measurement technique for use on a specific part characteristic. The need to make good quality decisions is the most important aspect of quality assurance and control. If the measurement system selected has too much variation or is unstable, an unacceptable product could be approved, resulting in customer dissatisfaction or worse. Conversely, the acceptable product could be rejected, applying additional pressure on the organization to react to a condition that does not require action. Error in the measurement system is inevitable. Many assume that the measurement is absolute, which unfortunately is not true. Many times, the measurement system may be completely unacceptable and requires replacement or considerable improvement.
MSA looks at five distinct parameters:
Guidelines for acceptance are based on two principles:
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The guidelines for acceptance are as follows:
What is Statistical Process Control (SPC)
Developed by Walter Shewhart at Bell Telephone, Statistical Process Control (SPC) is a collection of statistical techniques intended to understand the behavior of a system. SPC uses the primary statistical principles of Central Tendency (Mean, Median and Mode) and Variation (Spread or Standard Deviation). A process under study will reveal if it is operating in a stable and predictable way or in control.
The Normal Distribution
SPC is generally based upon the normal distribution. The Normal Distribution depicts a bell shape with known percentages in the area under the curve. The location of the curve (the central tendency) directly relates to the specification of the characteristic being measured. The spread of the curve is determined by adding 3 standard deviations (sometimes referred to as sigma) on each side of the central tendency. The percentage of product fitting under the curve can be applied to the process under study. For example:
If a process is running normally, its output will fit this percentage model. SPC utilizes the control chart to show the output “in real time”, shortening the reaction time if something does not agree with a previously proven process.
Control Charts
Control Charts are typically used to indicate patterns which may be different than the expected bell curve percentages. When a pattern is observed, the process is out of control and actions to investigate are common. Control Charts fall into two categories, variable and attribute. Variable Control Charts utilize data which, when plotted on the chart, can be interpreted. Attribute Control Charts show performance of a Go / No Go data set.
Variable control charts typically come in pairs; one for the central tendency and another for the spread. Each chart has a line drawn for the measurement of central tendency and control limits, equidistant lines on either side of the central tendency. The control limit lines equate to the expected spread at ±3 standard errors based on the sample size of the group or subgroup.
Samples are chosen at specified frequencies and the two points, one for central tendency, the other for spread, are plotted. The plotted points are evaluated along with up to six previous points. The stability of the process is determined through the following criteria:
When this criterion is used, the chart can indicate what will likely come next. Out of control does not relate to bad product, just different from previous experience. A chart may indicate an out of control condition but upon close examination, the analyst may want to keep it that way and establish a new best case.
Attribute control charts only depict conditions which are unacceptable. Actions are performed to improve the undesirable state.?Attribute control charts are often linked to continuous improvement because they can be excellent visual aids to show progress.
What is Production Part Approval Process (PPAP)
Production Part Approval Process (PPAP) is a standardized process in the automotive and aerospace industries.?PPAP demonstrates through documentation that as manufactured, the product and process perform as specified by design intent and purchasing requirements. The elements of PPAP are related to APQP in that they are created at key times during product and process design. The evidence of conformance is collected and provided as validation of proper planning. PPAP promotes a clearer understanding of the requirements to manufacturers and suppliers. PPAP also helps to ensure that the processes selected to manufacture parts can consistently reproduce the parts at planned production volumes. For automotive industry suppliers, the PPAP process is currently governed by the PPAP manual published by the Automotive Industry Action Group (AIAG).
PPAP is deployed at five levels based on risk. The lowest risk levels are 1 and 2 and are reserved for simple designs and well respected suppliers / manufacturers. Level 3 is the default, which requires all applicable elements be provided. Level 4 is the customized selection, used when specific changes require closer examination. Level 5 is reserved for the greatest risk parts and suppliers. When level 5 is indicated, additional supplier-customer collaboration is required. Level 5 often results in customer visitation during key core tool development and possibly during the first production trial run. The PPAP submission is similar to sample submissions used in many industries, however PPAP documentation must include prevention tools in addition to those which show product and process conformance.
A Cross Functional Team (CFT) is needed to complete PPAP documentation, as there are elements requiring input from:
Why?Use Quality Core Tools
The Quality Core Tools are used during the Product and Process Development phases of?New Product Introduction (NPI)?and during certain events such as experienced failure or engineering changes. The Quality Core Tools methodology from Quality-One harmonizes and links the inputs and outputs of the core tools to one another. Unlike many who see the tools as independent, linked tools increases their value to one another and reduces overall workload.
The main goals for any project are:
APQP and FMEA assure quality through prevention activities related to risk. APQP additionally supports on time delivery through planning and enhanced communication. Evidence of achieved quality is gathered by using superior gage systems validated through MSA and data collected and analyzed using SPC. Reviewing the Quality Core Tools, from inputs to outputs, an analyst would observe:
The common thread that all Quality Core Tools share are the Special Characteristics. Each tool receives Special Characteristics and either refines them, treats them or eliminates the need for them. Progress is measured based on the number of risks discovered and mitigated prior to PPAP.
How to Apply Quality Core Tools
Quality Core Tools are applied sequentially and collaboratively. Collaborative Product Process Design (CPPD)?depicts both a timing overlap of activities and a cross-functional communication between engineering communities.
Each Quality Core Tool’s output is linked to other tools in the Product Quality Plan. The timing for Quality Core Tools should be early product / process development as practical. Waiting until the last minute is not efficient and has a low / no impact on quality. The creation of the paperwork to “check the box” has no redeeming benefit to an organization.
An example of the value-added linkage can be demonstrated using the DFMEA and PFMEA relationships:
A more detailed application of the Quality Core Tools can be found by exploring the following links: