Using TRIZ to Enhance Quality Functional Deployment
By Ellen Domb
The Theory of Inventive Problem Solving (TRIZ) was developed by Genrich Altshuller and his colleagues in the former Soviet Union in 1946 and is practiced throughout the world. TRIZ research began with the hypothesis that there are universal principles of invention that are the basis for creative innovations that advance technology, and if these principles could be identified and codified, they could be taught to make the process of invention more predictable. More than two million patents have been examined, classified by level of inventiveness and analyzed to look for principles of innovation. The three primary findings of this research are:
- Problems and solutions were repeated across industries and sciences.
- Patterns of technical evolution were repeated across industries and sciences.
- Innovations used scientific effects outside the field where they were developed.
Much of the practice of TRIZ consists of learning the repeating patterns of problems/solutions and patterns of technical evolution, methods of using scientific effects, and applying general TRIZ patterns to the specific situation confronting the inventor. See Figure 1.
|
Early research conducted by the author indicated that inventors using TRIZ experienced an increase of 70 to 300 percent in the number of creative ideas generated for solving technical problems and also in the speed with which they generated innovative ideas. TRIZ was first introduced to practitioners of quality function deployment (QFD) in the United States at the 7th, 8th and 9th Annual QFD Symposiums and in Japan in 1995, and the appeal was immediately seen.
QFD won proponents because of the clarity with which it identified customers’ needs, organizational technological capabilities, design properties, reliability problems, functional capabilities and the relationshipsamong these factors. Many QFD users found themselves overwhelmed with the richness of these data. After understanding the relationship between the customers’ needs and their abilities to satisfy those needs, they wanted help creating innovative product and service designs to meet or exceed the customers’ needs. TRIZ is a family of tools that helps QFD practitioners use innovation to satisfy customers.
QFD and TRIZ
TRIZ tools can be used in a variety of stages of quality function deployment, and they can be organized in many different ways. Using a flowchart is an effective way to introduce TRIZ tools and explain how they are related. Figure 2 is a typical flowchart used for either a product design or process development problem.This flowchart displays many TRIZ tools. (Not shown on the flowchart are s-field analysis – a diagrammatic modeling system used for describing problems and identifying categories of solutions, used for difficult or advanced problems, and ARIZ (Algorithm for Inventive Problem Solving). ARIZ is a non-computational algorithm consisting of a series of more than 70 questions and is an alternate way of linking the tools and techniques of TRIZ.)
|
Analysis
The first stageis analysis. Tools shown on the flowchart that assist in analysis are:
- Functional analysis: This is familiar to QFD practitioners. Analyze the system, sub-systems and components in terms of the functions performed (not the technologies used). One technique in TRIZ is “trimming” – examining each function to see if it is necessary and, if it is, whether any other element of the system could perform the function. Breakthrough designs and reductions in cost and complexity are frequent results of functional analysis and trimming.
- The ideal final result (IFR): Familiar to QFD users as the customers’ demanded quality. Express the situation in terms of why the innovation is needed, using technology- and implementation-independent language. Strategic breakthroughs frequently come from the insight gained at this step. Quality improvement opportunities can be identified finding what elements make the system non-ideal. The progress that a design makes from a starting point toward the ideal final result is called “ideality” and is defined using the value equation as:
Ideality =S Functions useful / S (Functions harmful + Cost)
- Resource analysis: Identify the available things –energy sources, information, functions and other elements that are in or near the system that could be combined with the elements of the system to improve it. In the book, Step-by-Step TRIZ: Creative Solutions to Innovative Problems written by John Terninko, Alla Zusman and Boris Zlotin, the authors noted that QFD practitioners discovered that being aware of the uses of resources in TRIZ changed the way they conducted customer observation visits.
- Locating the zone of conflict: Familiar to quality improvement researchers as root cause analysis. This step focuses on understanding the exact cause of the problem. The “zone” refers to the time and place that the problem occurs.
Data-based Tools
If the problem has been solved in the analysis phase, developers frequently proceed to implementation. If it has not been solved, or if alternate solutions are desired for maximum creativity, the data-based tools – principles, prediction and effects – are used. Many TRIZ applications use all three of the data-based tools. The flowchart shows a decision (diamond symbol) indicating the choice of tools.
- Principles (also called resolution of contradictions) andtechnical contradictions are classical engineering trade-offs. The desired state cannot be reached because something else in the system prevents it. Physical contradictions are situations where one object has contradictory, opposite requirements. TRIZ guides the developer to design principles that resolve the contradiction and define itin terms of standard parameters.
- Prediction (also called technology forecasting) is another data based tool of TRIZ. TRIZ identifies eight patterns of technical evolution. Designs of systems, sub-systems or components can be deliberately moved to the next higher stage within a particular pattern once the pattern is identified. The eight patterns are:
- Increased ideality
- Stages of evolution
- Non-uniform development of system elements
- Increased dynamism and controllably
- Increasing complexity, then simplicity
- Matching and mismatching of parts
- Transition to micro-level and use of fields
- Decreased human interaction (increased automation)
- Effects is the third data-based tool and focuses on using scientific and engineering phenomena and effects outside the discipline in which they were developed. Tools include databases, science encyclopedias and searches of the technical literature to find alternate ways to achieve the functions needed to solve the problem. Classical examples include the use of geometrical solutions to mechanical problems (use of a Mobius strip doubles the lifetime of a belt) and use of biological solutions to chemical problems (tailored bacteria that “eat” contaminants, instead of complex filters) as well as using common science froma known area and applying it inanother way (Carbon-14 dating was well-known in chemistry for 30 years before archaeologists learned about it).
Evaluation of Solutions
The last block in the flowchart is evaluation of solutions. Solutions are compared to the IFR, to be sure that the improvements advance the technology and meet the customers’ needs. Multiple solutions may be combined to improve the overall solution using a feature transfer.The flowchart shows that remaining problems are resolved by iterating the process. The advantage of TRIZ is that the iterations are fast and a great number of innovative ideas are developed at each stage.
The general problem solving process of TRIZ can be used whenever the product or process developer has inventive problems. Specific tools that may be useful by themselves in quality function deployment are shown in the table below;the stages of QFD in which they are useful are also indicated.
TRIZ Tools Used Throughout QFD | |||||||||
|
Quality Function Deployment Stages |
||||||||
TRIZ Techniques | Product Planning | Visit the Gemba (Manufacturing Floor) | Voice of the Customer | Demanded Quality Deployment | Reliability Deployment | Function Deployment | Concept Selection | Component Selection | Production Planning |
Ideal Final Result |
X |
|
|
X |
X |
X |
X |
|
|
Technology Forecasting |
X |
|
|
X |
X |
|
X |
X |
|
ResolvingContradictions |
X |
X |
X |
X |
X |
X |
X |
X |
X |
Use of Resources |
|
X |
|
|
|
|
X |
X |
X |
Functional Analysis |
X |
|
|
X |
X |
X |
|
|
X |
Trimming |
X |
|
|
X |
X |
X |
|
|
X |
Scientific Effects |
|
|
|
|
|
|
X |
X |
X |
Feature Transfer |
X |
X |
|||||||
Anticipatory Failure Determination |
X |
Summary
TRIZ can enhance the practice of QFD. Researchers will continue to find ways to integrate these methods to help all product and process developers create innovative solutions that win market leadership by solving customer problems.
About the Author:
Ellen Domb is the founder and principal TRIZ consultant of the PQR Group. She is also the founding editor of The TRIZ Journal and a commentator for Real Innovation. Contact Ellen Domb at ellendomb (at) trizpqrgroup.com or visit http://www.trizpqrgroup.com.