a. Replace or divide (either fully or partially) OBJECT S1 or its action with multiple inexpensive or short-living objects, actions, or sub-parts, which compress or simplify its characteristics and properties, and/or are limited but sufficient to achieve the desired objective.
b. Compress certain qualities of OBJECT S1 (e.g., the degree of participation, complexity, or lifetime), with no loss of functionality, to achieve the desired objective.
Separation principle: Separation in subsystem.
Solution strategy: Improve the 7 quality factors(**).
(**) Quality, Reliability, Maintainability, Supportability, Human Factors, Security, Protection.
Type: Strategic inventive principle.
Examples of Application:
This inventive principle suggests dividing the evaluated object or its action into multiple low-cost, short-living objects to achieve innovation.
For example, these days, it explains major developments, such as digital computing, nanotechnology, and the use of particles that appear in transient phenomena.
It particularly highlights one with significant relevance today, which is artificial intelligence. The Language of Nature's Innovation deduces it from the need for learning from vast amounts of information, which entails a significant workload. This is resolved by using three of the 1248 TRIZ contradictions that address innovation challenges.
These three contradictions are the only ones where the following innovation parameters coincide to replace human action with digital activity for the analysis of vast and variable information:
Par. 26 Copy or replicate, which imitates the human action of analysis through a digital machine.
Par. 27 Inexpensive Short-living Objects, which divides the large volume of information for analysis by a person into many data bits.
Par. 28 Substitution of mechanics, which replaces human analytical mechanics with digital algorithms.
The referenced contradictions for analyzing vast amounts of information are as follows:
a) Contradiction:
Improve More workload or heaviness to identify information accurately and mitigate the lower precision or accuracy of current measurements for critical precision services. Examples: facial recognition, voice language, etc.
Evaluated Object S1: Person who must detect information accurately
Evaluated Object S2: Source of voluminous information to analyze
Solution to improve (+) 1. Heaviness of mobile object and attenuate (-) 28. Measurement accuracy, considers the following inventive principles IP. [28, 27, 35, 26].
b) Contradiction:
Improve the difficulty of detecting or measuring behavior or patterns and mitigate the heaviness or workload. Examples: customer behavior, consumption, processes, etc.
Evaluated Object S1: Person who must detect relevant information
Evaluated Object S2: Source of voluminous information to analyze
Solution to improve (+) 37. Difficulty of detecting or measuring and mitigate (+) 1. Heaviness of mobile object: Inventive principles [27,26,28,13].
c) Contradiction:
Improve the ease of achieving the desired outcome and preserve the efficient use of energy. Examples: industrial process productivity, labor force performance, etc.
Evaluated Object S1: Person managing productivity
Evaluated Object S2: Source of voluminous information to manage
Solution to improve (+) 32. Ease of achieving the desired outcome and preserve (+) 1. Energy use of mobile object: Inventive principles [28,26,27,1].
The interpretation of a contradiction depends on the context in which it is analyzed; therefore, the previous contradictions will correspond to an application of artificial intelligence, as long as they are combined with a larger volume of information to be analyzed by a person, which involves using the innovation parameters Par.7. Volume of mobile object or Par.8. Volume of stationary object. Additionally, in each specific case, there may be other undesirable effects that need to be considered to obtain a comprehensive solution.
Considering the above, the following is a challenge formulation for facial recognition, which leads to the application of artificial intelligence.
Facial Recognition Case
To improve facial recognition, where Object S1: Facial identification inspector interacts with Object S2: Multi-dimensional-faced individual. For more details, refer to the link for solved cases, Case No. 19.
Object S1 has the following undesirable effects:
Par.1 Heaviness of moving object: Increased weight due to the workload of facial identification for many individuals throughout the day.
Par.7 More volume of moving object: Increased volume of visual information to process for precise facial identification throughout the day.
Par.11 Stress/pressure: Elevated work-related stress due to the workload of facial identification for many individuals throughout the day.
Par.12 Shape/Composition/Configuration: Less suitable shape for facial identification of many individuals throughout the day.
Par.24 Loss of information: More information loss due to details that go unobserved in the facial identification of many individuals throughout the day.
Par.28 Measurement accuracy: Reduced precision in facial identification of many individuals throughout the day.
Par.35 Adaptability or variability: Diminished adaptability to the variability of the individuals to be identified throughout the day.
To improve facial recognition, the following desirable effect has been selected for the facial identification inspector:
Par.19 Energy use of moving object: More efficient use of energy by the facial identification inspector.
The application of the Aatrizinventor algorithm allows for the selection, based on the sensitivity analysis it provides, of an optimal combination of innovation parameters and their corresponding contradictions to provide a solution to the analyzed challenge.
The selected undesirable effects are as follows:
Par.1 Heaviness of moving object
Par.11 Pressure/ Tension
Par.28 Measurement accuracy
Par.35 Adaptability or Versatility
The selected desirable effect is:
Par.19 Use of energy by moving object
This selection ranks second among the 10 recommendations provided by the sensitivity analysis.
The algorithm selects a solution that considers 8 contradictions. For more details, refer to the link for solved cases, Case No. 19. The essential contradiction of the evaluated case is IP.[35,5,1,10], which states:
The physical state of Evaluated Object S1, the Facial Identification Inspector (IP.35 Transformation / Parameter Changes), must be transformed
by merging it with another object that facilitates the achievement of the desired goal (IP.5 Merging/Separating), in this case, a facial identification system based on artificial intelligence that is mentioned in the recommended complementary contradiction No. 3.
Object S1 must be segmented into two parts, Inspector and indicated AI, adding new functions (IP.1 Segmenting/Integrating),
and finally, the required changes must be made in advance (IP.10 Preliminary Action)
Complementary contradiction No. 3 allows for the recommendation of artificial intelligence, where the contradiction Par. [+1, -28] is applied, considering the following inventive principles IP. [26, 30, 36, 34], which state:
IP.28 Mechanics Substitution
Replace the current identification mechanics that use the natural visual field of the Facial Identification Inspector* with a digital optical field for a high-resolution image sensor, with the capability to process and validate the captured information.
27. Cheap Short-Living Objects
Replace the identification mode of the Facial Identification Inspector* with multiple low-cost and easy-to process and validate digital vision objects that simplify the action of the Facial Identification Inspector*, sufficient to achieve the desired outcome.
IP.35 Transformation / Parameter Changes
Replace the identification mode of the Facial Identification Inspector* with multiple low-cost and easy-to process and validate digital vision objects that simplify the action of the Facial Identification Inspector*, sufficient to achieve the desired outcome.
IP.26 Copying/ Replicating
- Instead of using the Facial Identification Inspector or any of its parts or properties, which may not be available, be expensive and/or fragile, it is recommended to use simpler and more economical copies or replicas to fulfill the desired function, and if possible, with improved features and properties for accurate information detection. Harmful, unwanted, or unnecessary characteristics should be discarded. In this case, facial identification with imprecise natural vision is replaced by a digital application of artificial intelligence.
Another example of inventive principle No. 27 can be found in the link for solved cases, Case No. 7, which addresses the challenge of Object S1: Locking pin operating in the locking mechanism of the inspection hatch of the loading door of the Estonia ferry, which experiences damage in its interaction with Object S2: Male-female parts of the mechanism.
To improve the lower operating strength of the Locking Pin* (Par.14 Strength/Resistance) and preserve the ease of changing the Locking Pin* (Par.34 Ease of change, repair, or maintain), the contradiction Par.[14,9] is applied, considering the following inventive principles IP.[27,11,3,0]. The specific application is shown below:
27. Inexpensive or Short-lived Objects
The Locking Pin* should be replaced with multiple low-cost objects or subparts. Supported by other contradictions associated with this case, the pin* is changed from a cylindrical shape to a conical shape. Here, a cone is understood as a piece composed of multiple conical parts of different diameters that together form a cone (this is a good example of relational thinking, which has no limits except for your paradigms).
IP.11 Beforehand Cushioning
The conical shape of the Locking Pin* allows for beforehand compensation of the undesirable effects that are anticipated to occur if the damaged pin is replaced again with a cylindrical one.
IP.3 Local Quality
The pin* must be modified in a localized manner by changing its shape from uniform to non-uniform, from cylindrical to conical.
In the TRIZ Contradiction Matrix, 10.18% of the identified contradictions contain the strategic inventive principle No. 27.
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