method of claim-based technology analysis for strategic...
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Journal of Intellectual Property Rights Vol 21, July 2016, pp 243-259
Method of Claim-Based Technology Analysis for Strategic Innovation
Management – Using TPP-Related Patents as Case Examples
Chia-Wei Jui†,1 Amy J. C. Trappey2 and Chien-Chung Fu3
1,3Institute of Nano Engineering and Micro Systems, National Tsing Hua University, Taiwan 2Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan
Received 21 December 2015; accepted 18 July 2016
Analysis of patents reveals trends in technology development in given domains, particularly for commercial adaptation concerning intellectual property (IP) protection. Such an approach allows enterprises to track IPs and evaluate their potential competitiveness vis-à-vis their competitors. Patent clustering is a core step of the entire patent analysis process for conducting technology analysis and can be utilized to group various patents into relatively consistent categories. Forecasting methods are used to develop optimal R&D strategies and anticipate potential outcomes. However, current clustering methods for such technology forecasting, based on general patent keywords or text mining have difficulty in carrying out categorization efficiently and precisely to provide decision makers with insights into technological trends. This research develops a new methodology of patent claim-based technology clustering to predict IP protected technology frontiers as the
critical references for the strategic innovation planning. An in-depth patent analysis case study is conducted on two photon polymerization (TPP) technology to demonstrate the generalized methodology working in practice. With annotated elements in independent claims of patent documents, patentable features are identified for given patents. The patentable features to achieve the task of simplification have been highlighted. Afterward, patents are clustered in accordance to the identification of patentable features in the simplified sentences to provide the clusters with names and definitions. The proposed approach establishes a unique clustering principle so as to enhance the accuracy and credibility of patent analysis based on the legally protected patent claims. This approach provides insight into the landscape of future technological trends, particularly for TPP technologies.
Keywords: Patent analysis, Two Photon Polymerization (TPP), claim based technology analysis, patent clustering, independent claim, patent search
Two photon polymerization (TPP) is a branch of
various technology segments used in three
dimensional (3D) object fabrication (also known as 3D printing), which has been successfully applied
experimentally since the 1960s through the use
of pulsed ruby lasers.4
Many patents related to TPP processes have been issued for subsequent
improvements. Fig. 1 shows USPTO application
trends related to TPP patents from 1967 to 2014. Firms require insight into technical trends not only
to prevent unproductive investments but also to obtain
information relating to an emerging technology and its market opportunity for future applications. Patent
analysis is a well-known method used to identify
technological developments. The visualization expression for the result of patent analysis is called
patent maps, which are used to present complex
patent information in formats easily understood and
interpreted in both technical and managerial perspectives. Patent maps are created from
quantitative and qualitative analyses of patent
documentation in domain-specific technologies.10
The quantitative analysis is based on statistical
processing of patent bibliographical information,
e.g., the number of patent applications, assignees, inventors, applicant names and countries of origin,
etc. On the other hand, the qualitative approach analyzes the contents of patents, and often presents
technical aspects through matrix or tree formations.
The maps in managerial aspects comprise statistics of data relating to bibliographies of patents such
as assignees, countries, application dates, issued
dates, classification codes, citations and other usable bibliographical information. Moreover, the
technology-oriented maps are presented in a
form such as a technology/function matrix or a tree-structured form showing the development of
concerned field of specialities.11
—————— †Corresponding author: Email: [email protected]
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Fig. 1−TPP patent application trends from 1967-2014
Accordingly, patent maps are also called
technology roadmaps and are used to provide
managers with useful information for strategic innovation management, especially for executives
responsible for decision making related to
technology investment. However, the toughest problem in the analysis performed with
patent technology maps involves carrying out
categorization efficiently and precisely to provide decision makers with information reliable
enough to show true insight into market trends.
This is also the most significant criticism of the traditional clustering approach.
26
Hence, an alternative approach has been
developed to assess patent-claim based technology in a way that addresses the shortcomings of patent
clustering methods. The research focuses on
performing technology analysis using claim-based clustering. The TPP technique has been used as a
case example. Different from traditional k-means clustering algorithm for patent analysis, the new
methodology efficiently identifies the patentable
features of independent claims from patent documents. This facilitates the prediction of critical
technology applications and trends. The proposed
methodology also helps to precisely identify market trends for strategic innovation planning
Two Photon Polymerization (TPP)
Two Photon Polymerization (TPP) uses a
locally-focused high-intensity light to cause photo-polymerization in a resin, converting it from
liquid to solid.9 For instance, TPP can locally-focus
a near-infrared femtosecond laser on a photo-polymerizable resin to create 3D micro-
nanostructures. The TPP technique uses femtosecond
laser pulses with photosensitive materials1-2, 28
and is based on the phenomena of two-photon absorption
(TPA) which was first proposed by Göppert-Mayer
in 19313 and observed experimentally in 1960
4
following the invention of the laser. Potential
applications were subsequently demonstrated in
fields such as photonic crystals,1,2,27
optoelectronics,5
biology,8 micromachines
6 and MEMS.
7
TPP may enable advances similar to those
provided by the use of lithography in the fabrication of planar semiconductor devices.
Considerable research has used this principle to develop new patented applications. However,
TPP techniques have yet to be systematically
subjected to analysis to anticipate emerging technologies or applications, or to identify potential
competitors in domain-specific technologies.
This calls for a systematic patent analysis of targeting this technology domain.
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Patent Analysis
A patent is a country- or region-specific exclusive
right to a product or a process that generally provides a new way of doing something, or offers a new
technical solution to a problem (WIPO 2015).
Such patent protection is granted for a limited period. The application entails the disclosure of information
which is critical for subsequent technological
development (WIPO 2015). Patent statistics have frequently been analyzed to serve as both technological
and economic indicators (Grilliches 1990).12
R&D teams are under pressure to accommodate
shortened product life cycles and constantly changing market demands.
13 Granstrand (1999) suggested that
successful patent analysis can reduce R&D costs and
help firms improve market share.14
R&D engineers and business strategists rely on patent analysis to
understand technological development and future
trends.15
Patent analysis is critical for optimizing strategic enterprise planning, mergers and acquisitions,
licensing opportunities, R&D, and human resources.16
In terms of technology analysis for strategic innovation management, patent analysis promotes effective
management of proprietary technologies and optimizes
product development and research processes. Such analysis allows firms to accurately evaluate the
competitive landscape, predict future trends, and plan
counter measures against competing firms.17
Patent has become a core value of corporate assets lead to patent
analysis which plays an important role in the effective
operation of the enterprise.18,19
According to Hong (2009), patent analysis incorporates quantitative and qualitative components.
20
Qualitative analysis focuses on patent content extracted
using text mining techniques.13
Quantitative analysis focuses on metadata extracted from bibliographical
information (e.g. inventors, assignees, filing dates,
issue dates, citations) using statistical processing techniques.
13,20 Most previous studies on patent
analysis have relied on text mining and visualization
techniques to analyze patent content.21
Text mining uses analytical tools to derive
machine-readable data from texts written in natural language by identifying significant patterns.
23,24 Term
frequency-inverse document frequency (TF-IDF)
derives the importance of individual terms based on how frequently it occurs within a text.
22 Juan Ramos
25
applied TF-IDF to determine word relevance
in document queries. Tseng et al.23
developed text mining techniques specifically for patent analysis,
including text segmentation, summary extraction,
feature selection, term association, cluster generation,
topic identification and information mapping. Alternatively, visualization-based approaches visually
represent patent information and result analysis.
For instance, patent maps or clustering provide convenient insight into technological trends in a given
domain21
. Kim et al.19
proposed a visualization
approach to create clusters of related patents.
Cluster Analysis
Clustering creates groups of data into unsupervised
classification based on similar internal features or characteristics.
13 A variety of clustering
methodologies have been devised, and the method
used should be suited to the particular data set to be clustered. Clustering results are then
interpreted by domain experts. Clustering seeks to
maximize similarity of objects within a cluster while maximizing distinction between clusters.
13
For patent analysis, researchers must analyze large
amounts of patent information and produce accurate interpretations. K-means clustering is one of the
most popular clustering algorithms. Kim et al.19
proposed a visualization approach to cluster patent documents with keywords using K-mean algorithm.
However, K-means clustering suffers from some
drawbacks13,21,22
. In addition, the method entails a high degree of computational complexity, particularly
for large data sets. Furthermore, the accuracy of
the resulting clusters is questionable because the method randomly selects the initial centroids.
26
Methodology
This paper uses a domain-specific patent analysis technique. An overview of the methodology
and the research framework is shown in Fig. 2.
The proposed novel approach to patent-claim based technology analysis seeks to enhance strategic
innovation planning.
This study analyses TPP-related patents filed in the U.S., based on a search of the Thomson Innovation
(TI) commercial patent database. The patent
search strategy and process are illustrated in Fig. 3. The individual steps are described briefly in the
following section.
Targeting a concerned field of technology and determining data coverage. The proposed approach
targets a specific technology domain. This requires
the clear definition of the subject for patent analysis. Test data were extracted from the Thomson
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Fig. 2 − Overview of the methodology and the research framework
Fig. 3 −Flowchart of patent search strategy
Innovation (TI) database from 1836 to March of
2015 for U.S. patent applications related to TPP
technology.
Collecting Keywords Preliminary keywords are sourced from domain
experts or are extracted from highly-related patent
documents. These are then used to develop a preliminary search query to search patent documents
and form a preliminary patent pool.
Screening Related-Patent Preliminary screening is needed to determine
which patents in the preliminary patent pool fall
within the specified technology domain. The efficacy of such screening is dependent on the specificity of
patent-related definitions.
Renewing Patent Search Queries to Form an
Optimal Patent Pool The relevance screening process should employ an
exhaustive list of keyword synonyms for the related
patents, along with the patent classification number (e.g., IPC or UPC). Searches can be iterative with
continually updated search strategies and criteria.
Several iterations should produce a final optimal patent pool composed of relevant patent documents.
Patent Clustering According to Claim Analysis
The resulting optimal patent pool was composed of
402 patent documents, including patent applications and grants. These documents were then used to
produce a patent management map using the
Intellectual Property Defense-based Support System (IPDSS) software to generate visualization graphs for
analysis of application trends over time, assignee
activity, and assignees’ countries of origin, inventors, citations, and the distribution of various patent
classification numbers. A technology analysis was
conducted by interpreting claims for patents within the optimal patent pool. In other words, our
method is a claim-based technology analysis for
strategic innovation management. Fig. 4 illustrate the
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Fig. 4 − Patent cluster process derived from the core step of the overall patent analysis process
technology cluster procedure, which corresponds to
the core step of our overall patent analysis process. The left figure of Fig. 4 shows that the patent analysis
process and claim-based patent clustering is a core
step in the overall procedure. The right figure presents a detailed description of the patent cluster. First,
each element was annotated in each independent
claim. This helped in understanding what elements constitute the claimed invention. Preferably, if the
patent specification includes more than one claim,
then each independent claim should be reviewed. Then identification of patentable features among the
various elements was done in each independent
claim. Only a few patents use file wrappers to further identify patentable features. Patent classification
codes such as IPC and UPC may also be used as a
reference. For simplicity, the patentable features with a single sentence were highlighted. Finally, these
simplified feature descriptions are compared to define
a patent cluster based on similar patentable features. The resulting clusters are then named and defined.
Cluster results are used to build technology clusters
in a fish-bone figure. The ontological schema for the corresponding domain-specific technology and
technology function matrix are described in the
following section.
Forecasting Technology Trends
Forecasting of technology domain trends can identify potential applications for a specific
technology cluster or sub-clusters. Patent technology
maps show development trends in specific technology domains, allowing firms to monitor potential
competitors, making them an indispensable resource
for effective enterprise management. The key patentee may either be a top assignee or potential competitor,
and the patent maps shows at glance areas in which
these companies are active and inactive.
R&D Strategy and Market Opportunities
Using patent-claim based technology analysis and the proposed patent analysis method, patent maps of
specific technologies can be generated to provide
a comprehensive understanding of a technical field, recent technology distribution trends, and the
various phases of technological development for
technological subfields. This allows managers to predict future patent deployments or R&D trends.
It also allows for the monitoring of patent
deployments of major manufacturers, providing insight into development trends among a firm’s
competitors, thus allowing for the strategic allocation
of R&D resources. As shown in Fig. 5, this study
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Fig. 5 − Architecture Diagram for Patent Analysis Objectives
seeks to help technical R&D teams devise R&D
strategies for precise patent deployment to help firms
identify and take advantage of market opportunities.
Case Demonstration of the Methodology
This section presents a case study of TPP-related U.S. patents to demonstrate the comprehensive
capabilities and practical contributions of our
proposed methodology. The case study can be divided into four parts. Part one describes the TPP-based
technique as a case of patent analysis in a domain-
specific technology. The second part describes the strategic patent search process and the formation of an
optimal pool composed of 402 U.S. patents (including
patent applications and grants). The third and fourth parts use the real case as an example to deal with
patent management mapping and patent technology
mapping. The fourth part describes the application of patent clustering principles.
TPP-Based Technique TPP-based direct laser writing is a novel technique
tightly focuses near-infrared femtosecond laser
pulses on photosensitive materials through high-magnification lens producing two-photon absorption,
thereby causing the polymerization of photosensitive materials. The two-photon absorption effect is
limited to the light focal point, and the pulse width
of the femtosecond laser is very short, with duration of only a few picoseconds to nanoseconds
and thus a limited cumulative heat effect. This allows
for the production of structures at the sub-micron scale. Using a precise three dimensional platform,
the position of the focal plane can be controlled to
fabricate three dimensional structures of any shape at the sub-micron level. Figure 6 shows a schematic
diagram for the direct laser writing technique
Fig. 6 − Under two-photon excitation, the effective excitation is generated at the focal point of the beam cross-section
based on two-photon polymerization. The effective
excitation will be generated at the focal point of the beam cross-section only
Result of TPP Patent Search The proposed patent analysis method focuses on
TPP technologies. Key phrases for patent searches
are collected and shown in Table 1 and Table 2. These phrases are searched across patent names,
abstracts and claims from the collected patent
applications and grants. Strategically unifying the search results for both set of key phrases
(Tables 1 and 2) generates an initial patent pool
of 449 TPP patents. Subsequent filtering produces an optimal pool of 402 TPP patents.
Visualization of Patent Analytical Map
The optimal patent pool was statistically analyzed using the IPDSS patent management system,
providing enterprises or R&D teams with visualized
graphical representations of useful patent information. Patent management analysis generates a patent
management map, provides additional information
regarding patent numbers, nation of origin, potential competitors, citation ratios and patent classification
codes (e.g., IPC and UPC). The resulting maps
present competition trends, market participation, and human resource engagement.
Figures 1 and 7, respectively, present patent trends
for TPP-based technology patent applications drawn in application year and earliest priority year. Overall
trends are still positive, indicating that the technology
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Table 1 − First set of key phrases for patent search
First set of key phrase Synonyms Interpreation
Two-photon Two-photon*
Twophoton*
2-photon*
Two photon*
Multi-photon*
Multiphoton*
Multi photon*
Two-Photon Photopolymeriz*
Two-Photon Photoinitiated Polymerization
Two-photon induced photopolymerization
Two-Photon polymeriz*
Two-Photon Fluorescence-Induced Photopolymerization
Two-Photon Absor* (TPA)
Two-Photon Excit*
Two-photon laser
Two-Photon Materials
Two-Photon Lithograph*
Two-photon 3D lithography
Two-Photon Process*
Two-photon fabrication
Two-Photon Micro-Nanofabrication
Two-photon exposure
Two-photon radiation
Two–photon irradiation
3D Three dimension*
3D
3 D
3-D
Stereoscopic
Femtosecond laser* Femtosecond laser* The term of femto means ultra fast, it denotes 10−15second.
Table 2 − Second set of key phrases for patent search
Second set of key phrase Synonyms Interpreation
Photon exposure photon exposure
photon radiation
photon irradiation
photon absor*
photon polymeriz*
Generic term of two photon polymerization
Focused laser beam Focus* or focal
Locally/spatially/localize*
Laser/(electromagnetic radiation/electro-magnetic radiation) or (near-IR or near-infrared)
Resist or photoresist or resin or photosensitive substance
Lens
Laser writ*/writ* laser or laser beam writ*
The beam of the laser was focused into the resin with an object lens
Curing/cured Cur*
Solidif*
The resin was cured by the irradiation of focused laser beam
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Fig. 7 − TPP patent application trends (by earliest priority year)
is being applied in a wider range of fields. The
differences between the two charts indicate that an
increasing number of patentees would use U.S. continuing applications to take advantage of the
priority date. Table 3 shows analysis results for the activity of
major TPP patentees related to TPP technology, in
which, Fujifilm Corporation (JP) and 3M Innovative Properties Company (US) are seen to have
significantly expanded their patent holdings, but
using different patent filing strategies. 3M makes good use of provisional applications (PA) and
continuation applications. 3M also uses the
international application mechanism of the Patent Cooperation Treaty (PCT), employing flexible and
aggressive strategies in its patent applications and
investing considerably greater R&D resources than Fujifilm. Fig. 8 shows 3M’s US patent application
strategy. Tables 4 and 5 respectively show statistics
for the top 5 IPCs and UPCs based on TPP-related technologies, with classifications defined in the last
column of each table.
Technology Trend Analysis Patent technology maps are used to analyze
patented technologies by category, thereby
developing a technology language more comprehensible to R&D professionals, along with
various hierarchical technology classes. The most
difficult analysis problem for patented technology
Table 3 − Statistics of major TPP patentees related to
TPP technology
Assignees Patent counts
Inventor counts
Patent age
Fujifilm Corporation (Tokyo, JP) 18 20 8.5
3M Innovative Properties Company (Saint Paul, MN)
13 54 9.25
The Regents of the University of California
10 29 15.6
Mempile Inc. (Wilmington, DE) 9 12 9.44
Panasonic Corporation
(Matsushita Electric, Osaka, JP)
7 13 10.14
Massachusetts Institute of
Technology (Cambridge, MA)
6 31 6
Samsung Electronics Co., Ltd. (KR) 6 27 6.83
Carl Zeiss 4 10 14.75
Cornell Research Foundation, Inc. (Ithaca, NY)
4 10 22.5
diagrams involves maximizing the efficiency and
precision of categorization to provide decision makers with reliable insight into market trends.
The proposed methodology performs technology
clustering on 402 selected patents through claim construction. In this process, tedious claim-related
syntax is deciphered and every element of
each independent claim is systemically decomposed. This not only efficiently identifies patentable
features, but also highlights these features in a single
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Fig. 8− 3M’s US patent application strategy
Table 4 − Statistics for the top 5 TPP-based IPCs
IPC Patent counts
Context
G02B21/00 14 Microscopes
G01N21/64 11 Systems in which the material
investigated is optically excited by fluorescence or phosphorescence
G11B7/24 11 Record carriers characterized by shape,
structure or physical properties, or characterized by the selection of the material
G11B7/00 9 Recording or reproducing by optical
means, e.g., recording using a thermal beam of optical radiation, reproducing using an optical beam at lower power
G06K9/00 8 Methods or arrangements for reading or
recognizing printed or written characters or for recognizing patterns
Table 5− Statistics for the top 5 TPP-based UPCs
UPC Patent
counts
Context
250/458.1 7 A source of radiant energy and a phosphor material which luminescence or which quenches luminescence as a result of excitation of the material by the radiant energy
382/133 7 The image analyzing system designed
specifically for biomedical applications such as cell analysis, classification or counting
359/385 6 Structure for illuminating an object being viewed in combination with a microscope or object illuminating structure designed specifically for use with a microscope
600/476 6 Surgery diagnostic testing including means
for detecting nuclear, electromagnetic, or ultrasonic radiation wherein the electromagnetic energy is in the range detectable by the human eye
250/459.1 5 Methods which include the irradiation of a phosphor material by a radiant energy source where not elsewhere provided.
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Table 6 − Illustration of claim interpretation based on claim-based technology analysis
Patent No. United States Patent Classification (UPC)
Claim Interpretation and hierarchical technology clustering
US20110046764 700/98 (3-D product design,
e.g., solid modeling)
1. A process of manufacturing a 3D mold to fabricate a high-throughput and low cost sub-micron 3D
structure product, said process integrating 2-photon lithography and nano-imprinting, comprising : using 2-photon laser lithography and 3D write technology to make a 3D mold of each layer of the 3D structure product, using nano-imprinting to form a sheet of polymer film of each layer of the 3D structure from said 3D mold of that layer, and fabricating each layer to make the sub-micron 3D structure product.
11. The 3D mold of a layer of the sub-micron 3D structure product as claimed in…………………..………..., layer by layer to form the seed metal layer and
removing the wafer from the chamber.
Modeling denotes a micro fabrication for producing 3D structure product.
Then, 3D printing is defined as a method for the layer-by-layer fabrication of 3D micro-nanostructure product, and is referred to as an additive manufacture. Accordingly, the hierarchical technology clustering like:
•Modeling
••3D Print
•••Process
••••Integrate TPP and nano-imprint
descriptive sentence, thus facilitating precise and efficiency categorization. By contrast, traditional
clustering uses a K-means algorithm, which is fast
but imprecise. An illustration of using claim interpretation to perform hierarchical technology
classes based on our claim-based technology
analysis is shown in Table 6. Table 6 shows evidence that the logical hierarchical technology
classes are similar to the description of United States
Patent Classification (UPC). For example, 700/98 is a major UPC of US 20110046764 and the
hierarchical description of that is relating to a special
process of using solid modeling micro fabrication to produce 3D product design. This is similar to
our hierarchical technology classes based on our
claim-based technology analysis, which is logical defined with hierarchy by a process of integrating
TPP and nano-imprint and an adoption of 3D print
with layer-by-layer fabrication to perform a modeling micro fabrication and finally achieve a
3D structure product. Hence, the patentable features
cited in the claim of the patent application must be identified, requiring precise categorization based
on the aforementioned clustering principle.
The proposed patent analysis method seeks to address this need.
Clustering the related patents and presenting the
results in graphical representations produces a patent technology map. For example, Fig.9 shows a fish-
bone diagram for TPP technology clustering,
hierarchically organizing the patent clusters. The technologies are divided into six clusters: image
system, modeling, optical device, material, photonic
crystal and biotechnology. As shown in Table 3, the two key patent holders for TPP technology are the
Fujifilm Corporation and 3M. Fujifilm has the largest
overall number of patents, but these are nearly all focused in the optical device cluster and pertain to
optical data storage media. In contrast, 3M’s patent
distribution is relatively broad, using core technology principles to produce diverse and innovative
applications. Figure 10 shows 3M’s patent clusters
based on TPP technology, with the majority in the photo-reactive composition group, with most of these
focusing on optical/physical/chemical characteristic
controls of reactive species, including controls on glass transition temperature (Tg), solubility, hydro-
phobicity, refractive index, mixture compositions,
chemical compositions, particle sizes. These are used to produce stable, accurate and high-resolution
three dimensional optically functional elements. In
addition, 3M possesses patents for imaging systems, photonic crystal with periodic dielectric structures,
processes for making micro-lens arrays for the
production of aspherical micro-lenses, and processes for making light guides with three-dimensional light
extraction structures. Through filing continuation
applications, 3M can likely expand and enrich its patent network. Figure 11 shows a TPP ontology
scheme correlating each of the clustered technologies.
Mapping the correlations of the clusters in the TPP ontology schema illustrates how different
technologies clustered on each other and how new
technology emerge. This ontology schema thus shows the structure of the entire patent landscape associated
with these various technologies. For example, patents
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Fig. 9 − Overall technological landscape based on TPP Fish-bone diagram
Fig. 10 − 3M’s patent clusters based on TPP technology
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Fig. 11− TPP ontology schema
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in Cluster1 are related to image systems whereas those in Cluster 6 are related to biotechnology.
This is a somewhat artificial distinction and strong
links exist between various subclasses in these two clusters. This reveals that different technology
clusters relate to one another, sometimes in
unexpected ways, and how new technologies emerge. As shown in Fig. 12, representative patents
and patentees were chosen from the clustered
patents based on the aforementioned patent clustering principle to emphasize important patents and
major (potential) competitors. This information
allows enterprises and R&D teams to better understand and monitor follow-up patent
development, including claim amendments during
the examination process, possible prior art, licensing trends, patent validity and legal status.
The technology-function matrix follows the
patent clustering principle in categorizing the relevant patents according to function. Therefore,
TPP technologies are individually clustered according
to their associated functions as shown in Fig. 13. Technology categorization must be conducted at
the sub-class level, after which calculation of the
number of patents in each technology sub-cluster was done and then in each functional cluster.
Table 7 shows the TPP technology-function matrix.
Patent analysis seeks to anticipate future market developments from the viewpoint of patents,
especially from recent patent applications. Such
information provides insight into the R&D directions of the major international manufacturers or potential
competitors, and can thus provide firms with a
significant competitive advantage. For example, TPP-based 3D printing falls into a sub-category
of the Modeling cluster which is the second cluster
based on fish-bone clustering. It is defined as a method for the layer-by-layer fabrication of
3D micro-nanostructures based on two photon/multi-
photon polymerization technology, and is referred to as an additive manufacture based on TPP technology.
The technology classification is further divided
into structure, method, material and applications for micro optics, biotechnology and scaffolds used for
tissue engineering. The Modeling cluster is isolated
from the overall classification framework and the corresponding representative patent numbers are as
shown in Fig. 14. Analysis based on the time of patent
application shows that the patent sub-cluster is composed of applications filed in recent years.
Figure15 indicates that the 3D printing sub-category
based on TPP technology has emerged in recent years, which encourage further development to secure new
market opportunities. This also serves as a powerful
Fig. 12 − Representative patents and patentees from the proposed clustering method
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Fig. 13 − TPP technology-function clustering
Table 7 − TPP technology-function matrix
T1-Image system
T2- Modeling
T3-Optical device
T4-Material T5-Photonic crystal
T6-Biotechnology Tech/
Function
T1-1
Micros-
copy
T1-2 Apparatus
T2-1
3D
print
T2-2
Single
step
T3-1
Micro-
lens arrays
T3-2
Optical
data storage
T3-3
Light
guides
T4-1
Reactive
species
T4-2
Multi-
photon
photo initiator
T4-3
Inorganic
particles
T5-1 Structure
T5-2 Method
T6-1 Diagnosis
T6-2
Bio-
imaging technique
T6-3
Biological
tissue
F1
Stability 16 9 1 6 4 5 2 5 3 5 0 1 0 3 4
F2
High spatial
resolut-ion 28 11 1 9 5 8 3 1 1 2 1 1 2 3 5
F3
Simplified
process 1 2 1 4 2 4 4 4 4 2 0 2 1 0 0
F4
Reduce
writing time 2 1 1 5 3 5 2 5 2 1 2 1 1 2 1
F5
Machining
accuracy 23 6 2 6 5 6 3 0 1 3 3 0 0 1 2
F6
High energy
density 14 2 0 4 2 3 1 2 3 4 2 1 2 3 2
F7
Low cost 4 2 1 0 1 2 0 6 10 6 1 0 1 0 0
F8
Enhancing
image
contrast
9 6 0 1 1 0 1 5 1 3 0 0 2 7 6
indicator for predicting the future development of
technological applications. Major competitors in this technology sub-cluster include Nanoscribe
(Germany), Helios Applied Systems (Singapore),
and A*STAR (Singapore). Nanoscribe specializes in equipment and positioning, while Helios has
developed a process integrating two-photon
lithography and nano-transfer printing for the production of a sub-micron 3D structural product,
and A*STAR has developed a 3D biological
compatible structure which can be used for tissue engineering and organ transplant.
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Fig. 14 − Classification framework for the second cluster (modeling) and corresponding patent numbers
Fig. 15 − Patent application trend related to the TPP-based 3D printing sub-cluster
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Conclusion
The creation of three-dimensional micro
nanostructures through the TPP technique is used as an example to develop a claim-based clustering
method to address problems raised by the
traditional K-means clustering algorithm including a lack of precision in clustering during patent
technology analysis. Experimental results point to
the following important findings, which can provide reference for strategic innovation management
decision-making. First, fundamental TPP-related
patents with a broad scope of claims have already been secured and the possibility of infringement
will be anticipated (e.g., the application of TPP
to microscopy). However, following more than two decades of development, some TPP-related
technologies have lost patent protection, and
subsequent applications, including 3D structural products, processes, imaging systems, apparatus or
materials, are not fundamental patents.
Second, in recent years, TPP patenting trend is
gearing towards the innovative applications derived from existing technologies, e.g., using an infrared
laser device (US20140378954) for closing bleeding
wound of humans or animals by means of TPP, or using TPP technique as one step of method
for detecting protein crystallization (US8946655).
For the subject matter of patent examination, in addition to objects and methods, there is new use,
which can produce unpredictable effect. Third, this
study indicates that Fujifilm and 3M are the two key players in TPP-based technology, based on their
respective patent holdings. However, these firms
have followed strikingly different patent deployment strategies. Fujifilm’s patents mostly focus on
optical data storage media, but 3M company’s patents
are more widely distributed and the firm has used existing technologies to develop multiple
innovative applications. For example, photo-curable compositions characterized by physical/ chemical/
optical properties are used to produce stable,
accurate and high-resolution three-dimensional optical functional elements, photonic crystals with
periodic dielectric structures, as spherical micro-
lenses, and light guides with three-dimensional light extraction structures. Through filing US continuation
applications, the company can likely expand and
enrich its patent network.
Fourth, the TPP-based 3D printing related patents match exactly the trend of gearing towards
the innovative applications derived from the existing
technology, which, nonetheless, requires further
development for securing the market opportunities. Major players, currently in this space, including
Nanoscribe, Helios Applied Systems and A*STAR,
and their patents can be valuable as R&D intelligence for potential competitors in the emerging fields.
Furthermore, managers should be alert to the
activities of potential competitors in this emerging field, especially for executives responsible for
decision making related to technology investment.
It can be a valuable intelligence such as the target of license and thus provide firms with a significant
competitive advantage. Accordingly, as a result of this
research’s contributions, the claim-based technology analysis enables to understand the landscape of
emerging technologies and forecast its trend in
the future.
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