Method of Claim-Based Technology Analysis for Strategic...

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]

J INTELLEC PROP RIGHTS, JULY 2016

244

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.

JUI et al.: METHOD OF CLAIM-BASED TECHNOLOGY ANALYSIS FOR STRATEGIC INNOVATION MANAGEMENT

245

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


246

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


247

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


248

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


249

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


250

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


251

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.


252

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


253

Fig. 9 − Overall technological landscape based on TPP Fish-bone diagram

Fig. 10 − 3M’s patent clusters based on TPP technology


254

Fig. 11− TPP ontology schema


255

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


256

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.


257

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


258

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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