Increasing the Amount of Knowledge Reuse from Engineering Design

Repositories

A Research on the Needs and Behaviours of Novice Designers

Cristina Carro Saavedra and Udo Lindemann

Institute of Product Development, Technische Universität München, Boltzmannstraße 15, Garching, Germany

1 RESEARCH PROBLEM

Engineering design is a knowledge-intensive

activity, in which designers are constantly learning.

The knowledge gained with each new design can be

reused in future designs in order to avoid past

mistakes and do not reinvent the wheel.

Companies make efforts acquiring and storing

their knowledge, but this knowledge is often not

reused. 80% of the companies that participated in a

survey conducted by (Milton 2010) attempted to

collect lessons learned, but more than half did not

reuse them efficiently. (Ichijo and Nonaka 2007)

also remarked that “despite the growing interest in

knowledge management and the initiatives many

organizations have taken to manage knowledge, few

companies have succeeded in creating a knowledge-

based competence to gain and sustain a competitive

advantage”. Reality is that companies still fail

transforming knowledge into actions. Either they do

not apply the methods for knowledge reuse or they

do not succeed applying them. Therefore, the

question is what is hampering companies in the

successful reuse of the knowledge gained during

engineering design?

Numerous studies have been done to identify

barriers for knowledge reuse (Chirumalla 2013,

Ranjbarfard et al. 2014). Several approaches for

knowledge reuse have been also developed. A

shortcoming of the existing approaches for

knowledge reuse knowledge reuse is that they do not

deepen enough in the barriers existing at the level of

designers. Individuals are in the end the ones that

decide if they reuse or not. (Markus 2001) stated that

“each type of knowledge reuser has different needs

from repositories” and can experience different

problems to reuse knowledge. More understanding

of designers’ needs and behaviours while reusing

knowledge from company’s repositories is required.

The reuse of company-specific knowledge supports

especially novice designers that are not familiarized

with specific aspects of the company. Since novices

are the main target group for knowledge reuse

(Ahmed et al. 2000), they represent the focus of the

research.

Early-phases of design are especially challenging

for knowledge reuse due to the ill-defined status of

the design problems. (Baxter et al. 2007) remarks

that most methods for knowledge reuse are focused

on detailed design and it should be given more

attention to knowledge reuse in early design phases.

2 OUTLINE OF OBJECTIVES

The objective of the research is to increase the

amount of knowledge reused from companies’

repositories during early-phases of engineering

design. In order to achieve this aim, the research is

focused on understanding the needs and behaviours

of novice designers while reusing knowledge. The

understanding sets the basis for the development of

support to increase the knowledge reuse.

Subsequently, the research challenges (RC),

assumptions (A) and hypothesis (H) that motivate

the research are presented. The research questions

(RQ) derived from them are also introduced.

A 1: An understanding of the individual influent

factors for novice designers to reuse knowledge

from repositories is missing.

RQ 1: Which are the influent factors for novice

designers to reuse knowledge from the repositories

during early-phases of engineering design?

H 2: The identification of reuse situations during the

early-phases of the design process is the trigger for

knowledge reuse. Authors like (Wallace et al. 2005,

Baxter et al. 2007) remark the need of process-based

approaches for knowledge reuse.

RQ 2: Which are the situations of knowledge reuse

during early-phases of engineering design? How can

they be characterized?

Saavedra, C. and Lindemann, U..

Increasing the Amount of Knowledge Reuse from Engineering Design Repositories - A Research on the Needs and Behaviours of Novice Designers.

In Doctoral Consortium (DC3K 2015), pages 21-30

RC 3: Large amount of knowledge overwhelm

designers, resulting on a negative attitude towards

future knowledge reuse.

RQ 3: What is the relevant knowledge for designers

in each reuse situation?

RC 4: Lack of successful support for knowledge

reuse. Authors like (Ichijo and Nonaka 2007) and

(Milton 2010) highlighted the need.

RQ 4: How can novice designers be supported to

reuse the relevant knowledge in the identified reuse

situations?

The research is structured according to the stages

proposed by (Blessing and Chakrabarti 2009) in

their book Design Research Methodology (DRM).

The framework of the DRM is depicted in Figure 1.

A comprehensive Descriptive Study I is being

conducted in order to address RQ 1, RQ 2 and RQ 3.

The understanding builds the basis to answer RQ 4

during the Prescriptive Study. The support will be

evaluated during an initial Descriptive Study II.

Figure 1: Framework of the research methodology.

(Blessing and Chakrabarti 2009).

3 STATE OF THE ART

3.1 Knowledge Management

Knowledge management (KM) refers to the ability

of companies in leveraging and applying individual

and collective knowledge to help them compete (von

Krogh 1998, Alavi and Leidner 2001).

Consequently, “KM plays a critical role in

efficiency, competitiveness, and productivity of

organizations” (Manohar Singh and Gupta 2014).

3.1.1 Activities in Knowledge Management

The main activities of KM were defined by (Probst

et al. 1998). They are related to each other since they

are part of the process of KM (see Figure 2).

Figure 2: Activities of Knowledge Management (Probst et

al. 1998).

According to (McMahon et al. 2004), the

activities can be conducted with two focuses: 1)

emphasize human resources and communication

(personalization approach); or 2) promote collection

and organization of documented knowledge

(codification approach).

3.1.2 Types of Knowledge

Defining knowledge is a difficult task. The term has

received different definitions but any of them has

been established. However, the understanding of

most authors can be summarized in seeing

knowledge as information combined with

experience, interpretation and reflection (Nonaka

1994, Davenport et al. 1998, Zack 1999b, De Long

and Fahey 2000, Alavi and Leidner 2001).

A common resource in literature to succeed

defining such an abstract term is to classify the types

of knowledge. Numerous ways of classifying

knowledge have been proposed.

(Polanyi 1962, 1966) introduced the two

dimensions of human knowledge, the tacit and the

explicit. He described tacit knowledge as “non-

codified and non-verbalized knowledge that resides

in individual’s heads”. “Explicit knowledge is

encodable and transferable in formal language”.

(Zack 1999b) classified knowledge into general

and specific. “General knowledge is broad, often

public available and independent of particular

events”. “Specific knowledge is context-specific.”

(Alavi and Leidner 2001) and (Zack 1999a) also

classified knowledge depending on its content as

declarative (know-about), procedural (know-how),

causal (know-why), conditional (know-when), and

relational (know-with).

Some other classifications of knowledge are

depending on the origin (internal or external) or the

strategic value (core, advanced, innovative).

Knowledge

identification

Knowledge

goals

Knowledge

acquisition

Knowledge

development

Knowledge

distribution

Knowledge

usage

Knowledge

protection

Knowledge

evaluation

Feedback

DC3K 2015 - Doctoral Consortium on Knowledge Discovery, Knowledge Engineering and Knowledge Management

3.1.3 The Development of the Discipline

Coming from the field of strategic management, the

article of (Nonaka 1991) The Knowledge-Creating

Company represents a milestone in the development

of KM as a formal discipline.

Since then, numerous theorists and practitioners

have built on the discipline (Nonaka 1994, Grant

1996a, Grant 1996b, Davenport et al. 1998, Zack

1999a, Zack 1999b, Zack 2003, De Long and Fahey

2000). However, the successful implementation of

KM is not an easy task. “Despite the growing

interest in knowledge management and the

initiatives many organizations have taken to manage

knowledge, few companies have succeeded in

creating a knowledge-based competence to gain and

sustain a competitive advantage” (Ichijo and Nonaka

2007). This failure made questioning the

effectiveness of KM. (Zack et al. 2009) conducted

an empirical study to analyse the organizational

impact of KM. They claim that KM practices are

directly related to organizational performance and

thus, they built the foundation to continue

researching on the topic.

3.2 Knowledge Management in

Engineering Design

KM is especially relevant to support knowledge-

intensive activities like engineering design. Every

design project is different, so engineers must come

up every time with new solutions and ideas during

their work. Past knowledge can support the

development of solutions to new design problems

(Duffy et al. 1995). The codification approach of

KM provides a systematic support during the design

process. The knowledge is stored in repositories,

also called organizational memory systems (Markus

2001). The challenge is to make the maximum use

of the available knowledge by delivering it “in the

appropriate form at the right time” of the design

process (Blessing and Wallace 2000).

This particular case of supporting knowledge-

intensive activities using codified knowledge from

repositories receives in literature the name of

knowledge reuse (Markus 2001).

3.2.1 Knowledge Reuse from Repositories

(Markus 2001) built the foundations of a theory for

knowledge reusability. She defined basic concepts of

knowledge reuse and identified four types of

situations in which knowledge is reused.

The reuse process consists according to (Markus

2001) of four phases: capturing and documenting

knowledge; packaging knowledge for reuse;

distributing knowledge; and reusing knowledge. She

detailed further the last phase (reusing knowledge)

in four steps, presented in Figure 3.

Figure 3: The Knowledge Reuse Cycle and the four steps

of the reusing phase. (Adapted from Markus 2001).

(Markus 2001) determined the roles which

participate in the knowledge reuse process: the

knowledge producer; the knowledge intermediary;

and the knowledge consumer. She identified four

types of situations in which knowledge is reused

depending of the roles of the actors involved in the

reuse situation:

 Shared Work Producers: people working

together (homogeneous or cross-functional).

Producers of knowledge for their own later

reuse.

 Shared Work Practitioners: people doing

similar work in different settings. Producers

of knowledge for each other’s use.

 Expertise-Seeking Novices: people with an

occasional need for expert knowledge that

they do not possess.

 Secondary Knowledge Miners: people who

seek to develop new knowledge through

analysis of records produced by other people

for different purposes.

After presenting the framework, she concludes

that the type of repository and the associated KM

processes must be designed differently depending on

the reuse situation. “Successful knowledge reuse is a

matter of designing repositories that meet reusers’

needs” (Markus 2001).

Increasing the Amount of Knowledge Reuse from Engineering Design Repositories - A Research on the Needs and Behaviours of Novice

Designers

3.2.2 Types of Knowledge in Engineering

Design

The term design knowledge often refers to

knowledge about products’ geometry, that is

embedded in CAD models and it can be reused using

knowledge-based engineering (KBE) tools. This

knowledge can be abstracted in form of structural,

functional or behavioural models, so it can be reused

for any design situation or any physical structure.

Generic relations among abstract design elements

based on these models are the so called design

patterns (Bhatta and Goel 2002).

However, there is more knowledge that can be

reused in engineering design, like project-constrain

reasoning, problem resolution methods, solution

generation strategies, design intent, and supply chain

knowledge (Baxter et al. 2007). In fact, knowledge

in engineering design can be classified using the

types of knowledge described in section 3.1.2. Inside

each type the categories can be further concretized

for specific fields.

Some authors derived specific categories of

knowledge reused in engineering design conducting

empirical observations. (Cross and Sivaloganathan

2007) conducted their study within a mobile

elevating work platform manufacturer. They

determined the following categories of knowledge:

 Country- and market-specific requirements

 Experience, best-practice, tips and tricks

 Product-specific parameters

 Interactions, trade-offs, and design rules

 Knowledge contacts

 Legislation and approval bodies

 Manufacturing process capability and

available materials

 Preferred parts and installation

requirements

 Stakeholder behaviour

 Stakeholder requirements

(Gainsburg et al. 2010) propose also a classification

based on observations in structural engineering

companies.

3.2.3 Approaches for Knowledge Reuse in

Engineering Design

(Duffy et al. 1995) present a design reuse model

consisting of three processes and six knowledge-

related components. The goal of the model is

formalising design reuse in order to provide the

appropriate scope to be supported. The work is

theoretical and no evaluation is presented.

(Blessing and Wallace 2000) developed

PROSUS, a system to support knowledge reuse

during the design process focused in knowledge

generation. They identified the generation of

knowledge as the consequence of using knowledge.

Therefore, the core of the system is a working area

for the designer, in which the relevant knowledge

during design is generated and stored. They also

highlight that the whole knowledge reuse cycle (they

refer to it as knowledge-life cycle) must be taken

into account when developing knowledge-based

support for design. PROSUS does not explicitly

address the knowledge-life cycle but it sets the basis

to support the entire cycle through the indication of

context, which is the basis for understanding.

(Fruchter and Demian 2002) developed a

prototype knowledge management system, CoMem,

to support the activities that they identified in the

process of knowledge reuse: finding reusable items

and understanding these items in context. They do

not consider knowledge reuse as the complete

process (from generating to reuse) but only the last

phase according to (Markus 2001), reusing

knowledge. It is not explained who or how should

the system be fulfilled with knowledge to be

sustainable.

(Dani et al. 2006) developed a methodology to

support communication, sharing and reuse of best

practices in product development. The methodology

focuses in capturing, structuring and finding best

practices for new projects. The proposal is project-

focused instead of process-focused. Best practices to

be reused during a new project are identified at the

beginning of a new project and there is no method

suggested for the retrieval of best practices once the

project has started.

(Johansson et al. 2012) propose Matrix-Flow-

Charts (MFC) as an approach to support the reuse of

knowledge from manufacturing processes during

design. Their work is conducted within the field of

laser welding technology. Real implementation of

MFC or an evaluation are not conducted.

(Chirumalla 2013) developed a methodology to

reuse lessons learned (LL) in product development.

The LL are captured using templates and videos

with storytelling. The videos contribute to transfer

contextual and tacit knowledge. The integration of

the LL in the development process is not addressed.

3.2.4 The Research Gap

Despite the efforts made in research and the

evidence of the benefits of knowledge reuse, reality

is that companies still fail transforming knowledge

DC3K 2015 - Doctoral Consortium on Knowledge Discovery, Knowledge Engineering and Knowledge Management

into actions. Either they do not apply the methods or

they do not succeed applying them (Ichijo and

Nonaka 2007, Milton 2010). Therefore, the question

is what is hampering companies in the successful

reuse of the knowledge gained during engineering

design?

Numerous studies on the barriers for KM have

been carried out. The studies identify barriers related

to different aspects like people-related barriers,

technology-related barriers, organization-related

barriers, environment-related barriers or knowledge

characteristic-related barriers (Ranjbarfard et al.

2014). These barriers are usually also allocated to

the correspondent activities of KM. However, the

spectrum of barriers is large and the

interdependencies between the activities in KM are

high. Therefore, the understanding of the

implications of barriers on the knowledge processes

and which kind of support can overcome those

remains still incomplete.

(Davenport and Prusak 1998) stated that

“knowledge originates and it is applied in the minds

of knowers”. They point out with this statement that

the decision of applying knowledge depends

ultimately on individuals. Thus, individuals

represent the connecting link between KM initiatives

and firm performance. A better understanding of

individuals’ needs and behaviour when reusing

knowledge is the key to identify the reasons for the

failure in reuse.

Looking at individuals, it can be distinguished

between expert and novice designers. Knowledge

reuse is especially relevant for novice designers,

since it helps to “bridge the gap between novices and

experienced designers” (Ahmed et al. 2000),

contributing to a faster learning curve for novices.

The approaches presented in section 3.2.3. do

not focus on the specific needs of novices or experts.

However, the needs and behaviours of both groups

while reusing knowledge are different. For example,

(Ahmed and Wallace 2004) found that one

differential issue between experts and novices is the

awareness of knowledge needs. Novices were only

aware of their needs in 35% of the cases. They

present a method (C-QuARK) to support novice

designers in the step “defining the search question”

of the reusing stage established by (Markus 2001).

However, the integration of the method in a holistic

approach for knowledge reuse is missing.

We argue that the lack of differentiation of

reusers’ (knowledge consumers) requirements,

aspect that (Markus 2001) identified as of mayor

importance, is the main reason for the low

implementation in industry of approaches for

knowledge reuse and for the failure in case of

implementation. The specific requirements of the

individuals involved in the process are not taken into

account. Furthermore, the requirements of other

stakeholders during the reuse cycle, like knowledge

producers and knowledge intermediaries, must be

also considered for a system addressing the whole

reuse cycle to succeed. Due to the mismatch

between system features and stakeholders’

requirements, reuse systems are finally not properly

used or not used at all, and the knowledge reuse

during the design process does not occur.

Since novice designers are the stakeholders that

can profit the most from an approach for knowledge

reuse, this research proposes to start a deeper

investigation on stakeholders’ requirements by

analysing the requirements for novices and

proposing support for them. Thus, the target support

would be established and further investigations

should consider the integration of the other

stakeholders according to their specific requirements

in such a support.

4 METHODOLOGY

A research methodology based on the DRM of

(Blessing and Chakrabarti 2009) has been designed.

Figure 4: Research methodology.

The Research Clarification (RC) has been done

reviewing literature and non-experimentation with

students in design workshops.

The Descriptive Study I (DS I) constitutes the

largest research effort due to the current lack of

proper understanding on the research topic. There is

the need of obtaining empirical data for the analysis.

Therefore interviews with novices and experienced

designers will be conducted. Also non-experiments

with novices to observe and analyse their behaviour

during knowledge reuse will be conducted.

Increasing the Amount of Knowledge Reuse from Engineering Design Repositories - A Research on the Needs and Behaviours of Novice

Designers

An approach for support will be proposed during

the Prescriptive Study (PS). The reuse situations and

reused knowledge established in the DS I constitute

the framework to develop the support. The support

should help to overcome the harmful influent factors

identified during DS I.

The proposed support will be evaluated during

the Descriptive Study II (DS II) in comparative

design experiments, in which one group of designers

conducts a design development without support and

the other group does it with the support.

4.1 Research Clarification

Several approaches for knowledge reuse have been

proposed in literature. Numerous barriers for

knowledge reuse have been also identified.

However, the reasons for the lack of knowledge

reuse during engineering design are unclear. Setting

the focus of the research was difficult under these

conditions.

Novice designers were identified as the group

with higher potential for support. An approach to

understand better the influent factors that affect them

during knowledge reuse was to simplify the scene:

what if the complex environment of the company

(culture, network, time-pressure, etc.), or the

technological support were out of the picture?

Would in this case knowledge be successfully reused

during the design process? With the purpose of

answering this question, a non-experiment with three

students was realized. A non-experiment is

conducted when the understanding of the research

phenomenon or the available resources are “not

sufficient for permitting strong tests of causal

hypothesis” (Cook and Campbell 1979). Non-

experimentation is done to observe a phenomenon as

it occurs and helps to generate new ideas.

For the non-experiment, the students were

considered as “novice designers” and they were

given a design problem to solve in three hours. They

worked individually and they could ask questions to

the “knowledge repository” during their work. The

knowledge repository contained useful knowledge

for the design problem in form of knowledge pages

previously documented and categorized. For

simplification reasons, the knowledge repository

was a person. The person did not interact orally with

the participants and the communication was in

written form. The person acted as an “intelligent

knowledge retrieval system” providing the

correspondent knowledge page to the question

written by the participant.

The design process was divided in three phases:

idea generation, concept design and detailed design.

The participants should provide their output of each

phase to the moderator. Their requests for

knowledge during the process were documented and

the application of the knowledge contained in the

knowledge pages was analysed regarding the

outcomes of the design phases.

Two main problems were observed: difficulty to

articulate questions and difficulty to interpret the

knowledge that was received and reuse it

successfully. The first problem occurs due to the low

awareness of their knowledge needs. The fact that

the knowledge is available (explicit set up of the

experiment: there is knowledge available for your

specific design problem) did not appear to have a

significant impact. An interesting observation was

that the amount of requests increased as the design

process advances. Therefore, the phase of the design

process influences the amount of knowledge reused.

The request for knowledge is less in early-phases of

design. The second problem occurs due to the lack

of knowledge contextualization. The knowledge of

the knowledge pages was not documented in a way

that it was understandable for the participants how

they could apply it in their situation.

From the non-experiment is concluded that

barriers for knowledge reuse also exist in a

simplified environment. More understanding of the

phenomenon is needed, especially on early design

phases, before support can be developed. A literature

review shows that most methods for knowledge

reuse are focused on detailed design (Baxter et al.

2007) and it should be given more attention to

knowledge reuse in early design phases. Therefore,

the research continues in this direction.

4.2 Descriptive Study I

The DS I attempts to answer RQ 1, RQ 2 and RQ 3.

In order to answer the questions, an approach based

on three methods for data acquisition is proposed:

literature review, interviews and non-

experimentation. An overview of the proposed

methods is depicted in Table 1.

Table 1: Research methods applied during the DS I (√:

contribution; √√: main contribution).

Lit.

review

Interviews

with

novices

Interviews

with

experts

Non-experiments

Novices as participant

Experts as analysts

RQ1

√ √ √√

RQ2

√√ √ √

RQ3

√ √ √√ √

DC3K 2015 - Doctoral Consortium on Knowledge Discovery, Knowledge Engineering and Knowledge Management

Further details and the expected outcomes of each

method are explained in the following sections.

4.2.1 Literature Review

A literature review is being conducted in order to

find types of reuse situations and ways of

characterizing those (RQ 2), and types of knowledge

to be reused (RQ 3). The literature review should

provide the major contribution to answer RQ 2 and

contribute to answer RQ 3. However, not much

information has been found until the moment.

Regarding the identification and characterization

of reuse situations, there is the approach of (Markus

2001) explained in section 3.2.1. Sources proposing

classifications of design situations (considering

those as potential reuse situations) provide also

useful insights. (Sim and Duffy 2003) identified the

generic engineering design activities in three groups:

design definition activities (like abstracting or

detailing), design evaluation activities (like

analysing or modelling), and design management

activities (like planning or prioritizing). (Ponn 2007)

suggests three main categories to classify a design

situation: design task, designer/designer team,

boundary conditions.

Considering the types of knowledge to be reused

(RQ 3), the classifications of (Cross and

Sivaloganathan 2007) or (Gaingsburg 2010)

introduced in section 3.2.2 have been found. Other

authors in the field of engineering design adopt the

categories presented in section 3.1.2 that can be

generalized to other disciplines. These categories

seem too general to support the reuse of specific

company´s knowledge.

4.2.2 Interviews

Gathering empirical data is necessary to answer the

three research questions formulated.

For RQ 1 and RQ 2, interviews with novice and

expert designers are proposed as a method to

verify/extend the data obtained first by other means.

For RQ 3, the outcome from the interviews represent

the main source to obtain data.

In the case of RQ 1, the results from the non-

experiments refer to concrete cases. The interviews

to novice designers are proposed in order to check if

the influent factors identified during the non-

experiments can be generalized. Interviews to expert

designers with the same purpose are proposed.

Experts work with novices and from their

experience, they can also provide valuable insight

about the influent factors for novices.

The literature review to define the reuse

situations (RQ 2) does not seem conclusive. Only

one concrete classification has been found up till

now (Ponn 2007) and its focus differs from the focus

of the research at hand. If no further classifications

are found, an approach for the classification will be

proposed and its validity evaluated by interviewing

novices and experts.

Interviewing novice designers about the

knowledge they reuse and the knowledge they would

like to reuse contributes to answer RQ 3. However,

as it was already explained, novice designers are not

always aware of their knowledge needs. In order to

understand which kind of knowledge is reused, the

experience of expert designers is considered a key

factor. Therefore, the main contribution to RQ 3 are

the interviews with experienced designers.

4.2.3 Non-Experiments

Current literature is not sufficient to identify the key

influent factors. Interviews with novice and expert

designers may contribute but the factors are difficult

to be elicited in interviews. A more realistic

approach to identify influent factors is direct

observation of the process of knowledge reuse. Non-

experiments in form of design workshops are

proposed. (Blessing and Chakrabarti 2009) point out

that due to the lack of understanding in design

“design research usually involves non-experimental

and quasi-experimental research, in particular for

DS-I”. During the non-experiment, novice designers

must reuse knowledge, and expert designers support

the researches with the analysis of the results.

The non-experiments will be conducted similarly

to the one realized during the RC but focused on

early phases of design. The intention this time is to

conduct them with real knowledge in collaboration

with a development company that brings up a

realistic design problem. The knowledge repository

will be fulfilled with knowledge provided by the

company. The participants will be novice designers

from the company. Experienced designers from the

same company will support the researcher to analyse

the results. The effects of the non-use of available

knowledge or of the wrong use will be analysed. The

reasons for the non-use or wrong use will be

identified and the ways to overcome those will be

discussed with experts and novices.

A model to support the analysis of influent

factors for the participants during the non-

experiments has been developed (Carro Saavedra et

al. 2015). The model is centred in the individual and

it represents the knowledge processes for him

Increasing the Amount of Knowledge Reuse from Engineering Design Repositories - A Research on the Needs and Behaviours of Novice

Designers

associated to the factors influencing each process.

Three knowledge processes were identified and

seven factors were allocated to those processes. On

that basis, the model is being right now extended.

An alternative to the non-experiments could be a

case study. A case study would provide valuable

insights for RQ 2 and RQ 3. The possibility of

conducting a case study will be discussed with the

potential industry partners.

4.3 Prescriptive Study

The PS should provide an answer to the RQ 4. The

proposed support will be based on the outcome of

the DS I. Since the DS I is under development, the

final requirements of the support are not final yet.

However, a preliminary idea is proposed based on

the main barrier found until the moment: the lack of

awareness of the knowledge needs. If novice

designers do not know during the process in which

situations there is knowledge in the repository to

support them, they will not look for it. The

knowledge must be integrated in the design process

in order to have the chance to be reused. Three

hypothesis (H) are established:

H 1: Design situations (potential knowledge reuse

situations) can be systematically characterized.

H 2: Characterizing the design situation according to

pre-established parameters is easier for the novice

designer than the formulation of a search question in

early design phases of design.

H 3: The relevant types of knowledge to support a

design situation can be systematically matched to the

design situation.

Figure 5: Overview of the hypothesis formulated to ideate

the support.

The types of reuse situations and a way of

characterizing them are addressed in RQ 2. The goal

is to find a way of characterizing the design

situations for novices during early phases of design

that is suitable for designers to be made. Thus, they

could characterize their situations during the design

process and be connected to the type of knowledge

that was previously generated and considered useful

for the described situation.

The outcome of RQ 3 are the types of knowledge

to be reused. The idea is that types of situations and

types of knowledge can be systematically matched

(see Figure 5).

Based on these hypothesis, we propose

supporting novice designers in the final stage of the

knowledge reuse cycle (defined as reusing stage by

Markus 2001). One extra step have been added at

the beginning based on the first results of RQ 1:

realizing knowledge need. The proposed support is

depicted in Figure 6.

Figure 6: Proposed support of the steps during the

“reusing” stage of the knowledge reuse cycle.

Realizing knowledge need is supported by

indirect measure of indicators of a knowledge reuse

situation. That means, monitoring certain aspects of

the design process (e.g. time per task, keywords in

the opened documents, etc.) and recognizing thus the

knowledge need. The indicators will be investigated

and a methods for measuring will be proposed.

Defining search question is supported by the

characterization of the design situation (see H 2).

The characterization is the outcome of the RQ 2.

Locating experts or expertise and selecting an

appropriate expert or expertise are supported

automatically through the mapping of the design

situation characterized to the knowledge suitable for

DC3K 2015 - Doctoral Consortium on Knowledge Discovery, Knowledge Engineering and Knowledge Management

it. All piece of knowledge in the repository is

associated to a design situation. The types of

knowledge to be associated to the design situations

are the outcome of RQ 3.

The application of the knowledge is supported

because the knowledge provided matches the

situation. That means that aspects related to the

situation like motivation of designer or need of

knowledge contextualization are considered, so the

adequate piece of knowledge for its correct

interpretation under the situation is provided.

4.4 Descriptive Study II

The applicability of the proposed approach will be

evaluated in non-experiments, in which novice

designers are given a design task and the support.

The suitability of the characterization of design

situations by designers and the replicability of the

characterization will be the main aspects to analyse.

Suggestions for updates on the support will be

considered and the support will be further

developed. Several iterations will be conducted. The

exact number depends on the available time.

The final evaluation will be done in comparative

experiments. One group of novices will be given a

design task to realize without the support, whereas

another group of novices will receive the support.

The results will be compared to analyse the effects

of the support on the reuse of the knowledge

contained in the repository.

5 EXPECTED OUTCOME

Two main outcomes are expected:

 Understanding about the influent factors for

knowledge reuse by novice designers, their

needs for knowledge and the situations

during early-phases of the design process in

which knowledge may be reused.

 An approach to support novice designers

reusing knowledge from company’s

repositories during early-phases of design.

The approach will be continuously tested and

refined according to the results of real application

during design workshops with novice designers.

Thus, the suitability for novice designers is assured.

The support to be developed does not attempt to

address the complete knowledge reuse cycle under

consideration of all its stakeholders. The intention is

to understand the specific needs of novice designers

and how they could be supported. The proposed

support must be seen as the goal to pursue by a

holistic approach for knowledge reuse. Further

investigations should consider the integration in the

support for novices in all stages of the reuse cycle

(capture, package, distribution) and the requirements

of the stakeholders involved (knowledge producers,

intermediaries, other knowledge consumers).

6 STAGE OF THE RESEARCH

A Research Clarification (RC) based on literature

review was conducted in order to find evidence of

the existent problem and determine the research

goals. The research questions have been defined as

well as the areas of research and contribution.

The approach to address the Descriptive Study I

(DS I) has been developed and initiated. The first

findings from literature review provide an initial

answer to RQ 2 and RQ 3. A model to understand

the influent factors for the individual (novice

designer) while reusing design knowledge was

developed (Carro Saavedra et al. 2015). The model

will support the analysis of the non-experiments in

order to answer the RQ 1. At the actual stage we are

looking for industry partners to collaborate for the

non-experiments. The possibility of conducting a

case study will be discussed with the potential

partners. We plan to prepare and conduct the non-

experiments in 2016. We hope to provide answers

for research question RQ 2 and RQ 3 during 2016.

A preliminary approach for the Prescriptive

Study (PS) was developed. It builds upon the

outcomes of the DS I. The PS as well as the

Descriptive Study II are planned for 2017. The

research finishes in February 2018.

REFERENCES

Ahmed, S., Wallace, K., Blessing, L., 2000. Identifying

differences between novice and experienced designers.

Proceedings of Engineering Design Conference,

Brunel University, Uxbridge, pp. 97-106.

Ahmed, S., Wallace, K. M., 2004. Identifying and

supporting the knowledge needs of novice designers

within the aerospace industry. Journal of Engineering

Design, 15:5, 475-492.

Alavi, M., Leidner, D. E., 2001. Knowledge management

and Knowledge Management Systems: Conceptual

Foundations and Research Issues. MIS Quarterly,

25(1), 107-136.

Bhatta, S. R., Goel, A. K., 2002. Design patterns and

creative design. In Chakrabarti, A., Engineering

Desing Synthesis. Understanding, Approaches and

Tools (pp. 271-284). London: Springer.

Increasing the Amount of Knowledge Reuse from Engineering Design Repositories - A Research on the Needs and Behaviours of Novice

Designers

Baxter, D., Gao, J., Case, J., Harding, J., Young, B.,

Cochrane, S., Dani, S., 2007. An Engineering Design

Knowledge Reuse Methodology Using Process Model-

ling. Research in Engineering Design, 18(1), 37-48.

Blessing, L. and Wallace, K. 2000. Supporting the

Knowledge Life Cycle. MIT Sloan Management

Review, pp. 75-83.

Blessing, L., Chakrabarti, A., 2009. DRM, a Design

Research Methodology. Springer. London.

Carro Saavedra, C., Fernández Miguel, R. and Lindeman,

U., 2015. A worker-centered model to understand the

factors influencing knowledge application.

Proceedings of the 11

International Conference on

Knowledge Management, 04-06 November, Osaka.

Chirumalla, K., 2013. Development of a Methodology for

Lessons Learned Practice. From post-project learning

to continuous process-based approach. Doctoral

Thesis. Lulea University of Technology.

Cook, T. D., Campbell, D. T., 1979. Quasi-

experimentation: design and analysis issues for field

settings. Houghton Mifflin Company, Boston.

Cross, M. S., Sivaloganathan, S., 2007. Specialist

knowledge identification, classification, and usage in

company-specific new product development

processes. Proceedings of the Institution of

Mechanical Engineers, Part B: Journal of Engineering

Manufacture.

Dani, S., Harding, J. A., Case, K., Young, R. I. M.,

Cochrane, S., Gao, J., Baxter, D., 2006. A methodo-

logy for best practice knowledge management.

Proceedings of the Institution of Mechanical

Engineers, Part B: Journal of Engineering

Manufacture, 220(10), pp. 1717-1728.

Davenport, T. H., De Long, D. W., Beers, M. C, 1998.

Successful Knowledge Management Projects. Sloan

Management Review, 39(2), 43-57.

Davenport, T. H, Prusak, L., 1998. Working Knowledge:

How Organizations Manage what They Know.

Harvard Business School Press. Boston.

De Long, D. W., Fahey, L., 2000. Diagnosing cultural

barriers to knowledge management. Academy of

Management Executive, 14(4), 113-127.

Duffy, S. M., Duffy, A. H. B., MacCallum, K. J., 1995. A

Design Reuse Model. Proceedings of ICED 95,

Prague, 490-495.

Fruchter, R., Demian, P., 2002. Knowledge Management

for Reuse. International Council for Research and

Innovation in Building and Construction. 12-14 June,

Aarhus School of Architecture.

Gainsburg, J., Rodríguez-Lluesma, C., Bailey, D. E., 2010.

A “knowledge profile” of an engineering occupation:

temporal patterns in the use of engineering knowledge.

Engineering Studies, 2:3, 197-219.

Grant, R. M., 1996a. Prospering in Dynamically-

competitive Environments: Organizational Capability

as Knowledge Integration. Organization Science, 7(4),

375-387.

Grant, R. M., 1996b. Toward a knowledge-based theory of

the firm. Strategic Management Journal, 17, 109-122.

Ichijo, K., Nonaka, I., 2007. Knowledge Creation and

Management: New Challenges for Managers. Oxford

University Press. New York.

Johansson, C., Frostevarg, J., Kaplan, A. F. H., Bertoni,

M., Chirumalla, K., 2012. 3

IEEE International

Conference on Congnitive Infocommunications.

December 2-5, Kosice, Slovakia.

Manohar Singh, R., Gupta, M., 2014. Knowledge

management in teams: empirical integration and

development of a scale. Journal of Knowledge

Management, 18(4), 777-794.

Markus, M. L., 2001. Toward a Theory of Knowledge

Reuse: Types of Knowledge Reuse Situations and

Factors in Reuse Success. Journal of Management

Information Systems (18:1). Pp. 57-93.

McMahon, C., Lowe, A., Culley, S., 2004. Knowledge

management in engineering design: personalization

and codification. Journal of Engineering Design,

15(4), 307-325.

Milton, N., 2010. The Lessons Learned Handbook.

Practical Knowledge-Based Approach to Learning

from Experience. Chandos Publishing, Oxford.

Nonaka, I., 1991. The Knowledge-Creating Company.

Harvard Business Review, 69 (6), 96-104

Nonaka, I., 1994. A Dynamic Theory of Organizational

Knowledge Creation. Organization Science, 5(1),14-37.

Polanyi, M., 1962. Personal Knowledge: Towards a Post-

Critical Philosophy. The University of Chicago Press.

Chicago.

Polanyi, M., 1966. The Tacit Dimension. Anchor Day

Books. New York.

Ponn, J., 2007. Situative Unterstützung der methodischen

Konzeptentwicklung technischer Produkte. Doctoral

Thesis. Technische Universität München.

Probst, G., Gaub, S., Romhardt, K., 1998. Wissen

Managen: Wie Unternehmen ihre wertvollste

Ressource optimal nutzen, Gabler Verlag. Frankfurt.

Ranjbarfard, M., Aghdasi, M., López-Sáez, P., Emilio

Navas, J., 2014. The barriers of knowledge generation,

storage, distribution and application that impede

learning in gas and petroleum companies. Journal of

Knowledge Management, 18(3), 494-522.

Sim, S. K., Duffy, A. H. B, 2003. Towards an ontology of

generic engineering design activities. Research on

Engineering Design, 14, 200-223.

Wallace, K., Ahmed, S., Bracewell, R., 2005. Engineering

knowledge management. In Clarkson, J., Eckert, C.,

Design process improvement. A review of current

practice (pp. 326-343). London: Springer.

Von Krogh, G., 1998. Care in Knowledge Creation.

California Management Review, v40, 133-154.

Zack, M. H., 1999a. Developing a Knowledge Strategy.

California Management Review, 41(3), 125-145.

Zack, M. H., 1999b. Managing Codified Knowledge.

Sloan Management Review, 40(4), 45-58.

Zack, M. H., 2003. Rethinking the Knowledge-Based Orga-

nization. MIT Sloan Management Review, 44(4), 67-71.

Zack, M. H., McKeen, J., Singh, S., 2009. Knowledge

management and organizational performance: an

exploratory analysis. Journal of Knowledge

Management, 13(6), 392-409.

DC3K 2015 - Doctoral Consortium on Knowledge Discovery, Knowledge Engineering and Knowledge Management