Notes on IT and NPD

I read a paper-Information Technology and New Product Development by Muammer Ozer-and summarized it using the diagram below.

Some Notes on Knowledge Management

Definition
"Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating  and incorporating new  experiences  and information. It
originates and is applied in the minds of knowers. In organizations, it often becomes  embedded not only in documents or repositories but also in organizational routines, processes, practices,  and norms." [1]

Explicit and tacit

Explicit knowledge is often referred to those that can be codified and transmitted in a systematic and formal representation or language.

Tacit knowledge is often referred to personal, context specific knowledge that is difficult to formalize,
record, articulate, or encode. Tacit knowledge can be converted to explicit knowledge (externalization).

Both kinds of knowledge can be embedded in a company's products and processes.

Categories of KM strategies[2]

Codification and Personalization

Codification relies on computers. The value of codification lies in its ability to create economics of reuse. The goal of such an approach is that of connecting people with reusable codified knowledge.

Personalization relies more on social networks that allow knowledge workers to share tacit knowledge. Personalization creates value by connecting people with relevant knowledge. 

NPD[2]

New Product Development is a knowledge-intensive activity.

Characteristics:

(1) Short product & process life cycle

(2) Cross functional collaboration

(3) Cross institutional collaboration

(4) Transient existence of teams & high turn over (loss of knowledge)

[1] Davenport, T. H. and L. Prusak (2000). Working Knowledge: How Organizations Manage What They Know, Harvard Business Press.

[2] Ramesh, B. and A. Tiwana (1999). "Supporting collaborative process knowledge management in new product development teams." Decis. Support Syst. 27(1-2): 213-235.

Complexity research from Nam Suh

Nam P. Suh gave "Complexity in Engineering" in the CIRP 2005 Annual, which seems to be an abstract of his book. The book cover is a nice picture of fractals. 

I enjoy the introduction part greatly as it has some interesting points and says a lot of things I want to say but cannot say that clear. There is no unified definition of complexity, because researchers just use this word to satisfy their 'immediate needs'. So he intended to create a fundamental and scientific approach to complexity.

There are two interesting points about which  I would like to read more literature. Firstly, he gave different goals of engineering, natural science and social science in dealing with complexity, and stated that the underlying principles of complexity are the same in different disciplines. Secondly, he classified complexity methods into two camps- the physical domain and the functional domain.

His complexity theory is based on his former work-axiomatic design (AD). He defined four types of complexity- real, imaginary, combinatorial and periodic- as shown in the figure I created below.

It has also been mentioned that the introduction of functional periodicity can reduce system complexity. But there is not much detail about this. I would like to read his book and learn more. 

Some questions to think about:

1. Is this method applicable to PD process instead of design?

2. How do we implement this in real life?

乱想

今天看了同学的婚纱照，看着看着忽然想：我什么时候才能结婚啊...想完就被自己这个想法吓了一小跳

I should develop a better research plan/schedule

My reviewer, who is also a nice professor, recommended the book <DRM: a Design Research Methodology> in the PLM conference.

I am now reading the framework of the methodology. It would be a good idea if I can develop a research plan/schedule based on this.
Stage1: RC-Research Clarification
Stage2: DS I- Descriptive Study I
Stage3: PS -Prescriptive Study
Stage4: DS II -Descriptive Study II

Some questions to be considered:
How do you define the success of this research?
How do you evaluate the outcome?
What is the existing situation and desired situation respectively?

About the definition of complexity

The term 'complexity' does not have a unified definition yet. I used to think that a clear and widely accepted definition is necessary to do research on complexity, so the first objective of my research is to understand complexity and try to give it a general definition covering most fields. But after doing some literature review I found it not easy. This term has been used so widely, and even 'abused' [1],  in numerous fields. Complexity in one field can be defined totally different from it is in another. For example, in evolution, Kauffman viewed complexity as “the consequence of attempting to optimize systems with increasingly many conflicting constraints among the components” [2], whereas in computer science, complexity is often referred as the time or space used in computation [3]. The term 'complexity' itself is quite complex in the literature.

Why is this? It can be seen from the literature review that the definitions vary with the research target and scope. Each researcher lives in his/her own context, sees his/her own target, thinks about his/her own objectives. As a result, definitions are mostly limited to some specific problems, which cannot be applied to other areas. So others will then define their own complexity.

Do we need a unified definition? I would say no. Sometimes it is good we have various definitions for various fields and situations. Really general definitions will become those in dictionaries - 'the features of a problem or situation that are difficult to understand', which cannot provide much useful information to a specific problem or situation.

But we do need a definition for our own research scope in order to understand the problem and provide a basis for the research. So actually what we should do first is to clarify the research scope and target. 'Complexity in PD' is still big and need to be reduced.

1.Vicsek, T., Complexity: The bigger picture. Nature, 2002. 418(6894): p. 131-131.
2. Kauffman, S.A., The Origins of Order: Self Organization and Selection in Evolution1993: Oxford University Press.
3. Hartmanis, J. and A.M. Society, Computational Complexity Theory1989: American Mathematical Society.

PLM and social network - some ideas from the 9th international conference on PLM

The 9th international conference on PLM was held in Montreal. From the presentations I attended, it seems that one trend for PLM is that it will become more and more 'social' in the future.

One professor from Germany asked an interesting question: can product have a facebook? He proposed to use facebook as a Product Avatar representation for intelligent product. He said a product can have a facebook profile instead of a fan page. The facebook functions were interpreted as PLM functions. For example, 'in a relationship to' means 'connected', 'married' means 'constantly connected' and 'it's complicated' means 'connection with problems'. It is pretty fun seeing a set-off shaft is' in a relationship' XD. It seems that a facebook profile of products help manufacturers and customers to manage the huge amount of variations and keep all information and records up-to-date.


The keynote speaker from Dassault System gave the speech on the topic 'From traditional PLM to social PLM'. They developed a '3D Experience' platform, including '3D SwYm' for online collaboration and social innovation.


A presenter from a German company proposed informal communication in PD because this would-as she put-'improve the teamwork inside companies'.


Social PLM offers the advantages of faster information sharing, more customer interaction, more opportunities of innovation, etc. But does this mitigate complexity in PD or the opposite? Firstly, more customization adds product variety thus management may need to be improved; secondly, more information, if not managed well, will make searching very difficult and time consuming, thus good mechanism is needed to manage all the knowledge.