Lean Thinking For Lead-Time Reduction And Efficient Knowledge Creation In Product Development

<p>There are many distinct differences between manufacturing process and Product Development (PD) process, so lean tools have to be customized to deliver results in the later domain. The main focus of this dissertation is to extend them to manage and improve the PD process in order to develop the product faster while improving or at least maintaining the level of performance and quality. For aforesaid purpose, value stream mapping (VSM) method is used to explore the wastes, inefficiencies, non-valued added steps in a single, definable process out of complete PD process. Besides numerous intangible benefits, VSM framework will help the development team to reduce the lead-time by over 50%. Next, a set of ten lean tools and methods is proposed in order to support and improve efficiency of the knowledge creation (KC) process. The approach establishes a KC framework in PD environment, and systematically demonstrates how these lean tools and methods conceptually fit into and play a significant role in enhancing the performance of KC process. Following this, each of them is analysed and appropriately positioned in a SECI (socialization-externalization-combination-internalization) mode depending on the best fit. Quick and correct KC at the right time aids in further improving the development lead-time and product quality. </p> <p> Such successful innovation is often associated with adoption and execution of all SECI modes within any PD phase. This dissertation attempts to argue with this general notion and to distinguish different PD phases' affinity corresponding to distinct SECI mode. In this regard, an extended Fuzzy Analytic Hierarchy Process (EFAHP) approach to determine the ranking in which any PD phase is influenced from SECI modes is proposed. In the EFAHP approach, the complex problem of KC is first itemized into a simple hierarchical structure for pairwise comparisons. Next, a triangular fuzzy number concept is applied to capture the inherent vagueness in linguistic terms of a decision-maker. This dissertation recommends mapping the triangular fuzzy numbers (TFNs) with normal distributions about X-axis when the pessimistic value of one TFN is less than the optimistic value of other TFN (t23 ≤ t11). This allows us to develop a mathematical formulation to estimate the degree of possibility of two criteria as opposed to zero resulted by the use of the current technique in the literature. In order to demonstrate the applicability and usefulness of the proposed EFAHP in ranking the SECI modes, an empirical study of development phase is considered. After stringent analysis, we found that the combination mode was the mode that highly influenced the development phase.</p>

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Open Access Dissertation

Discipline thesis:degree_discipline

Industrial and Manufacturing Engineering

Year dc:date.available

2015

Author dc:creator

• Tyagi, Satish Kumar

Contributors dc:contributor

• Kai Yang

• Fuzzy AHP
• Knowledge creation
• Lean thinking
• Product development
• SECI model
• Industrial Engineering

Repository record dc:identifier

https://digitalcommons.wayne.edu/oa_dissertations/1171

OAI identifier oai:identifier

oai:digitalcommons.wayne.edu:oa_dissertations-2170