How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

Revolutionizing product development

Value stream mapping to reduce the lead-time of a product development process

This paper proposes a big-data analytics-based approach that considers social media (Twitter) data for the identification of supply chain management issues in food industries. In particular, the proposed approach includes text analysis using a support vector machine (SVM) and hierarchical clustering with multiscale bootstrap resampling. The result of this approach included a cluster of words which could inform supply-chain (SC) decision makers about customer feedback and issues in the flow/quality of food products. A case study in the beef supply chain was analysed using the proposed approach, where three weeks of data from Twitter were used.

/pdf/social-media-data-analytics-to-improve-supply-chain-4o90m8ciw3.pdf

Social media data analytics to improve supply chain management in food industries

Lean tools and methods to support efficient knowledge creation

Design for Six Sigma, lean product development and lean knowledge management are three effective methodologies in improving a product development process. The performance of a product development process can be measured by product value, product quality, product development lean time, efficiency and product life cycle cost. Design for Six Sigma can greatly improve product value and quality. Lean product development and lean knowledge management can help to achieve better product development lead time and efficiency by reducing wastes. Lean knowledge management can also help to improve product value and reduce product life cycle cost by adopting better technology and practices. These three methodologies are complementary and should be integrated.

The integration of DFSS, lean product development and lean knowledge management

The research under product development domain identifies and implements new concepts in design, planning, manufacturing, testing, and service sectors to keep up with the market demands. Many product developments are multi-generational in nature and may require redesigning the product at each generation because an optimized strategy for a single generation may not be the best option in the multi-generation scenarios. With this regard, this article proposes a novel product life-cycle cost estimation model to support engineering decision-making in a multi-generational product development environment. This cost estimation model develops a mathematical formulation which has three major cost constituents: development cost, service cost, and associated risks cost. The risks cost further includes three components coming from technical risk, market risk, and operation risk. The developed mathematical formulation measures the on-going multi-generational product development’s status, addresses its basic needs such a...

Development of a Product Life-Cycle Cost Estimation Model to Support Engineering Decision-Making in a Multi-Generational Product Development Environment

Many product development processes are multi-generational in nature and may require redesign of the product at each generation. This is due to the fact that an optimized product development strategy for a single generation may not be the best option for multi-generation scenarios. To provide measurements for deployment of multi-generational product development (MGPD), an integrated project cost model has been introduced in this paper. This model posits that integrated product development cost consists of three factors, namely: product development cost, service cost and associated risks costs. Further, the risks cost includes three main factors: technical risk, market risk and operation risk. This specialized product development framework addresses the basic needs of MGPD, such as design for future reuse and design for modularity, and also serves as a decision tool for project management. For the purpose of validating the proposed model, an empirical case study is illustrated by considering three candidate concepts. Therefore, the proposed strategic cost model measures the on-going MGPD status, as well as provides a cost tools to support the management decision-making.

Xianming Cai

Papers

Value stream mapping to reduce the lead-time of a product development process

Lean tools and methods to support efficient knowledge creation

The integration of DFSS, lean product development and lean knowledge management

Development of a Product Life-Cycle Cost Estimation Model to Support Engineering Decision-Making in a Multi-Generational Product Development Environment

Activity-based costing model for MGPD