دانلود مقاله ISI انگلیسی شماره 10459
عنوان فارسی مقاله

سیستم دانش کانبان برای پژوهش مجازی و توسعه

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
10459 2013 16 صفحه PDF سفارش دهید 9460 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Knowledge kanban system for virtual research and development
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Robotics and Computer-Integrated Manufacturing, Volume 29, Issue 3, June 2013, Pages 119–134

کلمات کلیدی
& مجازی تحقیق و توسعه  -    دانش مدیریت کانبان -      بازیابی دانش -     توصیه دانش -
پیش نمایش مقاله
پیش نمایش مقاله سیستم دانش کانبان برای پژوهش مجازی و توسعه

چکیده انگلیسی

Virtual research and development (R&D) is inevitable to reduce the product life cycle. Enterprises tend to rely on their foreign partners for supporting technology and knowledge acquisition to conduct and improve firms’ product development with low R&D risk. R&D is a highly creative and knowledge-intensive activity, Therefore, efficient knowledge flow, which transmits the right knowledge to the right people at the right time, is key to improving efficiency of the R&D process. Kanban supports visual production control using the card of providing information to regulate the flow of inventory and materials. To enhance the knowledge flow efficiency in the virtual R&D process, this study proposes a knowledge kanban system utilizing the philosophy of kanban management and knowledge engineering techniques. Employees can quickly, easily, and exactly determine what knowledge they need to learn, create, share, and maintain by the knowledge kanban system. This system assists employees to do the right thing, to reduce the cycle time of R&D processes, and to enhance the reuse of knowledge, to create new knowledge. To achieve this objective, this study first proposes a knowledge flow model in virtual R&D based on the analysis result of knowledge in virtual enterprises (VEs), and then designs the knowledge kanban model according to the knowledge flow model in virtual R&D and proposes the knowledge kanban functional framework based on the knowledge kanban model. Finally, this study develops the related technologies to implement the knowledge kanban system. The knowledge kanban system is an effective tool to facilitate knowledge creation, storage, transmission and sharing for R&D engineers to develop knowledge in problem solving and product development, to improve enterprise competitiveness.

مقدمه انگلیسی

Virtual research and development (R&D) [1] and [2] is inevitable to reduce the product life cycle. Virtual R&D develops differentiated products and services to meet market needs by multi-functional virtual enterprises, and whose communication, coordination, and cooperation among employees is supported by the Internet and information technologies and the principles of rationalization and collaboration [3], [4] and [5]. Virtual R&D team members who do not work at the same time or place [6] often face tight schedules and a need to start quickly and perform instantly [7]. Therefore, virtual R&D management is recognized as an important task. Kanban implements a manufacturing philosophy of producing what is needed in the right quantity, in the right place, and at the right time [8].Various kanban systems have been designed to control and regulate the manufacture of goods to follow quantity and timing demands. Except for goods, knowledge has also been recognized as an important source of competitive advantage and value creation [9], particularly for the R&D process. R&D processes can transform information of technological advancements and market demands into the needed knowledge for new product concepts and process designs [10]. Knowledge, such as design experience, design knowledge, and an existing product model, has great effect on new product development. Knowledge can facilitate collaborative product development, which enable different enterprises to contribute to a common development project objective. People can make abstractions and analogies between problems and use past experience and skills to solve new problems [11] and [12]. Because R&D is a highly creative and knowledge-intensive activity, easier access to data and documents can help firms reduce the development cycles and lead times [13]. Unfortunately, it is impossible for users to iterate all knowledge to determine the needed knowledge in large-scale knowledge bases, which involves a large amount of knowledge [14], and it is difficult for users to decide what knowledge is needed before they know it. Therefore, efficient knowledge flow, which transmits the right knowledge for the right people at the right time, is the key point to improve efficiency of the R&D process. Searching and sharing knowledge are major parts of knowledge flow, which stimulates organizational learning, innovation, and competencies. Presently, with the rapid development of network communication technology and information technology, people can acquire considerable knowledge from various channels by network communication technologies. However, additional available information and knowledge can result in “information overload,” which impairs the learning desires of knowledge requesters. Consequently, providing more knowledge than needed, often results in poor knowledge utilization. Knowledge sharing refers to the exchange and discussion of knowledge among members of an organization, between internal and external teams, or between organizations to improve organizational competiveness through effective knowledge exchange, integration, and synergy [15] and [16]. Knowledge sharing in distributed environments requires more a priori trust than face-to-face communication [17]. However, trust depends on an implicit set of beliefs, which are vague. Trust varies with time, environment, and other factors. Consequently, trust is fuzzy and dynamic [18], very complex, and cannot be easily evaluated because of its inter-organizational and distribution characteristics [19]. This research develops a knowledge kanban system to facilitate acquisition and utilization of knowledge distributed across allied enterprises, to improve enterprise competitiveness and to help virtual R&D engineers develop knowledge of problem solving and product development. The knowledge kanban system is a pull system that facilitates knowledge transmission, by providing only the right amount and type of knowledge that an employee requires at the right time, using the concept of kanban management and knowledge engineering technologies. The knowledge kanban system is an effective tool to facilitate knowledge creation, storage, transmission and sharing to reduce project lead time and shorter new product development cycles.

نتیجه گیری انگلیسی

This study develops the knowledge kanban system using the concept of kanban management and knowledge engineering technologies. The knowledge kanban system provides visual signals for employees to determine what relevant knowledge needs to be learned to support them to execute their activities smoothly and what knowledge they need to create, share, and revise. The knowledge kanban system enables smooth knowledge flow, which supports knowledge management system for storage, retrieval, transfer, and reuse of knowledge to enhance efficiency of virtual R&D processes. Through knowledge reuse, employees can improve their personal capability to do the right thing first, which can reduce rework and the cycle time of R&D processes. Consequently, efficient knowledge transmission and utilization can improve new knowledge creation, which results in knowledge assets increment to achieve competitive advantage of enterprises. VEs are composed of many diverse and international enterprises. In the future, the knowledge kanban system needs to add multi-language capability. Besides, the knowledge kanban system only notifies employees to create knowledge associated with activities, which is executed by the employee. Converting individual knowledge into organizational knowledge appears as one of the most important tasks to increase knowledge assets for enterprises. Therefore, it is important to develop a knowledge elicitation approach to capture valuable knowledge based on activities and employee personal characteristics.

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