Knowledge Management in Process Planning

Denkena, Berend; Shpitalni, M.; Kowalski, P.; Molcho, Gila; Zipori, Y.

doi:10.1016/j.cirp.2007.05.042

Cited by 116 publications

(45 citation statements)

References 11 publications

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“…Such tools are becoming increasingly common and include carbon footprint estimation, life cycle assessment [12][13][14][15] and life cycle management [16,17], design for the environment, and product stewardship [18,19]. Numerous examples of applications of these tools have been reported [20][21][22].…”

Section: Manufacturing and The Environmentmentioning

confidence: 99%

Sustainable Manufacturing and Design: Concepts, Practices and Needs

2012

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An investigation is reported on the importance of integrating sustainability with manufacturing and design, along with other objectives such as function, competitiveness, profitability and productivity. The need of utilizing appropriate tools like design for environment, life cycle assessment and other environmentally sound practices that are cognizant of the entire life cycle of a process or product is highlighted. It is likely that sustainability and environmental stewardship will be increasingly important considerations in manufacturing and design in the future and are likely to influence the main priorities for advancing manufacturing operations and technologies. Designers and manufacturing decision makers who adopt a sustainability focus and establish a sustainability culture within companies are more likely to be successful in enhancing design and manufacturing. It is concluded that more extensive research and collaboration is needed to improve understanding of sustainability in manufacturing and design, and to enhance technology transfer and applications of sustainability.

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Section: Manufacturing and The Environmentmentioning

confidence: 99%

Sustainable Manufacturing and Design: Concepts, Practices and Needs

2012

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“…As is commonly recognized, knowledge is an essential asset for organizations and plays a crucial role in innovation; innovation can be regarded as the knowledge-based creation, and the knowledge-based outcome [13,39,40]. Process innovation knowledge is used to support process innovation activities correctly implemented and to produce new process knowledge.…”

Section: Knowledge-driven Computer-aided Process Innovationmentioning

confidence: 99%

Manufacturing Process Innovation-Oriented Knowledge Evaluation Using MCDM and Fuzzy Linguistic Computing in an Open Innovation Environment

Wang

Tian

et al. 2017

Sustainability

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In today's complex, constantly evolving and innovation-supporting manufacturing systems, knowledge plays a vital role in sustainable manufacturing process planning and problem-solving, especially in the case of Computer-Aided Process Innovation (CAPI). To obtain formalized and promising process innovation knowledge under the open innovation paradigm, it is necessary to evaluate candidate knowledge and encourage improvement suggestions based on actual innovation situations. This paper proposes a process innovation-oriented knowledge evaluation approach using Multi-Criteria Decision-Making (MCDM) and fuzzy linguistic computing. Firstly, a comprehensive hierarchy evaluation index system for process innovation knowledge is designed. Secondly, by combining an analytic hierarchy process with fuzzy linguistic computing, a comprehensive criteria weighting determination method is applied to effectively aggregate the evaluation of criteria weights for each criterion and corresponding sub-criteria. Furthermore, fuzzy linguistic evaluations of performance ratings for each criterion and corresponding sub-criteria are calculated. Thus, a process innovation knowledge comprehensive value can be determined. Finally, an illustrative example of knowledge capture, evaluation and knowledge-inspired process problem solving for micro-turbine machining is presented to demonstrate the applicability of the proposed approach. It is expected that our model would lay the foundation for knowledge-driven CAPI in sustainable manufacturing.

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“…The study on (Huang and Diao, 2008) proves that those documentations were difficult to understand and usage was not very prominent for the employees who will work in future, due to the documentation format as wells as their standards. In the papers (Denkena et al, 2007), due to the change business standards, about 50% of information was not presented in information system. Moreover the concept of information retrieval and reuse are not applicable for the systems, because they are only documented but not managed.…”

Section: Related Workmentioning

confidence: 99%

An Advanced ontology based automatic approach in improving the similarity by means of combining the sub‐graphs between the information

Sumathy

Chidambaram

2016

Int. j. adv. appl. sci

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In this research an advanced and automatic approach in finding the new products which are similar to the previous one that results in a rapid experience in production of design of manufacturing procedure of the new product has been proposed. The proposed work is based on advanced ontology based semantic model which computes similarity between the subgraphs in an effective manner. It builds a hierarchical structure by means of new similarity index that forms by overlapping sub-graph of existing two product concepts. By means of stored data the similarity measurement is calculated by matching the similar characteristics with the new one that helps in discovering knowledge. The examined result with the real-time data shows minimum computation cost along with high processing speed in similarity according to the global environment. Thus proves the proposed scheme is far better than other existing similarity approaches.

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Knowledge Management in Process Planning

Cited by 116 publications

References 11 publications

Sustainable Manufacturing and Design: Concepts, Practices and Needs

Sustainable Manufacturing and Design: Concepts, Practices and Needs

Manufacturing Process Innovation-Oriented Knowledge Evaluation Using MCDM and Fuzzy Linguistic Computing in an Open Innovation Environment

An Advanced ontology based automatic approach in improving the similarity by means of combining the sub‐graphs between the information

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