Low-carbon product design for product life cycle

2015 ◽  
Vol 26 (10-12) ◽  
pp. 321-339 ◽  
Author(s):  
Bin He ◽  
Jun Wang ◽  
Shan Huang ◽  
Yan Wang
CIRP Annals ◽  
2002 ◽  
Vol 51 (1) ◽  
pp. 421-424 ◽  
Author(s):  
J.-H. Park ◽  
K.-K. Seo ◽  
D. Wallace ◽  
K.-I. Lee

2012 ◽  
Vol 616-618 ◽  
pp. 1090-1094
Author(s):  
Ying Yin

In the product design process,according to the environmentally responsible manufacturing principle to carry out remanufacturing engineering design,to achieve the purpose of reducing the amount of raw materials, energy conservation and protect the environment, remanufacture is a systemic engineering to consider the product life cycle, which can prolong the life of the product, optimize product design, achieve minimum cost of product life-cycle and maximum efficiency and minimum environmental pollution ultimately.


2014 ◽  
Vol 909 ◽  
pp. 154-159
Author(s):  
Rui Ping Jia

Based on low-carbon and product life-cycle design concept, this paper classifies risk factors in different stages of automotive product life cycle design risk evaluation indicator system and analyzes the different risk categories weight adopting the rough set and analytical hierarchy process to determine the key risks of automotive product in different stages of life cycle. Additionally, real instances are cited to verify the conclusions.


Author(s):  
Xiaomeng Chang ◽  
Janis Terpenny

In product design, passing undetected errors to the downstream can cause error avalanche, could diminish product acceptance and largely increase the overall cost. Yet, it is difficult for designers to collect all the related potential errors from different departments in the initial design phase. In order to deal with these problems, this paper puts forward an ontology based method to integrate related history error data from different data sources of multiple departments in an enterprise. By using the advantages of ontologies and ontology-based information systems in knowledge management and semantic reasoning, the method enables the investigation of the root cause of the related potential malfunctions in the early product design phase. The framework can provide warnings and root causes of related potential errors in design based on history data and further continuously improve the product design. In this manner, this method is expected to reduce the knowledge limitation of designers in the initial design phase, help designers consider the problems in the whole enterprise and the product life cycle more completely, facilitate design improvement more accurately and efficiently, and further reduce the cost of the overall product life cycle.


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