Remanufacturing Research on Recycling Products of Machinery and Equipment Base on ERM

2012 ◽  
Vol 616-618 ◽  
pp. 1090-1094
Author(s):  
Ying Yin
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
Raw Materials ◽  
Minimum Cost ◽  
Maximum Efficiency ◽  
Product Life ◽  
Environmentally Responsible ◽  
Product Design Process ◽  
Environmentally Responsible Manufacturing

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.

Approximate Product Life Cycle Costing Method for the Conceptual Product Design

CIRP Annals ◽  
2002 ◽  
Vol 51 (1) ◽  
pp. 421-424 ◽  
Author(s):  
J.-H. Park ◽  
K.-K. Seo ◽  
D. Wallace ◽  
K.-I. Lee
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
Life Cycle Costing ◽  
Product Life

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
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
Low Carbon ◽  
Carbon Product ◽  
Product Life

Ontology-Based Malfunction Forecast and Root Cause Analysis in Product Design

2012 ◽  
Author(s):  
Xiaomeng Chang ◽  
Janis Terpenny
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
Design Phase ◽  
Cause Analysis ◽  
Product Life ◽  
Design Improvement ◽  
Root Cause ◽  
Initial Design ◽  
The Cost

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.

Modeling and quantifying uncertainty in the product design phase for effects of user preference changes

2015 ◽  
Vol 115 (9) ◽  
pp. 1637-1665 ◽  
Author(s):  
Hamid Afshari ◽  
Qingjin Peng
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
User Preferences ◽  
User Preference ◽  
Design Parameters ◽  
Accurate Estimation ◽  
Product Life ◽  
Content Type ◽  
External Uncertainty

Purpose – The purpose of this paper is to quantify external and internal uncertainties in product design process. The research addresses the measure of product future changes. Design/methodology/approach – Two methods are proposed to model and quantify uncertainty in the product life cycle. Changes of user preferences are considered as the external uncertainty. Changes stemming from dependencies between components are addressed as the internal uncertainty. Both methods use developed mechanisms to capture and treat changes of user preferences. An agent-based model is developed to simulate sociotechnical events in the product life cycle for the external uncertainty. An innovative application of Big Data Analytics (BDA) is proposed to evaluate the external and internal uncertainties in product design. The methods can identify the most affected product components under uncertainty. Findings – The results show that the proposed method could identify product changes during its life cycle, particularly using the proposed BDA method. Practical implications – It is essential for manufacturers in the competitive market to know their product changes under uncertainty. Proposed methods have potential to optimize design parameters in complex environments. Originality/value – This research bridges the gap of literature in the accurate estimation of uncertainty. The research integrates the change prediction and change transferring, applies data management methods innovatively, and utilizes the proposed methods practically.

Study on Integration Architecture of Product Design and Manufacturing Based on Knowledge Engineering

2012 ◽  
Vol 152-154 ◽  
pp. 1359-1366
Author(s):  
Peng Zhang ◽  
Xiao Wei Xue ◽  
Zhao Lin Li
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Product Design ◽  
Resource Sharing ◽  
Product Life Cycle ◽  
Knowledge Engineering ◽  
Life Cycle Management ◽  
Product Life ◽  
Integration Architecture ◽  
Design And Manufacturing

The paper analyses problems existing in integration models of product design and manufacturing in enterprises. Under the theory of product life cycle management (PLM) and via the platform of J2EE, it builds a framework for establishment of integration architecture in product design and manufacturing based on knowledge engineering. The paper gives a detailed introduction to the structure, function characteristics and realization forms of the architecture. On the basis of this, the paper then studies integration methods of the information system based on XML and explores key technologies in the knowledge base plus network safety of the architecture. Finally, the paper emphatically analyzes types of flow of traditional knowledge and digital knowledge in enterprise knowledge management. The proposed architecture has realized close integration of various sectors so that knowledge runs through the whole process of product life cycle. As a result, the architecture can satisfy modern enterprises’ demand for collaborative manufacturing, resource sharing and network integration while supporting knowledge management and technological innovation.

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