Modularity For Product Family Considering Green Design

As the arising requirement for personalized design of products, theresearch to product family design is becoming more and more important inthe consolidation of resources. At the same time, considering the attentionto ecological design, the consideration of green design in the modularityfor product family design is very significant. However, nowadays thestudies on modularity design always focus on the design for single product,which can’t meet the requirement of mass manufacturing, also lacking theconsideration on ecological needs. Thus, this paper integrates the greendesign and modularity design for family product, using Homogeneityversus Heterogeneity Ratio (HHR) value for the classification ofmodularity and clustering algorithm based on CR value for clustering ofmodularity.In this paper, we classify the modularity of product family using theHomogeneity versus Heterogeneity Ratio (HHR) value, also consideringthe manufacturing quantity to optimize the HHR value, so as to be morepractical to reality.After the classification to modularity of product family, consideringeach modularity, we analyze the relationship between components.Integrating the green properties like the reusing probability, maintenancefluency etc. and get the matrix for the relationship of green design forproduct family.Based on the green matrix of relationship for product family, wepropose to use the clustering algorithm to design the modularity. Using theCR value to optimize the algorithm and acquire the platform for theproduct family modularity design.After the green design to modularity of product family, the case study of refrigerator design is applied in this paper, proving the practicality ofthis methodology. The methodology of modularity design proposed in thispaper reduce the quantity of component design by simplifying the redesignprocess and raise the reuse efficiency.In the end, this paper summarize all the research and propose theexploring space for this methodology and the development probabilities ofthe research.