Modular design to support green life-cycle engineering
Introduction
Not until recent years have people realized the importance of environmental protection. People pay more attention to the environment they are living in and the way people deal with the limited resources. Among resource disposal methods, recycling and garbage classification are two methods widely applied. These ways, however, are passive methods in the launch, usage and damage of products. Moreover, fierce market competition is shortening the product life cycle and the passive resource recycling approach can no longer cope with the ever-increasing burden current products have on the environment. Therefore, it is important to maximize the usage percentage of resources and minimize the damage to the environment in the early product design stage. This kind of more aggressive design tendency is referred to as green life-cycle engineering design (Otto and Wood, 2001, Tseng and Chen, 2004).
The so-called product life cycle refers to the total amount of time from material, manufacturing, assembly, consumer use, and final disposal or recycle of a product, and green life cycle is mainly determined by the last two stages, product use, disposal or recycle. While the use of a product will affect its life span, the disposal and recycle of a product will definitely affect the environment and the resource availability. To prolong the product’s life cycle and to make the most of resources, the end of the product life cycle does not imply the disposal of the components. Instead, we need to solve the problem from the root of the enterprise activities, especially from the R&D of new products (Tseng & Chen, 2004). Many researchers have explored the issue from different points of view, such as design for environment (DFE), design for recycling (DFR), and design for disassembly (DFD) (Güngör and Gupta, 1999, Lambert, 2003). Due to the fact that well-designed modular structures can improve product life-cycle activities, modularity plays a more important role than the whole product life-cycle approach. For example, not only will common modules increase the chances of efficient reuse and recycling operation, they also feature ease of upgrade and maintenance, ease of product diagnosis, repair, and disposal, and so on.
Taking green life cycle into consideration, the authors attempted to apply the green modular concept to product design. Advantages for this study are listed as follows (Gu and Sosale, 1999, Otto and Wood, 2001, Zhang and Gershenson, 2003):
- (1)
Reexamination of product functions and specifications ensures that the goal of environmental protection can be achieved.
- (2)
Reduction in product assembly time can enhance the efficiency of production.
- (3)
Products or product components can be recycled, reused and disposed of more easily.
- (4)
The life-cycle cost estimation enables designers to bring product cost into control.
There are different perspectives with respect to measuring the product modularity. Jose and Tollenaere (2005) had made a comprehensive review regarding the modular design issue. In Section 2, the different viewpoints will be discussed. In the past, most conceptual descriptions have been rendered regarding the green-oriented modular study but a scientific methodology is rarely seen. In our study, a new methodology of green-oriented modular design will be proposed in Section 3. The approach comprises the following three parts:
- (1)
Clarifying the liaison intensity of components: in addition to clarifying the liaison relationships of components through visualized diagrams, the liaison intensity of components is decided by their engineering attributes.
- (2)
The clustering algorithm: the goal of clustering is to assign the components whose liaison intensities are stronger in the same module. In this way, the liaison intensities among different modules are relatively weaker, indicating that it is easy to connect the components if they are assigned to the same module.
- (3)
Green pollution and cost analysis: while changing the design specification, designers need to green pollution take and costs into consideration so that they can work out the proper design ideas in accordance with the material property to fulfill the product functions.
These three parts will be discussed in Sections 4 Estimation of liaison intensity among components, 5 Grouping genetic algorithm (GGA), 6 Balance between cost and green design respectively. In Section 7, the design of a table lamp will be used to illustrate the methodology proposed in this study. Finally, conclusions are made in Section 8.
Section snippets
Diverse viewpoints
In the descriptive model of product functions, according to Otto and Wood (2001), modules can be defined as the integral physical structures corresponding to specific product functions. Meanwhile, the product function model is closely related to the customer’s needs. Therefore, a proper modular design is able to reduce the production cost and assemble components effectively into new products to cope with the rapid change of customer’s needs. The approach to meeting the customer’s needs and
Outline framework and related assumption for green-oriented modular design
The proposed methodology for the green modular design is shown in Fig. 2. The detail procedure is illustrated as follows:
- Stage 1:
Build up the scoring system:
- Step 1:
Evaluate the liaison intensity of product (Section 4.2).
- Step 2:
Calculate the liaison intensity (Section 4.3).
- Step 1:
- Stage 2:
Grouping genetic algorithms:
- Step 3:
Use the heuristic algorithm as the initial population (Section 5.3).
- Step 4:
Reproduction, an optimal rate between 0 and 1 is randomly generated for the use of reproduction. Such a rate serves as the threshold for the selection
- Step 3:
Terminology description
The section explains the definitions proposed to deal with modular design. Suppose an assembly product P is composed of a set of elements called components. These components are connected through mechanical links (liaisons). In this non-oriented connected graph G(C, L), C is the set of Nc nodes representing the components of the product, and L is the set of Nl edges symbolizing the links (liaisons) between these components (De Fazio & Whitney, 1987).
Product P = {Ci∣ i = 1, 2, 3, … , Nc}
Interconnected by N
Encoding
The diagram shown in Fig. 3 illustrates the way of coding proposed in this paper, each gene of which stands for a module. Such kind of genetic coding features a flexible length of the chromosome, which is helpful for searching the optimal number of modules. Moreover, it avoids the problem that too long a chromosome will reduce the efficiency. For a chromosome composed of five modules “ABCDE”, the number of modules can be expressed as A = {1}, B = {3, 6}, C = {4}, D = {2}, E = {5}. Each gene can correspond
Green analysis
The green analysis is conducted in this study according to the pollution value offered by Eco-indicator99 (http://www.pre.nl/). The Eco-indicator refers to the pollution reference value the component material causes to the environment. The higher value means higher injuries for the environment after the product is used. Because weight is used as an investigation unit for Eco-indicator, the estimated pollution value for a component can be represented as Formula (6):In
A practical example
As shown in Fig. 5a, the table lamp is composed of 22 components and 22 liaisons. First of all, we need to evaluate the liaison intensity of each component in terms of each engineering attribute. The outcome liaison intensity is shown in Table 5. Take liaison 1–2 as an example, it shows the relationship between Components 1 and 2; the single face contact has an intensity of 18 (Table 1); the put on combination type’s intensity is 4 (Table 2); the intensity of the hand type of assembly is 7 (
Conclusions
In this study, new methodologies for evaluating product modularity from the viewpoint of green life cycle are proposed. First, a score system using the liaison graph was adopted to evaluate the liaison intensity between components. Moreover, a GGA was adopted for the clustering of modules. Finally, green pollution and cost analysis was conducted to evaluate the clustering result. When the material of components is changed, the product component design is also modified, and so are the relations
Acknowledgement
Research was supported by the National Science Council of the Republic of China under grant number NSC 95-2221-E-167-021.
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