## 2 State of the Art  
Many attempts have been made in the literature toward products' disassembly planning. They mainly focus on the definition of strategies that can guide the designer toward a quantitative evaluation of disassembly ease for products. In Reference [14], the disassembly plant of a computer These approaches can detect interference directly from the 3D representation of a CAD model. However, higher accuracy of the result increases the cost of the computation. Using CAD, product disassembly can be carried out visually on a computer, so it is easier to generate an optimal disassembly sequence and to establish a correct and practical disassembly path for the part in the product. The product disassembly time depends on several factors such as component shape, size and weight, joining element, joining direction, disassembly tools, and equipment [19]. In the literature, different classifications have been proposed for mechanical connections and part interfaces [20; 21]. [PERSON] [22] proposed a structured method for analytically estimating the disassembly time in a complex assembly. They defined a repository (called Liaison_DB) containing the essential time base data of the main assembly liaisons and corrective factors that are used for the disassembly time estimation for calculation of the effective disassembly time. Even if the proposed classifications can be considered to be the basis for the development of a complete characterization of assembly/disassembly liaisons, they have some limitations as they are not complete and do not propose an effective disassembly time for each category or item, and they are based on a theoretical framework and not on experimental analyses. As is well known, the number of possible disassembly sequences significantly increases with the number of parts in a product. Thus, the generation of proper disassembly sequences order is critical. Good attempts to define methods that could help the designer achieve DfD optimization have been presented by [PERSON] [23]. The main issue concerns the complexity of mechanical assemblies that require high computational resources to be solved. The cited method proposed, despite introducing a very good methodology to find an optimal sequence of disassembly, is applied to a very simple subassembly. The application of such a method to a complex assembly does not provide the same optimal results, in terms of computational times, as most of the existing methods often require expensive computational resources while, at the same time, they often fail to find optimal solutions for complex product disassembly. However, the available disassembly evaluation methods today seldom make disassembly the preferred end-of-life solution for the reuse of parts or components in an economically sustainable way for lower value products. DfD has become a challenging problem for the automotive industry because it has been estimated that 75% of the weight of each vehicle disposed of can be recovered. Nowadays BMW is a leader in the dismantling and recovery of parts, and great interest from the market is addressed toward the dismantling of the gearbox [5]. A general classification for disassembly methods can be made as follows:  
* Interactive methods for the sequence generation that get information from the users. They can become unrealistic when the disassembly operator is not the designer of the product [24; 25]. * Automatic methods are preferred way for sequences generation. This allows one to generate the disassembly sequences automatically, according to the geometry relationship among the components in a product. However, how to find the easiest and simplest model for sequence generation in an automatic way is still an issue [26; 27; 28; 29; 30; 31; 32; 33]. * Searching algorithms, based on heuristic searching, wave propagation approach, and [PERSON]'s algorithm [34; 35; 36; 37; 38], have high computational complexity [39].