Earticle

In this research, we evaluate on the disassemblability of recycling process for vehicle front door using the symbolic chart method and machine-learning algorithm. It is applied to the front door of 1600cc class vehicle, and then the conventional steel door and CFRP door were compared. Based on the principle symbolic chart method, the number of processes can be different according to decomposer proficiency of suitability of recycling process, so the evaluation method is required to supply this issue. The machine learning algorithm, and artificial intelligence method were applied and the applicable tools for each experiment were used to compensate the variations in the number of processes according to different proficiencies. Because CFRP front door has integrated components compare to steel door, so its disassemblability processes were decreased to 80 from 103 of the conventional steel door’s. It can be confirmed that the disassemblability was increased from the suitability of recycling equation. In case of the steel, disassemblability was approximately 60.6, in case of the CFRP is approximately 72 for car front door. Therefore, it can be concluded that the disassemblability of CFRP was better in the evaluation of suitability of recycling.

In this paper, systematic approach is studied about assemblability and disassemblability of parts in order to reduce the assembly cost, and to disassemble products easily which is possible to recycle the parts. For this purpose, we selected one subassembly, and analysed assembly and disassembly process. From this result, we found the weakpoints of assembly and disassembly process, and then, the influencing parameters of assemblability and disassemblability are defined. On the basis of the analysis of these parameters we grasped the interrelation between assemblability and disassemblability. And, guidelines for assemblability and disassemblability are developed. Finally design alternatives are evaluated quantitatively in the aspects of assembly and disassembly by using the guidelines which developed in this research.

In this paper, to propose guideline of modular design for improvement of ease of disassembly, product structure must be considered. By analyzing characteristics of structure of subassembly, influencing factor of module can be defined and classified. Based on determination factor of influencing factor of module, criteria for improvement of ease of disassembly can be obtained through the interrelationship between product and process factors.

In recent years, Pressure to recycle has stemmed from environmental and economic reasons. This paper examines a new methodology that can estimate the disassemblability considering the recycling. Easy of disassembly estimation method outlined here is shown to provide one of several needed metrics for use during product design. This study suggests five main determining factors-fixing, grasping, access, disassembly and handling-as the five determining factors and determined to evaluate disassemblability. The evaluation based on disassemblability is demonstrated on an automobile parts example.

This paper presents a method for the automatic generation of assembly sequences based on the recursive extraction of a preferred part along with the verification of its disassemblability. To verify the disassemblability of the part we inference the geometric precedence constraints using a method of extracting separable directions for the part and determine the disassemblability cost by the separability and stability cost. The proosed method provides a local optimal solution of finding a cost effective assembly plan, and the feasibility of calculating robot motion programs by evaluating separable directions in flexible manufacturing application. A case study is given to illustrate the concepts and procedure of the proposed scheme.

This paper presents a method of an automatic work time evaluation based on the verification of a disassemblability and assembly configuration. Even though a work time evaluation is an important field of concern for planning assembly lay-out, there are some limitations using cumbersome user query or approximated work time data without considering assembly condition. To overcome such restriction, this paper presents a method to mathematically verify assembly conditions based on the disassemblability, which is defined by the separability and stability cost. The separability cost represents a facility of the part disassembly operation, and the stability cost which represents a degree of the stability for the base assembly motion. Based upon the results, we propose a new approach of evaluating work time using neural networks. The proposed method provides an effective means of solving the work time evaluation problem and gives a design guidance of planning assembly lay-out in flexible manufacturing application. Example study is given to illustrate the concepts and procedure of the proposed schemes.