Abstract

In the industry 4.0, the Cyber-physical system (CPS) is one of the most important core which makes the manufacturing process more intelligent. Intelligent assembly operation is an important key in intelligent manufacturing of CPS. To complete the intelligent assembly operation, the cooperation between assembly robotic arm and assembly sequence planning (ASP) is necessary. However, the ASP and writing robotic codes manually is time consuming and requires professional knowledge and experience. Because the Local Coordinate System (LCS) is often ignored when checking for interference. If product have inclined interference and without considering LCS and causing and infeasible ASP. Therefore, this paper proposes a LCCPIAS (Local Coordinate Cyber-Physical Intelligent Assembly System) system to achieve three objective functions. First, this paper presents a dual-projected-based interference analysis approach (DPIAA) that analyzes the relations between components. Second, this paper generates optimal assembly sequence automatically to let the assembly sequence more suitable for the robotic arm to perform the assembly operation. The last one is LCS can recognize inclined interference between components and generate feasible ASP. Furthermore, this paper uses CAD model to verify that the DPIAA is faster and consider LCS interference can solve inclined interference problem. In the future assembly factory, the proposed method can help to realize intelligent manufacturing.

Highlights

  • In the manufacturing process, assembly work consume a lot of cost and time of the whole production

  • The product assembly cost accounts for more than 40% of the total cost in the whole product manufacturing process [2], and the assembly time of the product accounts for the total manufacturing time 20-70%, so intelligent assembly operation is an important key to the Cyber-physical system (CPS) intelligent manufacturing

  • According to the output of dual-projected-based interference analysis approach (DPIAA), the ACO algorithm is used to automatically generate Good assembly sequence, so that the assembly sequence is more suitable for assembly of the robot arm operation

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Summary

Introduction

Assembly work consume a lot of cost and time of the whole production. If the best assembly sequence of products is automatically generated, it will reduce manufacturing time and costs and customers' rapidly changing needs can be met immediately [4, 8]. In order to generate the best assembly sequence, several heuristic algorithms are proposed to solve the problem. In addition if the assembly product has inclined assembly and without considering the LCS coordinates of the part itself only considering GCS, it will may generate wrong ASPs and lead to assembly process errors. According to the output of DPIAA, the ACO algorithm is used to automatically generate Good assembly sequence, so that the assembly sequence is more suitable for assembly of the robot arm operation

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