Published at : 25 Apr 2019
Volume : IJtech
Vol 10, No 2 (2019)
DOI : https://doi.org/10.14716/ijtech.v10i2.3064
Alfadhlani | Industrial Engineering Department, Andalas University, Limau Manis, Padang, 25163, Indonesia |
Anas Ma’ruf | Industrial Engineering Department, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Indonesia |
Isa Setiasyah Toha | Industrial Engineering Department, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Indonesia |
T.M.A. Ari Samadhi | Industrial Engineering Department, Bandung Institute of Technology, Jl. Ganesha 10, Bandung, 40132, Indonesia |
The assembly sequence
planning of a product can be generated through three phases: first, generating
precedence constraints; second, searching for assembly sequence alternatives;
and third, selecting the best assembly sequence. Assembly sequence generation
needs precedence constraints in order to find a feasible assembly. A collision
between two components can cause the blocking of one by the other after assembly.
This research proposes an automated method for generating precedence
constraints. The method employs certain information: the collision-free
assembly path; the number of connections between components; and component volume.
This information is extracted from the CAD (Computer Aided Design) database.
The methods resulting from the research will be used to develop an automated process
of assembly sequence generation using a three-dimensional (3D) solid drawing in
the form of a stacked drawing in a CAD system.
Assembly sequence; CAD; Collision detection; Precedence constraint
Assembly is the process of joining parts together to form a completed product, and needs to be evaluated as early as possible in the product design stage so that it will not be difficult to install a component because of tolerance error, inappropriate dimensions or geometry errors. A product designer needs to improve the design if assembly difficulties occur, an additional task which will increase the production cost. It is essential to plan assembly because there are feasible assembly sequence alternatives which can be selected, based on dimensions and geometry. An appropriate assembly sequence will reduce operational difficulties, tool quantity and work hours, so consequently it will also reduce production costs (Lai & Huang, 2004).
Designers can evaluate the assembly process at the early stages of the design using CAD. Previous researchers have proposed assembly sequence generation methods based on CAD systems, such as Delchambre (1992), Ariastuti et al. (1998), Tseng and Li (1999), Toha et al. (2004) and Alfadhlani and Toha (2005; 2008). Some of these studies have proposed automatic methods to generate the assembly sequence.
Possible assembly sequences for complex product assembly planning is determined by consider precedence relation information (Lai & Huang, 2004). Precedence relation is defined as precedence constraint, it contains information about the list of components that must be assembled beforehand (predecessors) and the choice of components to be joined together later
(successors). In assembly planning, the precedence relation needs to be determined to ensure that the planned assembly operation can be applied. The geometric model of product assembly can be used to generate precedence constraints.
Delchambre (1992) distinguished two types of precedence constraint: hard constraints and soft constraints. Hard constraints arise because of the geometrical condition of components and their position in the final assembly, while soft constraints comprise stacking and technological constraints. Stacking constraints arise if external fasteners (such as screws) hold together a stack of other components, so it is best to impose a given assembly sequence for this group of components. On the other hand, technological constraints are specified by the operator, and arise because of the use of specific tools. It is recommended that soft constraints are considered in assembly planning. If the generated assembly sequences are feasible without considering the soft constraints, then they can be ignored.
Ariastuti et al. (1998) and Toha et al. (2004) used "face and joint" information as precedence constraints which are determined from the assembly line in the CAD system, while Li et al. (2010) identified such constraints by using a connector knowledge-based approach, employing standard connectors such as threaded fasteners or keys. Morato et al. (2013) generated precedence constraints based on component motion planning and component interaction clusters, which can mutually affect each others’ accessibility when assembled. All three methods above used the disassembly approach, which requires complex geometry analysis.
A feasible assembly must be free of collisions between components, which can occur when one component is blocked by another in the assembly. The collision-free assembly path (CFAP) information in this paper was established by using a CFAP algorithm proposed by Alfadhlani et al. (2011). The paper discusses the development of an automated method for generating precedence constraints using the disassembly approach, and considering the CFAP information, the number of component connections, and component volume. All these data were extracted from the CAD database using the component database formation algorithm proposed by Alfadhlani et al. (2011). SolidWorks 2005 was used as the CAD system, and a stacked drawing in a 3D solid model was used as input.
The remainder of the paper is divided into the following sections. Section 2 elaborates the rules of precedence diagramming, while Section 3 explains the process of generating precedence constraints based on a collision-free assembly path. Section 4 explains the priority rules for selecting the component to be released, Section 5 discusses the use of associative law as a rule for improving precedence constraint, and Section 6 describes the algorithm of precedence constraint generation. Section 7 provides an example of the implementation of the proposed methods for generating precedence constraints, and the conclusions are presented in Section 8.
This research was conducted as part of an effort to help product assembly planners to generate feasible assembly sequences automatically. Assembly precedence constraints were determined by the following steps: (1) extract component geometric data from the CAD system; (2) build the component database; (3) detect component collisions; (4) build the collision-free path database; and (5) generate the precedence constraints. The paper proposes a fully automated method for generating precedence constraints using the disassembly approach. A 3D stacked drawing in a solid model is used as input as it has more information than a 2D drawing. The exploded view and the assembly line to obtain connection information for each component, as proposed by Ariastuti et al. (1998) and Toha et al. (2004), and also analysis of the component motion planning, as proposed by Morato et al. (2013), did not need to be performed in this proposed method. Product designers have defined connection types between components when designing products in a CAD system. In SolidWorks, the connection type is defined by the mating type; consequently, the information on the mating type and the volume of the component is used in this method.
A CAD system was used in the development of the models and the algorithm, while the software used was SolidWorks 2005. This CAD system has relatively complete features, so are able to show how the components are assembled to build the final product. We proposed an automatic precedence constraint method in the paper and developed two rules and an algorithm. We built the algorithm using the rules and information on the assembly collision-free path as input. The proposed method was tested, correctly showing the product disassembly precedence constraints. We developed the prototype software in the SolidWorks 2005 CAD system for implementation. The research is a part of an effort which is currently being made to propose an automated method to generate assembly sequences.
The author thanks the Institute of Research and Community Service, University of Andalas for providing financial assistance under grant number 01/UN.16/PL/API/2014.
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