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1.
Process planning is the function within a manufacturing facility that establishes the machining processes and parameters to be used so as to convert a piece-part from its initial form to the final form predetermined on an engineering drawing. Computer-aided process planning (CAPP) has become a major focus of manufacturing automation as it forms the interface between computer-aided design (CAD) and computer-aided manufacturing (CAM). Issues in CAPP include part representation, process selection, alternative process-plan generation, intermediate surface and tolerance determination, and operation sequencing. This paper focuses on quantitative models for determining cutting dimensions and tolerances for intermediate surfaces, and on a heuristic for sequencing cutting operations.  相似文献   

2.
Computer-aided process planning is an important interface between computer-aided design and computer-aided manufacturing in computer-integrated manufacturing environments. In this paper, the complicated process planning is modeled as a combinatorial optimization problem with constraints, and a hybrid graph and genetic algorithm (GA) approach has been developed. The approach deals with process planning problems in a concurrent manner by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the global optimal objective. Graph theory accompanied with matrix theory, as the basic mathematical tool for operation sequencing, is embedded into the main frame of GA. The precedence constraints between operations are formulated in an operation precedence graph (OPG). The initial population composed of all feasible solutions is generated by an elaborately designed topologic sort algorithm to the OPG. A modified crossover operator guaranteeing only feasible offspring generated is used, two types of mutation strategies are adopted, and a heuristic algorithm is applied to adjust the infeasible plan generated by the mutation operator to the feasible domain. A case study has been carried out to demonstrate the feasibility and efficiency of the proposed approach.  相似文献   

3.
Disassembly sequencing using genetic algorithm   总被引:3,自引:2,他引:1  
At the end-of-life (EOL) of a product, there are several options available for its processing including reuse, remanufacturing, recycling and disposing. In almost all cases, a certain level of disassembly may be necessary. Thus, finding an optimal (or near optimal) disassembly sequence is crucial to increasing the efficiency of the process. Disassembly operations are labor intensive, can be costly, have unique characteristics and cannot be considered as the reverse of assembly operations. Since the complexity of determining the best disassembly sequence increases with increase in the number of parts of the product, it is extremely crucial that an efficient methodology for disassembly sequencing be developed. In this paper, we present a genetic algorithm for disassembly sequencing of EOL products. A case example is considered to demonstrate the functionality of the algorithm.  相似文献   

4.
Computer-aided process planning (CAPP) is one of the key components in computer integrated manufacturing (CIM) environment. Fully automatic CAPP systems require information transfer between CAD/CAM systems to be mutual, dynamic, concurrent, automatic and efficient. The difficulty in achieving this is the management of the vast amount of heterogeneous data, knowledge and complicated inference processes encountered in developing automatic planning systems. The objective of the reported research is to develop a framework for modelling and managing engineering product and manufacturing capability information in an integrated feature-based CAD/knowledge-based process planning environment. The feature-based design system is developed with a commercial boundary representation (Brep) solid modeller with additional feature-modelling functions. The process planning system is developed using a knowledge-based system, which is fully integrated with the design system through an information mapping mechanism. Process planning decisions are made by searching for a match between the product requirements and the process capability of available manufacturing systems. This is achieved by invoking the rules coded in an inferencing mechanism (an inference engine). Both the underlying methodologies and the implementation aspects will be addressed in this paper.  相似文献   

5.
In a multi-plant collaborative manufacturing system, the manufacturing operations and assembly operations for producing a product can be distributed at different plants at various locations. The components are assembled with assembly operations performed in a multi-plant assembly sequence. In this research, a multi-plant assembly sequence planning model is presented by integrating (1) assembly sequence planning, and (2) plant assignment. In assembly sequence planning, the components and assembly operations are sequenced according to the assembly constraints and assembly cost objectives. In plant assignment, the components and assembly operations are assigned to the suitable plants to achieve multi-plant cost objectives. The feasible assembly sequences are generated using the developed graph-based models of assembly precedence graphs and matrices. A genetic algorithm (GA) method is presented to evaluate the multi-plant assembly sequences with an objective of minimizing the total of assembly operational costs and multi-plant costs. The main contribution lies in the new model for multi-plant assembly sequence planning and the new GA encoding scheme for simultaneous assembly sequence planning and plant assignment. Example products are tested and discussed. The test results show that the presented method is feasible and efficient for solving the multi-plant assembly sequence planning problem.  相似文献   

6.
When inspection is conducted in the fields of design and manufacturing, how well that inspection is carried out is as important as how well the design and manufacturing are done. It is important that we consider how well a product is inspected in the offshore industry because offshore structures are operated far from center of operations. This paper presents a fast and effective inspection system to guarantee product performance after the design and manufacturing process by using Mixed Reality (MR) and Ubiquitous Sensor Network (USN).  相似文献   

7.
Process planning is a function in a manufacturing organization that selects the manufacturing processes and parameters to be used to transform a part from its initial state to the final form according to the design specifications. It is a bridge between product design and product manufacturing. The activities of process planning include understanding the part specifications or product design data, selection of job material and tool, setup planning, sequencing the operations within a setup, determination of process parameters for each operation, and generation of process sheets. This paper outlines a method to develop a generative computer-aided process planning system for axisymmetric components for a job shop environment. A decision support system is used to perform semi-structured tasks such as setup planning and establishing precedence relationship among various operations.  相似文献   

8.
Annotated bibliography on computer-aided process planning   总被引:3,自引:1,他引:2  
Computer-aided process planning (CAPP) has attracted great research interest for the last two decades and a large volume of material has been published on the subject. With the introduction of contemporary manufacturing philosophies such as concurrent engineering, agile manufacturing and the like, the research in process planning has been gradually transformed into an inter-disciplinary and multi-faceted problem domain. By compiling, classifying and annotating a sample of articles published in the last few years, the paper provides a logical organisation of the literature on process planning. Some rudimentary analysis is included based on observations made during the compilation process.  相似文献   

9.
Due to the unexpected, fast, and constant changes of market requirements and the hypercompetency, robust manufacturing systems are needed that adjust easily to operational variability and the customized product supply. The simply substitution of components, software, hardware, and/or their adaptation by parameters resetting are an attractive option to face this challenge. Short product life cycles are an undeniable consequence and evidence of this. For this reason, to develop products or services profitably in the product manufacturing field, it is common to use the product family concept, which involves sharing components, functional features, and manufacturing process, both to make a cheaper product development process and to obtain customized products. A new generation of manufacturing systems that deploy characteristics such as adaptability and flexibility responding to the market dynamics called reconfigurable manufacturing systems (RMS) are required by market according to manufacturing experts. The manufacturing systems with modular architecture are the best way to meet flexible and adaptable RMSs because they allow reconfiguration by a simple module substitution or by resetting module operation parameters. This paper presents a design methodology developed to obtain modular RMS. The method integrates the utilization of modular architecture principles, selection algorithms (analytical hierarchical process), clustering algorithms (average linkage clustering algorithm), family product features and functional system analysis in the classical product design process. The methodology proposed allows defining the most adequate modular system architecture and the modular definition of the reconfiguration variables that are needed to reach the flexibility required. A real study case about a heat exchanger assembly machine is presented where this methodology is applied in order to present an evidence of its usefulness.  相似文献   

10.
To produce an electronic product, both assembly operations and machining operations are required in the process plan. In most cases, the assembly operations and machining operations need to be combined in a continued order with an integrated sequence. This is different from the traditional process planning approaches in which machining operations and assembly operations are separated as two independent tasks with no interactions. For an electronic product, the two types of operations and the associated costs may affect each other in an interactive way. Therefore, the sequence planning of assembly operations and machining operations must be analyzed with an integrated model. In this research, a graph-based model is presented to represent the assembly and machining operations in an integrated model. The related operation cost functions are developed to evaluate the costs for the integrated assembly and machining sequences. The integrated sequence planning problem is solved using a genetic algorithm approach with an objective of lowest operation costs. As a result, the assembly operations and machining operations can be planned in an integrated sequence suitable for producing electronic products. The result shows that the developed method using the genetic algorithm approach is efficient for solving the integrated sequence planning problem. Example products are demonstrated and discussed.  相似文献   

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