A CONFIGURATION SYSTEM FOR FASTENER DESIGN（AN APPROACH TOWARDS COMPUTER AIDED CONCEPTUAL DESIGN）

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A manufacturing-oriented approach for multi-platforming product family design with modified genetic algorithm

With highly fragmented market and increased competition, platform-based product family design has been recognized as an effective method to construct a product line that satisfies diverse customer’s demands while aiming to keep design and production cost-effective. The success of the resulting product family often relies on properly resolving the inherent tradeoff between commonality across the family and performance loss. In this paper, a systematic multi-platforming product family approach is proposed to design a scale-based product family. In the light of the basic premise that increased commonality implies enhanced manufacturing efficiency, we present an effective platform decision strategy to quantify family design configuration using a commonality index that couples design varieties with production variation. Meanwhile, unlike many existing methods that assume a single given platform configuration, the proposed method addresses the multi-platforming configuration across the family, and can generate alternative product family solutions with different levels of commonality. A modified genetic algorithm is developed to solve the aggregated multiobjective optimization problem and an industrial example of a planetary gear train for drills is given to demonstrate the proposed method.     

Tolerance analysis based on Monte Carlo simulation: a case of an automotive water pump design optimization

Successful products are those presenting the highest quality at a fair cost. Although different approaches can be used to define the concept of quality, functional reliability is always a major requirement, due to implications such as safety and user losses regarding maintenance expenses, and product availability. Intelligent designs are robust and result in a fair cost. Robust designs are those insensitive to sources of variation occurring during the product life, keeping their performance under variable use conditions, like thermal and stress effects. The robustness approach is a function of two main design criteria: low complexity and tolerance design. Design for manufacture and assembly is closely related to decreasing complexity. Tolerance design is a tool in which the unavoidable manufacturing variations are considered during product development. This work presents a proposal for an intelligent design in an actual application by considering design simplification through the reduction of parts for an automotive water pump. The tolerance analysis is performed by means of a powerful statistical approach—a Monte Carlo simulation—in which process behavior is randomly simulated representing a high production volume. Additionally, service thermal effects are also contemplated, and assembly tests are proposed for automatic rejection of non-conforming parts, assuring high reliability and full compliance with functional requirements. This is an example of integrated design–manufacturing work aiming at both cost saving and improved reliability.

     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.     

Function and process modeling for integrated product and manufacturing system platforms

Manufacturing companies face increasingly tougher individual customer requirements that force them to revise conceptual solutions for the redesigning of products. This situation limits the reuse of ready-made components and requires physical changes to the manufacturing system. In these settings, platforms must be prepared with greater flexibility to allow development over time. The corresponding platform models need to include conceptual considerations for products and manufacturing systems. The literature advocates functional modeling to capture these considerations but applies it separately to either the product domain or to the manufacturing domain. Further, its relationship to manufacturing processes is not expounded. Thus, functional modeling falls short of its potential to facilitate the integrated development of products and manufacturing systems.This paper puts forth an integrated platform model using functional modeling to capture the conceptual considerations for products and manufacturing systems together with the manufacturing processes. The model is tested for consistency and then illustrated by studying a real case example from the automotive industry modeled according to the approach suggested. The example shows that the model facilitates an understanding of the design of products and their manufacturing systems, including functions shared across domains and across lifecycle phases. Thus, the model is proposed for the conceptual phase of designing, aimed at reusing and redesigning components, machinery, manufacturing processes and design solutions.     

面向配置设计的产品功构建模方法

针对产品配置设计过程中存在的客户和设计者之间交互语义一致性以及功能域与结构域之间映射等问题,鉴于事物特性表技术,通过规定产品信息的数据格式使产品数据能在不同系统之间进行交流,提出了基于事物特性表的产品需求信息元方法,构造了面向配置设计的功构模型;着重探讨了模型的优化算法及基于功构模型的产品配置设计流程;最后给出了面向配置设计的产品功构建模应用实例．     

A new DFM approach to combine machining and additive manufacturing

Design for manufacturing (DFM) approaches aim to integrate manufacturability aspects during the design stage. Most of DFM approaches usually consider only one manufacturing process, but product competitiveness may be improved by designing hybrid modular products, in which products are seen as 3-D puzzles with modules realized individually by the best manufacturing process and further gathered. A new DFM system is created in order to give quantitative information during the product design stage of which modules will benefit in being machined and which ones will advantageously be realized by an additive process (such as Selective Laser Sintering or laser deposition). A methodology for a manufacturability evaluation in case of a subtractive or an additive manufacturing process is developed and implemented in a CAD software. Tests are carried out on industrial products from automotive industry.     

Design parameterization and tool integration for CAD-based mechanism optimization

This paper presents an open and integrated tool environment that enables engineers to effectively search, in a CAD solid model form, for a mechanism design with optimal kinematic and dynamic performance. In order to demonstrate the feasibility of such an environment, design parameterization that supports capturing design intents in product solid models must be available, and advanced modeling, simulation, and optimization technologies implemented in engineering software tools must be incorporated. In this paper, the design parameterization capabilities developed previously have been applied to support design optimization of engineering products, including a High Mobility Multi-purpose Wheeled Vehicle (HMMWV). In the proposed environment, Pro/ENGINEER and SolidWorks are supported for product model representation, DADS (Dynamic Analysis and Design System) is employed for dynamic simulation of mechanical systems including ground vehicles, and DOT (Design Optimization Tool) is included for a batch mode design optimization. In addition to the commercial tools, a number of software modules have been implemented to support the integration; e.g., interface modules for data retrieval, and model update modules for updating CAD and simulation models in accordance with design changes. Note that in this research, the overall finite difference method has been adopted to support design sensitivity analysis.     

Design Verification for Bent Sheet Metal Parts: A Graphs Approach

Design for manufacturing requires the flexible verification and optimization of design features with regard to the suitability to the planned production methods. The automatic identification and generation of a suitable process plan for large scale bent sheet metal parts would provide a tool that would allow efficient feedback in the design phase. In this paper, a number of problem-size reduction methods are proposed to bring automatic manufacturability verification a few steps closer to reality. The scale of the reformulated combinatorial problems is illustrated, indicating the suitability for solution by means of known search algorithms.     

A concurrent engineering constraint-based system

This research article demonstrates the use of constraint networks for modelling the knowledge which is necessary for concurrent product and process design. A knowledge-based constraint network system has been developed to maintain design consistency and to support the selection of appropriate manufacturing processes according to pre-defined constraints. A number of constraints related to existing manufacturing facilities and expertise are formulated and modelled using the rules of the knowledge-based toolkit. These constraints are implemented to identify the appropriate machining processes and to show the feasibility of a product's design as it progresses and before making the final prototype. The combination of design and manufacturing constraints enables designers to examine whether the designed part can be manufactured with the available manufacturing facilities.     

Configuration products and quotients in geometric modeling

The six-dimensional space SE(3) is traditionally associated with the space of configurations of a rigid solid (a subset of Euclidean three-dimensional space R³). But a solid itself can be also considered to be a set of configurations, and therefore a subset of SE(3). This observation removes the artificial distinction between shapes and their configurations, and allows formulation and solution of a large class of problems in mechanical design and manufacturing. In particular, the configuration product of two subsets of configuration space is the set of all configurations obtained when one of the sets is transformed by all configurations of the other. The usual definitions of various sweeps, Minkowski sum, and other motion related operations are then realized as projections of the configuration product into R³. Similarly, the dual operation of configuration quotient subsumes the more common operations of unsweep and Minkowski difference. We identify the formal properties of these operations that are instrumental in formulating and solving both direct and inverse problems in computer aided design and manufacturing. Finally, we show that all required computations may be approximated using a fast parallel sampling method on a GPU and provide error estimates for the approximation.