資源目錄里展示的全都有預(yù)覽可以查看的噢，，下載就有,,請放心下載，原稿可自行編輯修改=【QQ：11970985 可咨詢交流】====================喜歡就充值下載吧。。。資源目錄里展示的全都有，，下載后全都有,,請放心下載，原稿可自行編輯修改=【QQ：197216396 可咨詢交流】==================== A review and analysis of current computer-aided fixture design approaches Iain Boyle, Yiming Rong, David C. Brown Keywords: Computer-aided fixture design Fixture design Fixture planning Fixture verification Setup planning Unit design ABSTRACT A key characteristic of the modern market place is the consumer demand for variety. To respond effectively to this demand, manufacturers need to ensure that their manufacturing practices are sufficiently flexible to allow them to achieve rapid product development. Fixturing, which involves using fixtures to secure work pieces during machining so that they can be transformed into parts that meet required design specifications, is a significant contributing factor towards achieving manufacturing flexibility. To enable flexible fixturing, considerable levels of research effort have been devoted to supporting the process of fixture design through the development of computer-aided fixture design (CAFD) tools and approaches. This paper contains a review of these research efforts. Over seventy-five CAFD tools and approaches are reviewed in terms of the fixture design phases they support and the underlying technology upon which they are based. The primary conclusion of the review is that while significant advances have been made in supporting fixture design, there are primarily two research issues that require further effort. The first of these is that current CAFD research is segmented in nature and there remains a need to provide more cohesive fixture design support. Secondly, a greater focus is required on supporting the detailed design of a fixture’s physical structure. 2010 Elsevier Ltd. All rights reserved. Contents 1. Introduction………………………………………………………………………………………2 2. Fixture design…………………………………………………………………………………….2 3. Current CAFD approaches……………………………………………………………………….4 3.1 Setup planning…………………………………………………………………………….4 3.1.1 Approaches to setup planning……………………………………………………...4 3.2 Fixture planning…………………………………………………………………………..4 3.2.1 Approaches to defining the fixturing requirement…………………………………6 3.2.2 Approaches to non-optimized layout planning…………………………………….6 3.2.3 Approaches to layout planning optimization………………………………………6 3.3 Unit design………………………………………………………………………………...7 3.3.1 Approaches to conceptual unit design……………………………………………..7 3.3.2 Approaches to detailed unit design………………………………………………...7 3.4 Verification………………………………………………………………………………..8 3.4.1 Approaches to constraining requirements verification…………………………….8 3.4.2 Approaches to tolerance requirements verification………………………………..8 3.4.3 Approaches to collision detection requirements verification………………………8 3.4.4 Approaches to usability and affordability requirements verification………………9 3.5 Representation of fixturing information…………………………………………………..9 4. An analysis of CAFD research…………………………………………………………………...9 4.1 The segmented nature of CAFD research ………………………………………………...9 4.2 Effectively supporting unit design ………………………………………………………10 4.3 Comprehensively formulating the ?xturing requirement………………………………..10 4.4 Validating CAFD research outputs……………………………………………………....10 5. Conclusion…………………………………………………………………………………...…10 References…………………………………………………………………………………………10 1. Introduction A key concern for manufacturing companies is developing the ability to design and produce a variety of high quality products within short timeframes. Quick release of a new product into the market place, ahead of any competitors, is a crucial factor in being able to secure a higher percentage of the market place and increased profit margin. As a result of the consumer desire for variety, batch production of products is now more the norm than mass production, which has resulted in the need for manufacturers to develop flexible manufacturing practices to achieve a rapid turnaround in product development. A number of factors contribute to an organization’s ability to achieve flexible manufacturing, one of which is the use of fixtures during production in which work pieces go through a number of machining operations to produce individual parts which are subsequently assembled into products. Fixtures are used to rapidly, accurately, and securely position work pieces during machining such that all machined parts fall within the design specifications for that part. This accuracy facilitates the interchangeability of parts that is prevalent in much of modern manufacturing where many different products feature common parts. The costs associated with fixturing can account for 10–20% of the total cost of a manufacturing system [1]. These costs relate not only to fixture manufacture, assembly, and operation, but also to their design. Hence there are significant benefits to be reaped by reducing the design costs associated with fixturing and two approaches have been adopted in pursuit of this aim. One has concentrated on developing flexible fixturing systems, such as the use of phase-changing materials to hold work pieces in place [2] and the development of commercial modular fixture systems. However, the significant limitation of the flexible fixturing mantra is that it does not address the difficulty of designing fixtures. To combat this problem, a second research approach has been to develop computer-aided fixture design (CAFD) systems that support and simplify the fixture design process and it is this research that is reviewed within this paper. Section 2 describes the principal phases of and the wide variety of requirements driving the fixture design process. Subsequently in Section 3 an overview of research efforts that have focused upon the development of techniques and tools for supporting these individual phases of the design process is provided. Section 4 critiques these efforts to identify current gaps in CAFD research, and finally the paper concludes by offering some potential directions for future CAFD research. Before proceeding, it is worth noting that there have been previous reviews of fixturing research, most recently Bi and Zhang [1] and Pehlivan and Summers [3]. Bi and Zhang, while providing some details on CAFD research, tend to focus upon the development of flexible fixturing systems, and Pehlivan and Summers focus upon information integration within fixture design. The value of this paper is that it provides an in-depth review and critique of current CAFD techniques and tools and how they provide support across the entire fixture design process. 2. Fixture design This section outlines the main features of fixtures and more pertinently of the fixture design process against which research efforts will be reviewed and critiqued in Sections 3 and 4, respectively. Physically a fixture consists of devices that support and clamp a work piece [4,5]. Fig. 1 represents a typical example of a fixture in which the work piece rests on locators that accurately locate it. Clamps hold the work piece against the locators during machining thus securing the work piece’s location. The locating units themselves consist of the locator supporting unit and the locator that contacts the work piece. The clamping units consist of a clamp supporting unit and a clamp that contacts the work piece and exerts a clamping force to restrain it. Typically the design process by which such fixtures are created has four phases: setup planning, fixture planning, unit design, and verification, as illustrated in Fig. 2 , which is adapted from Kang et al. [6]. During setup planning work piece and machining information is analyzed to determine the number of setups required to perform all necessary machining operations and the appropriate locating datums for each setup. A setup represents the combination of processes that can be performed on a work piece without having to alter the position or orientation of the work piece manually. To generate a fixture for each setup the fixture planning, unit design, and verification phases are executed. During fixture planning, the fixturing requirements for a setup are generated and the layout plan, which represents the first step towards a solution to these requirements is generated. This layout plan details the work piece surfaces with which the fixture’s locating and clamping units will establish contact, together with the surface positions of the locating and clamping points. The number and position of locating points must be such that a work piece’s six degrees of freedom (Fig. 3 ) are adequately constrained during machining [7] and there are a variety of conceptual locating point layouts that can facilitate this, such as the 3-2-1 locating principle [4]. In the third phase, suitable unit designs (i.e., the locating and clamping units) are generated and the fixture is subsequently tested during the verification phase to ensure that it satisfies the fixturing requirements driving the design process. It is worth noting that verification of setups and fixture plans can take place as they are generated and prior to unit design. Fixturing requirements, which although not shown in Kang et al.[6] are typically generated during the fixture planning phase, can be grouped into six classes ( Table 1 ). The ‘‘physical’’ requirements class is the most basic and relates to ensuring the fixture can physically support the work piece. The ‘‘tolerance’’ requirements relate to ensuring that the locating tolerances are sufficient to locate the work piece accurately and similarly the‘‘constraining’’ requirements focus on maintaining this accuracy as the work piece and fixture are subjected to machining forces. The ‘‘a(chǎn)ffordability’’ requirements relate to ensuring the fixture represents value, for example in terms of material, operating, and assembly/disassembly costs. The ‘‘collision detection’’ requirements focus upon ensuring that the fixture does not collide with the machining path, the work piece, or indeed itself. The ‘‘usability’’ requirements relate to fixture ergonomics and include for example needs related to ensuring that a fixture features error-proofing to prevent incorrect insertion of a work piece, and chip shedding, where the fixture assists in the removal of machined chips from the work piece. As with many design situations, the conflicting nature of these requirements is problematic. For example a heavy fixture can be advantageous in terms of stability but can adversely affect cost (due to increased material costs) and usability (because the increased weight may hinder manual handling). Such conflicts add to the complexity of fixture design and contribute to the need for the CAFD research reviewed in Section 3. Table 1 Fixturing requirements. Generic requirement Abstract sub-requirement examples Physical ● The fixture must be physically capable of accommodating the work piece geometry and weight. ● The fixture must allow access to the work piece features to be machined. Tolerance ● The fixture locating tolerances should be sufficient to satisfy part design tolerances. Constraining ● The fixture shall ensure work piece stability (i.e., ensure that work piece force and moment equilibrium are maintained). ● The fixture shall ensure that the fixture/work piece stiffness is sufficient to prevent deformation from occurring that could result in design tolerances not being achieved. Affordability ● The fixture cost shall not exceed desired levels. ● The fixture assembly/disassembly times shall not exceed desired levels. ● The fixture operation time shall not exceed desired levels. Collision Prevention ● The fixture shall not cause tool path–fixture collisions to occur. ● The fixture shall cause work piece–fixture collisions to occur (other than at the designated locating and clamping positions). ● The fixture shall not cause fixture–fixture collisions to occur (other than at the designated fixture component connection points). Usability ● The fixture weight shall not exceed desired levels. ●The fixture shall not cause surface damage at the work piece/fixture interface. ● The fixture shall provide tool guidance to designated work piece features. ● The fixture shall ensure error-proofing (i.e., the fixture should prevent incorrect insertion of the work piece into the fixture). ● The fixture shall facilitate chip shedding (i.e., the fixture should provide a means for allowing machined chips to flow away from the work piece and fixture). 3. Current CAFD approaches This section describes current CAFD research efforts, focusing on the manner in which they support the four phases of fixture design. Table 2 provides a summary of research efforts based upon the design phases they support, the fixture requirements they seek to address (boldtext highlights that the requirement is addressed to a significant degree of depth, whilst normal text that the degree of depth is lesser in nature), and the underlying technology upon which they are primarily based. Sections 3.1–3.4 describes different approaches for supporting setup planning, fixture planning, unit design, and verification, respectively. In addition, Section 3.5 discusses CAFD research efforts with regard to representing fixturing information. 3.1. Setup planning Setup planning involves the identification of machining setups, where an individual setup defines the features that can be machined on a work piece without having to alter the position or orientation of the work piece manually. Thereafter, the remaining phases of the design process focus on developing individual fixtures for each setup that secure the work piece. From a fixturing viewpoint, the key outputs from the setup planning stage are the identification of each required setup and the locating datums (i.e., the primary surfaces that will be used to locate the work piece in the fixture). The key task within setup planning is the grouping or clustering of features that can be machined within a single setup. Machining features can be defined as the volume swept by a cutting tool, and typical examples include holes, slots, surfaces, and pockets [8]. Clustering of these features into individual setups is dependent upon a number of factors (including the tolerance dependencies between features, the capability of the machine tools that will be used to create the features, the direction of the cutting tool approach, and the feature machining precedence order), and a number of techniques have been developed to support setup planning. Graph theory and heuristic reasoning are the most common techniques used to support setup planning, although matrix based techniques and neural networks have also been employed. 3.1.1. Approaches to setup planning The use of graph theory to determine and represent setups has been a particularly popular approach [9–11]. Graphs consist of two sets of elements: vertices, which represent work piece features, and edges, which represent the relationships that exist between features and drive setup identification. Their nature can vary, for example in Sarma and Wright [9] consideration of feature machining precedence relationships is prominent, whereas Huang and Zhang [10] focus upon the tolerance relationships that exist between features. Given that these edges can be weighted in accordance with the tolerance magnitudes, this graph approach can also facilitate the identification of setups that can minimize tolerance stack up errors between setups through the grouping of tight tolerances. However, this can prove problematic given the difficulty of comparing the magnitude of different tolerance types to each other thus Huang [12] includes the use of tolerance factors [13] as a means of facilitating such comparisons, which are refined and extended by Huang and Liu [14] to cater for a greater variety of tolerance types and the case of multiple tolerance requirements being associated with the same set of features. While some methods use undirected graphs to assist setup identification [11] , Yao et al. [15] , Zhang and Lin [16] , and Zhang et al. [17] use directed graphs that facilitate the determination and explicit representation of which features should be used as locating datums ( Fig. 4 ) in addition to setup identification and sequencing. Also, Yao et al. refine the identified setups through consideration of available machine tool capability in a two stage setup planning process. Experiential knowledge, in the form of heuristic reasoning, has also been used to assist setup planning. Its popularity stems from the fact that fixture design effectiveness has been considered to be dependent upon the experience of the fixture designer [18] .To support setup planning, such knowledge has typically been held in the form of empirically derived heuristic rules, although object oriented approaches have on occasion been adopted [19] . For example Gologlu [20] uses heuristic rules together with geometric reasoning to support feature clustering, feature machining precedence, and locating datum selection. Within such heuristic approaches, the focus tends to fall upon rules concerning the physical nature of features and machining processes used to create them [21, 22]. Although some techniques do include feature tolerance considerations [23], their depth of analysis can be less than that found within the graph based techniques [24]. Similarly, kinematic approaches [25] have been used to facilitate a deeper analysis of the impact of tool approach directions upon feature clustering than is typically achieved using rule-based approaches. However, it is worth noting that graph based approaches are often augmented with experiential rule-bases to increase their overall effectiveness [16] . Matrix based approaches have also been used to support setup planning, in which a matrix defining feature clusters is generated and subsequently refined. Ong et al. [26] determine a feature precedence matrix outlining the order in which features can be machined, which is then optimized against a number of cost indicators (such as machine tool cost, change over time, etc.) in a hybrid genetic algorithm-simulated annealing approach through consideration of dynamically changing machine tool capabilities. Hebbal and Mehta [27] generate an initial feature grouping matrix based upon the machine tool approach direction for each feature which is subsequently refined through the application of algorithms that consider locating faces and feature tolerances. Alternatively, the use of neural networks to support setup planning has also been investigated. Neural networks are interconnected networks of simple elements, where the interconnections are ‘‘learned’’ from a set of example data. Once educated, these networks can generate solutions for new problems fed into the network. Ming and Mak [28] use a neural network approach in which feature precedence, tool approach direction, and tolerance relationships are fed into a Kohonen self-organizing neural network to group operations for individual features into setups. 3.2. Fixture planning Fixture planning involves the comprehensive definition of a fixturing requirement in terms of the physical, tolerance, constraining, affordability, collision prevention, and usability requirements listed in Table 1 , and the creation of a fixture layout plan. The layout plan represents the first part of the fixture solution to these requirements, and specifies the position of the locating and clamping points on the work piece. Many layout planning approaches feature verification, particularly with regard to the constraining requirements. Typically this verification forms part of a feedback loop that seeks to optimize the layout plan with respect to these requirements. Techniques used to support fixture planning are now discussed with respect to fixture requirement definition, layout