A dimensioning and tolerancing methodology for concurrent engineering applications I: problem representation

This paper is the first of two which present a methodology for determining the dimensional specifications of all the component parts and sub-assemblies of a product according to their dimensional requirements. To achieve this goal, two major steps are followed, each of which is described in a paper. In the first paper, all relationships necessary for finding the values of dimensions and tolerances are represented in a matrix form, known as a Dimensional Requirements/Dimensions (DR/D) matrix. In the second paper, the values of individual dimensions and tolerances are determined by applying a comprehensive solution strategy to satisfy all the relationships represented in the DR/D matrix. The methodology is interactive and suitable for use in a concurrent engineering (CE) environment. The graphical tool presented in this paper will assist a CE team in visualizing the overall D&T problem and foreseeing the ramifications of decisions regarding the selection of dimensions and tolerances. This will assist the CE team to systematically determine all the controllable variables, such as dimensions, tolerances, and manufacturing processes.     

CONCURRENT PRODUCT PORTFOLIO PLANNING AND MIXED PRODUCT ASSEMBLY LINE BALANCING

Reconfigurable products and manufacturing systems have enabled manufacturers to provide "cost effective" variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variants to offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.     

A methodology for extracting dimensional requirements for a product from customer needs

Dimensional requirements greatly influence the performance of a product, yet there is no systematic process for determining them. Often as a result, some dimensional requirements are overlooked at the design stage, which forces costly changes at a latter stage of product realisation (such as manufacture and assembly). A methodology is presented here which will assist extracting the dimensional requirements for a product from the customers needs. It is suitable for use in a Concurrent Engineering (CE) environment and incorporates some of the existing methodologies used in CE viz. quality function deployment, tree diagrams (The New Seven Tools) and Pughs concept selection method. It provides a systematic way of determining the dimensional requirements of a product and establishes clear links between customer needs and the dimensional requirements. These links will help the CE team to understand the product requirements and how they are to be satisfied through the dimensional aspects of a design.     

基于装配要求优化选择零件公差

在设计图纸上标注尺寸和公差是产品设计的两个重要阶段,为了提高零件的互换性,降低成本和废品率,文章提出一种优化装配零件公差的新方法。该方法根据初始所分配的公差和装配要求,建立一个含多个变量和多个约束条件的优化数学模型。通过规划求解来确定各零件的尺寸公差,使所有的装配要求都得到满足,且方法简单,适合所有的使用者。     

Automatic design of machining fixtures: Conceptual design

Fixtures are used in many manufacturing operations. Owing to the great variety of parts and manufacturing operations, parts may have different sets of fixturing requirements and call for different design strategies. Although there are numerous possibilities for fixture designs, a few basic configurations are clearly identifiable. Based on the belief that it would be more promising to develop one design strategy for each type of fixture than to attempt to develop a general strategy for all types of fixtures, a three-stage design process has been proposed for automatic design of fixtures: conceptual, configuration, and detail design. This paper focuses on the conceptual design stage. A methodology is presented by which the part shape, part features, and cutting force field are analysed to generate conceptual designs of fixtures.     

A strategy for solving coupled functional equations

The designer, in order to guarantee the function of the product, firstly identifies the functional requirements and then establishes the relationships between each functional requirement and dimension. These relationships are known as functional equations. A body of literature proposing a number of strategies has been published for the solving of these independent functional equations but there has been less interest in the solving of coupled functional equations, which require an extra strategy to determine an optimum solution order. In this paper a strategy suitable for computer application and which can be used for generating an optimum solution order for a group of coupled functional equations is proposed. This should fill the need for a means of identifying this presently overlooked aspect of dimensioning and tolerancing and, while determining the solution of a group of coupled functional equations, take into account a number of factors such as the number of functional equations involved and the number of independent and coupled dimensions in each functional equation. This revised version was published online in October 2004 with a correction to the issue number.     

Constraint-based simulated annealing (CBSA) approach to solve the disassembly scheduling problem

Globalization, coupled with environmental requirements, has spearheaded new levels of requirements for product end-of-life, the last phase of product lifecycle management especially for product remanufacturing and recycling which involves product disassembly to retrieve the desired parts and subassemblies. Selection of optimal disassembly schedule is a major challenge for remanufacturing and recycling industries as it directly affects the inventory of the manufacturing unit and influences the final product cost. This paper proposes a constraint-based simulated annealing (CBSA) algorithm methodology to determine the ordering and disassembly schedule to minimize inventory level for products with general assembly product structure, i.e., taking into consideration part commonalities. The proposed CBSA algorithm uses the constraint-based genetic operators integrated with the simulated annealing (SA) approach that makes the algorithm more search exploratory (guarantee the optimal or near-optimal solution) and converge efficiently to the optimal solutions (less time-consuming). The proposed algorithm has higher likelihood of avoiding local optima as compared with standard SA and genetic algorithms. This is achieved by exploring a population of points, rather than a single point in the solution space. The proposed methodology is validated using a numerical case study for disassembly scheduling problem with part commonality.     

敏捷制造环境下装配产品变形设计方法

为了获得满足顾客个性化需求的装配产品设计方案 ,提出了通过修改现有成熟零件的设计的变形设计方法。建立了描述装配产品构成零件之间配合关系的模型并识别出反映装配产品构成零部件之间尺寸关联关系的约束组。每个约束组的变形设计过程被归结为一个混合整数线性规划 (MILP)问题 ,而所有约束组的MILP问题的组合求解过程则反映了装配产品的变形设计优化过程。开发了软件原型系统并进行了仿真 ,仿真结果表明该方法能够在合理的时间内获得新的、可行的装配产品设计方案 ,可以作为装配产品设计方案的生成器 ,以缓解顾客个性化需求对产品设计带来的压力     

630吨摩擦螺旋压力机的冲顶分析与研究

本文以产品质量和工艺过程为基本要求,通过对工作机构的能量及螺杆螺纹头数的分析,找出解决 ６３０ 吨摩擦螺旋压力机冲顶问题的方法—螺杆螺纹头数由四头改为两头。     

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review

Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations, which ultimately result in out-of-tolerance parts and products. Once in the ramp-up stage of production, SOVA will be able to compare predicted misalignments with actual measurements to determine the degree of mismatch in the assemblies, diagnose the root causes of errors, isolate the sources from other assembly steps, and then, on the basis of the SOVA model and product measurements, recommend solutions.     

Automated dimensional inspection planning using the combination of laser scanner and tactile probe

Combining multiple sensors on CMMs (Coordinate Measuring Machines) is useful to fulfil the increasing requirements on both complexity and accuracy in dimensional metrology. Yet, the methodology to plan measurement strategies for systems combining different types of sensors is still a major challenge. Such planning is commonly done in an interactive way. This paper presents a methodology which can create inspection plans automatically for CMM inspection combining a touch trigger probe and a laser scanner. The inspection features are specified based on the extracted geometry features and the associated PMI (Product and Manufacturing Information) items from a CAD model. A knowledge based sensor selection method is applied to choose the suited sensor for each inspection feature. For touch trigger measurements, the sampling strategy considers the measurement uncertainty calculated by simulation. A geometry-guide method is developed for collision-free probing path generation. For laser scan measurements, the required view angles and positions of the laser scanner are determined iteratively, based on which the scan path is generated automatically. The proposed methodology is tested for several cases and validated by measurement experiments. The methodology provides suited planning results and can be used for automated dimensional inspection, i.e. Computer Aided Quality Control (CAQC).     

Particle swarm optimization for minimizing assembly variation in selective assembly

Quality of a product is based on the quality of the mating parts. When the parts are assembled interchangeably, the assembly variation will be the sum of the component tolerances. If the assembly variation is to be less than the sum of the component tolerances, selective assembly is the only solution. In conventional selective assembly, the corresponding selective groups are assembled. In this paper, selective group combinations for assembling the mating parts is obtained using particle swarm optimization (PSO). The combination obtained has resulted in an appreciable reduction in assembly variation. The proposed algorithm has been demonstrated for a linear assembly, which consists of three components having equal dimensional distributions. The assembly variation obtained by interchangeable assembly is 36 μm. By implementing the proposed method, the assembly variations are reduced from 36 to 7.2 μm. However, this algorithm can be extended for assemblies with more number of components and with different dimensional distributions.     

STEP-Based Multiview Integrated Product Modelling for Concurrent Engineering

The demand for high-quality and low-cost products with a short development time for the dynamic global market has forced researchers and industries to focus on various effective product development strategies. Product modelling has been recognised as one of the key factors in determining the success of various product development strategies and for industrial competitiveness now and in the future. This paper proposes a methodology that represents multiview integrated product modelling based on the outcome of a research project on ISO 10303 STEP. The methodology consists of the architecture and information requirements for an integrated product model and a mapping mechanism for the multiview operations of the model, which support product development in a concurrent engineering environment. This methodology will facilitate further research in developing sophisticated product modelling for concurrent product development. ID="A1"Correspondance and offprint requests to: Dr K. S. Chin, Department of Manufacturing Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China, E-mail mekschin@cityu.edu.hk     

Effect of uncertainties on substructure coupling: Modelling and reduction strategies

Different strategies for modelling and reducing the effect of uncertainties on the dynamic behaviour of coupled structures are discussed in this paper. In assembled structures, each component satisfies specifications about material properties and dimensional tolerances. Variability of design specifications within the tolerance field may affect the dynamic behaviour of the assembled structure more than that of any individual component substructure. Among modelling strategies, non-predictive techniques such as post-processing of data from a set of randomly assembled structures and analysis of sensitivities to uncertain variables are considered. However, emphasis is placed on a less trivial yet simple strategy such as the use of design of experiments to fit a regression model. Different reduction strategies are considered according to whether small design changes (even revised tolerance allocation) are still possible or not. In the latter case, selective assembly is extended to problems where the performance requirement is not the clearance between two parts, but a prescribed dynamic behaviour.     

高性能精密制造

高性能制造是高端装备和产品的关键零部件以性能精准保证为目标的几何和性能一体化制造,体现了由几何尺寸及公差要求为主的传统制造向高性能要求为主的先进制造的跃升。从制造的现状、需求和发展趋势出发,阐明了高性能零件的内涵、高性能制造的特点、面临的问题及其分类体系,并结合实例给予了深入分析和说明,为高端装备中一大批关键零部件的精密制造难题提供了可行的解决策略和途径。     

Tolerance design of mechanical assembly using NSGA II and finite element analysis

The technological and financial limitations in the manufacturing process are the reason for non-achievability of nominal dimension. Therefore, tolerance allocation is of significant importance for assembly. Conventional tolerance allocation methods are limited by an assumption that all parts are rigid. Every mechanical assembly consists of at least one or more flexible parts which undergo significant deformation due to inertia effect. Finite element analysis is used to determine the deformation of components in an assembly. Therefore, integration of statistical tolerance design with finite element analysis will guarantee that the optimal tolerance values of various components of the assembly obtained as end product of the tolerance design will remain within tolerance variation. Then the product can function as intended under a wide range of operating conditions for the duration of its life. In this paper, tolerance design of a piston cylinder assembly is done to demonstrate the proposed methodology.     

Efficient management of production-inventory system in a multi-item manufacturing facility: MTS vs. MTO

Suppliers produce a variety of products to serve both large and small customer orders with unreliable demand information. Furthermore, suppliers also face customer pressure to improve quality, lower cost, and reduce delivery delay. These conflicting objectives lead firms to use both make-to-stock and make-to-order production strategies together. These manufacturing strategies were known to be competing policies and in some cases the choice depends on characteristics of the product. In this study, the firms that manufactured multiple-item types are considered to be free to choose either production policy for each product type (no product-specific requirements are present). Then, using the order-arrival characteristics and cost parameters for each product type, the firm wants to decide which production/scheduling policy to use for each product type. Two production policy (MTS vs MTO) and two scheduling strategy (FIFO vs cyclic) are considered in this study. The analysis and numerical study show that there is no dominant strategy neither for production policy, nor product scheduling policy.     

精密模具零件的高速加工技术及策略

分析了高速加工的机床功能部件、高速加工刀具刀柄及安装要求,从切削走刀方式及加工顺序的选择等方面,论述了精密模具零件高速加工工艺技术及策略。通过实例,总结了高速加工中应注意的实际问题,对解决精密模具工作零件及复杂零件的高效加工具有一定的实际意义。     

Rule-based production planning in flexible manufacturing systems

Production planning in flexible manufacturing may require the solution of a large-scale discrete-event dynamic stochastic optimization problem, due to the complexity of the system to be optimized, and to the occurrence of discrete events (new orders and hard failures). The production planning problem is here approached for a multistage multipart-type manufacturing shop, where each work cell can share its processing time among the different types of parts. The solution of this problem is obtained by an open-loop-feedback control strategy, updated each time a new event occurs. At each event time, two coupled problems are solved: 1) a product-order scheduling problem, conditioned on estimated values of the production capacities of all component work cells; and 2) a production-capacity planning problem, conditioned on predefined sequences of the product orders to be processed. In particular, the article aims at defining a production planning procedure that integrates both analytical tools, derived from mathematical programming, and knowledge-based rules, coming from experience. The objective is to formulate a hybrid (knowledge-based/analytical) planning architecture, and to analyze its use for multicell multipart-type manufacturing systems.