浅谈提高工艺规程编制质量的途径

要全面提高工艺规程的编制质量 ,必须在管理、生产、技术等各个环节不断总结、不断改进 ,本文从 8个方面进行论述 ,这样 ,工艺规程的编制质量可提高到一个新水平 ,是保证产品技术经济效果的重要环节。     

产品全生命周期的工艺质量模型与并行制造方法研究

提出了现代质量观念下面向产品全生命周期的工艺质量的概念，建立了统一的工艺质量模型。该模型分为5个层次，即整体工艺质量层、质量特性层、工艺质量要素层、工艺决策参数层和集成信息平台层，由8个元组组成。在此基础上，探讨了基于工艺质量模型的并行制造实施方法，包括鉴别质量特性、配置工艺质量要素、工艺质量要素自动“聚焦”与协同决策、工艺质量评价，以及工艺质量改进5个步骤，有利于保证与改进产品全生命周期中的工艺质量和产品质量。     

发动机零件机械加工工艺规程工序图表文件改进

机械加工工艺规程图表文件是零件加工的具体指导文件,工艺规程的内容体现了总体工艺的水平,也决定了零件的加工质量。针对传统工艺规程存在的不足,改进了零件机械加工工艺规程图表文件,改进后的工艺规程内容全面、详细、唯一,能够保证现场零件加工方法的一致性及可靠性,解决零件加工质量过分依靠工人技能的问题,尤其在零件大批量生产过程中,优势更加明显。本文对新工艺规程每部分的格式、作用及编制方法进行了介绍。     

机械制造工艺质量的模糊评价

针对机械制造工艺质量中存在模糊不确定因素,应用模糊数学的概念和方法,建立了工艺质量的模糊评价模型,并具体对焊接工艺质量进行了模糊评价。结果表明,该方法具有较强的实用性和可操作性。     

基于质量功能展开的特钢产品多工艺方案增量设计方法

分析了特钢产品客户特殊需求的特点及其对传统模块化产品和工艺设计的影响.针对客户特殊需求的不断多样化和个性化的现状,基于质量功能展开原理,建立了特钢产品多工艺方案增量设计质量屋模型.在常规需求模块化设计的基础上,应用混合推理方法,实现了特钢产品客户特殊需求向工程属性和质量特性的映射.利用线性加权法对增量设计中各可行工艺方案进行了综合评价,并按照质量屋的瀑布式分解过程,将产品规划依次映射到工艺链规划、工序规划和质量规划中.该方法实现了应对动态变化的特钢生产环境的多工艺方案增量设,形成了有效的产品和工艺设计阶段的质量控制方案.     

机械制造工艺质量的模糊评价

针对机械制造工艺质量中存在模糊不确定因素 ,应用模糊数学的概念和方法 ,建立了工艺质量的模糊评价模型 ,并具体对焊接工艺质量进行了模糊评价。结果表明 ,该方法具有较强的实用性和可操作性     

一种U形金属波纹管成形工艺的研究

介绍了成形质量对U形金属波纹管疲劳寿命的影响,分析了各种成形工艺的特点及其成形质量,提出一种综合了几种成形工艺优点的新工艺,并通过简单的试验验证了新工艺对成形质量的改善.试验结果表明:新工艺能保证波形几何尺寸、改善波纹表面应力状态和粗糙度,可为波纹管的工艺设计提供参考.     

强化工艺纪律检查工作促进电器产品质量提高

1工艺纪律的执行是工艺管理的重要部分工艺纪律是为了更好地发挥工艺工作的作用,保证工艺的贯彻和实施所作的要求、规定和建立的规章制度。在工艺纪律的约束和控制下,能够促进各项工艺工作的科学化、程序化和规范化,因而工艺纪律的实施是工艺管理的一个重要组成部分。2工艺纪律是促进产品质量提高的重要保证现在不管是企业家,还是普通员工都深刻认识到：“质量是企业的生命”。那么如何提高产品的制造质量呢？人们在长期的生产斗争实践中,早已达成共识,实物质量是制造出来的。在影响产品质量的五大因素：“人、机、料、环、法”中,当…     

合金钢大方圆坯连铸机的工艺参数及设计特点

介绍了合金钢大方圆坯连铸机的工艺参数,采用的关键技术及设备设计特点。生产期间铸坯质量较好,该连铸机达到了国内先进水平。     

浅谈郊县工业企业的工艺整顿

上海市郊县工业特别是乡镇企业这几年发展很快,全国的情况也大体如此。乡镇企业有活力,产品转向快,但目前乡镇企业的产品一般质量不稳定、品种少、水平低,究其原因主要是工艺管理落后、工艺纪律松懈、工艺水平低。本文作者提出郊县工业企业必须进行工艺整顿和如何开展工艺整顿工作的意见,很及时,这对上海市乃至全国的乡镇企业都具有普遍意义。希望本文能引起乡镇企业中领导与技术人员的注意。     

QFD based optimal process quality planning

Process quality planning is an important activity of quality assurance. It aims to determine manufacturing processes with appropriate process capability to produce product characteristics. Quality function deployment (QFD) is a powerful tool for quality planning, which starts with identifying customer needs and ends with determining process plans. However, most studies on quality planning by QFD are limited to the product planning stage. The approach to process quality planning through QFD has rarely been discussed. This paper adopts the optimal QFD model and further develops it for process quality planning. By incorporating an empirical capability function for process elements, a composite process capability index (CCp) is presented to reflect the overall process quality level. Constraints including technical feasibility, correlations among process elements, project budget and development time are considered. A case study of the numerical control (NC) machining process quality for a thin-walled complex window frame of airship is given to illustrate how the proposed model can be effectively applied by process quality team to determine the optimal target level of process elements concerning with resources utilization .     

Towards the integration of process and production planning: an optimisation model for cutting parameters

This paper aims to contribute to process and production planning integration through the development of a new cutting parameters optimisation model. The developed model considers simultaneously the technology-related constraints and a shop floor constraint determined by the available time at each workstation. The latter, being a constraint related to the part machining time, is associated with the set of all elementary machining operations and implies the development of a new multi-operation optimisation model. In this approach, part machining time is a new variable for shop floor scheduling. Since the limiting factor of workstation available time at every scheduling date depends on the shop floor status, optimum part machining time can range from the time for minimum cost to the time for maximum production rate. The introduction of the available time in the optimisation process allows for the generation of improved schedules according to several performance measures. The proposed optimisation model is non-linear, uni-criterion and multi-variable. The search of the optimal solution is carried out using sequential quadratic programming.     

基于自适应蚁群算法的工艺路线优化

针对计算机辅助工艺设计中最优方案选择,提出一种以制造资源更换率最低为目标的自适应蚁群优化方法(Adaptive ant colony algorithm,AACA)。通过分析零件特征,根据精度要求对制造特征进行分解,提出加工元概念。加工元被定义为特定的制造特征、加工阶段、加工方法、制造资源、装夹位置的集合,工艺路线的确定被转换为对加工元的优化顺序安排问题。以制造特征之间的几何位置约束,各加工阶段的先后顺序约束为基本元素,构造加工元优选约束矩阵,给出基于优选约束矩阵的加工元优选原则。在加工元优先顺序约束和可用制造资源的共同约束下,将缩短加工周期、提高加工质量和降低加工成本的综合目标表达为制造资源更换率最低,进行优化目标函数的数学建模。指出加工元优化排序可类比旅行商问题,并选择AACA进行优化求解。实例分析表明提出的方法可以可靠和有效地得到符合生产实际的工艺路线。     

On-line integration of a process planning module with production scheduling

An approach to the on-line integration of process planning and production scheduling is reported. Based on a geometric modeller, a geometric analyser and a knowledge base, the process planner generates alternative process plans and provides automatic tool selection and calculation of the appropriate machining parameters. Time and cost estimations are input to the decision-making module in the production scheduling system that produces optimal scheduling decisions as well as a complete record of the actual state of the factory resources. An information flow, designed as a relational data model, maintains the interaction between the process planning and the production scheduling systems and provides the dynamic feedback to the process planner. Specific geometry features of the blank, the finished part and the cutting tools, and geometry features-based rules are stored in the database of a developed CAPP system by using a separate CAD interface. The integrated production planning and production scheduling system and the CAPP system were validated with rotational parts machining.     

具有重合加工体积的零件工序工艺规划

数控铣床、加工中心等自动化加工设备在一道工序中铣削零件多个表面时,要根据经济性优化每个工步的加工体 积,即进行底层的工艺规划。提出一种用于该类工序工艺规划的优化方法,该方法的特点是简单、实用、计算量小。     

五轴加工刀具路径生成的有效加工域规划方法

为复杂曲面五轴数控加工的刀具路径优化生成问题提出一种新的有效加工域规划方法。在对工件被加工表面和刀具的几何特征进行分析的基础上,得到在加工件表面上各处的最优可加工域宽度和刀具切削方向。通过采用离散采样和插值计算生成优化的有效加工域集,得到最优化的初始刀具路径;同时建立一种迭代搜索算法,用于解决最优加工域的选择规划问题。采用此算法生成优化的后续刀具路径,使得有效加工域最终完全覆盖整个被加工表面。给出的示例显示相对于传统的五轴加工刀具路径生成算法,有效加工域规划方法可以减少刀具路径的总长度和加工时间,得到更为优化的刀具路径和更好的工件表面质量,因此有效加工域规划方法可以被用于五轴数控加工实践以降低加工成本和提高产品质量。     

Integrated assembly and machining planning for electronic products using a genetic algorithm approach

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.     

Concurrent process tolerance design based on minimum product manufacturing cost and quality loss

In a concurrent design environment, a robust optimum method is presented to directly determine the process tolerances from multiple correlated critical tolerances in an assembly. With given distributions of multiple critical assembly dimensions, the Taguchi quadric quality loss function is first derived. The quality loss is then expressed as the function of pertinent process tolerances. A nonlinear optimal model is established to minimize the summation of manufacturing costs and product quality loss. An example illustrates the proposed model and the solution method .     

Development of multi-objective optimization models for electrochemical machining process

Owing to the complexity of electrochemical machining (ECM), it is very difficult to determine optimal cutting parameters for improving cutting performance. Hence, optimization of operating parameters is an important step in machining, particularly for unconventional machining procedures like ECM. A suitable selection of machining parameters for the ECM process relies heavily on the operator’s technologies and experience because of their numerous and diverse range. Machining parameters provided by the machine tool builder cannot meet the operator’s requirements. Since for an arbitrary desired machining time for a particular job, they do not provide the optimal conditions. To solve this task, multiple regression model and ANN model are developed as efficient approaches to determine the optimal machining parameters in ECM. In this paper, current, voltage, flow rate and gap are considered as machining parameters and metal removal rate and surface roughness are the objectives. Then by applying grey relational analysis, we calculate the grey grade for representing multi-objective model. Multiple regression model and ANN model have been developed to map the relationship between process parameters and objectives in terms of grade. The experimental data are divided into training and testing data. The predicted grade is found and then the percentage deviation between the experimental grade and predicted grade is calculated for each model. The average percentage deviations for the training data of the linear regression model, logarithmic transformation model, excluding interaction terms and ANN model, are 12.7, 25.6 and 3.03, respectively. The average percentage deviations for the testing data of the three models are 9.83, 26.8 and 2.67. While examining the average percentage deviations of three models, ANN is having less percentage deviation. So ANN is considered as the best prediction model. Based on the testing results of the artificial neural network, the operating parameters are optimized. Finally, ANOVA is used to identify the significance of multiple regression model and ANN model.     

A Fast and Reliable Tool for Estimates for Plastic Blowing Moulds

This work presents a procedure to evaluate machining costs of dies made on CNC machines. Our survey deals with companies manufacturing plastic blowing moulds, and it is limited to the unit parts, that is, to the estimation step without going to the detail of process planning. To do this, we developed a process that uses the techniques of the semi-analytical method. This method is based on the decomposition of the shape required to manufacture the cavities; every cavity is decomposed in the same way for machining complex features, in order to determine the machining process and machining time, and the volume of metal to remove and the surface produced. ID="A1" Correspondence and offprint requests to: Dr Z. Bouaziz, Department of Mechanical Engineering, Route de Soukra Km3, BP W 3038, Sfax, Tunisia. E-mail: zoubeir.bouaziz@voila.fr