Concurrent process/inspection planning for a customized manufacturing system based on genetic algorithm

Producing products with multiple quality characteristics is always one of the concerns for an advanced manufacturing system. To assure product quality, finite manufacturing resources (i.e., process workstations and inspection stations) could be available and employed. The manufacturing resource allocation problem then occurs, therefore, process planning and inspection planning should be performed. Both of these are traditionally regarded as individual tasks and conducted separately. Actually, these two tasks are related. Greater performance of an advanced manufacturing system can be achieved if process planning and inspection planning can be performed concurrently to manage the limited manufacturing resources. Since the product variety in batch production or job-shop production will be increased for satisfying the changing requirements of various customers, the specified tolerance of each quality characteristic will vary from time to time. Except for finite manufacturing resource constraints, the manufacturing capability, inspection capability, and tolerance specified by customer requirement are also considered for a customized manufacturing system in this research. Then, the unit cost model is constructed to represent the overall performance of an advanced manufacturing system by considering both internal and external costs. Process planning and inspection planning can then be concurrently solved by practically reflecting the customer requirements. Since determining the optimal manufacturing resource allocation plan seems to be impractical as the problem size becomes quite large, in this research, genetic algorithm is successfully applied with the realistic unit cost embedded. The performance of genetic algorithm is measured in comparison with the enumeration method that generates the optimal solution. The result shows that a near-optimal manufacturing resource allocation plan can be determined efficiently for meeting the changing requirement of customers as the problem size becomes quite large.     

A flexible process information reuse method for similar machining feature

Dynamically changing machining conditions and uncertain manufacturing resource availability are forcing manufacturing enterprises to search advanced process planning in order to increase productivity and ensure product quality. As growing quantities of the three-dimensional process models are gradually applied, reusing the embedded manufacturing information in process models with less time and lower cost attracts a lot of attention. In this paper, a new flexible method is presented to reuse the existing process information based on retrieval of the similar machining feature. First, the three-level organization model is introduced to represent the process information; the machining feature which is seen as the parent layer carries the corresponding manufacturing information. To ensure accurately that the process information are obtained, the associated mechanism between the machining feature and process information is created. Second, an eight-node representation scheme is designed to represent the similar machining feature having same variations in topology and geometry. For accelerating similar feature retrieval, the extension-attributed adjacency graph and the topological relationship of the machining feature faces are built. Finally, some aircraft structural parts are utilized in the developed prototype module to verify the effectiveness of the proposed method. This method can be used as the basis for accumulation of the process information; it can promote the development and application of the intelligent process planning.     

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。     

Java-based computer-aided process planning

This investigation addresses distributed environments for computer-aided process planning (CAPP) over a network. The Java 2 Enterprise Edition (J2EE) standard using Java is applied to implement cross-platform and distributed computing architecture, thus reducing the system loading during manufacturing process planning. The product-oriented standard, standard exchange of product (STEP), model data is applied to define a robust data model that associates product, shape, and feature definitions and provides the mechanisms for data exchange, sharing, and integration with other engineering systems, such as computer-aided design (CAD) and computer-aided manufacturing (CAM). STEP AP224 is engaged to define the machining features of machined products in the proposed CAPP system. The life cycle of a product from design to sale, and especially the period of manufacturing, can be greatly shortened; the cost of manufacturing can be reduced and the quality of the product can be improved using the proposed CAPP system.     

Computer-aided geometrical dimensioning and tolerancing for process-operation planning and quality control

This paper describes an extension of a model which determines an optimum set of dimensions and tolerances for machining processes at minimum manufacturing cost. This optimisation minimizes the cost of scrap, which is a function of manufacturing tolerances, as the objective function. Requirements of design sizes, geometrical tolerances (including both form and position) and machining allowances are expressed mathematically as constraints for the optimisation. A computerised trace method has been extended to determine the relationships between geometrical tolerances and associated relevant manufacturing dimensions and tolerances. In addition to the manufacturing cost, the model takes into account manufacturing sequence, distribution of manufacturing dimensions, process capabilities, tolerances, design sizes, geometrical tolerances, machining allowances and optimum scrap level. The resulting computerized interactive system can be used not only in process planning, but also in quality control.     

Neutral representation of tolerance information for process planning using STEP AP 224

The focus of CIM is on information as it is the crucial element for integrating all the manufacturing activities. CAPP, as one of the key elements in CIM, needs to extract the manufacturing information such as machining features and precision specifications like surface roughness and tolerances from a geometric model in order to link CAD and CAM. However, these data are not real attributes of the geometric model in most of the current CAD systems. Therefore, human interpretation is inevitable for further processing of CAD model for downstream application like process planning or inspection. This paper proposes a scheme to represent the manufacturing information in a neutral format using STEP technology in order to enable downstream users such as process planner and inspection planner to make correct decisions on process selection, processing conditions, etc. It is shown that by using STEP AP224 manufacturing information encompassing machining features, surface roughness, dimensional and geometric tolerances can be completely represented together with part geometry, which certainly contributes to successful implementation of CIM.     

Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

Manufacturing variation models in multi-station machining systems

In product design and quality improvement fields, the development of reliable 3D machining variation models for multi-station machining processes is a key issue to estimate the resulting geometrical and dimensional quality of manufactured parts, generate robust process plans, eliminate downstream manufacturing problems, and reduce ramp-up times. In the literature, two main 3D machining variation models have been studied: the stream of variation model, oriented to product quality improvement (fault diagnosis, process planning evaluation and selection, etc.), and the model of the manufactured part, oriented to product and manufacturing design activities (manufacturing and product tolerance analysis and synthesis). This paper reviews the fundamentals of each model and describes step by step how to derive them using a simple case study. The paper analyzes both models and compares their main characteristics and applications. A discussion about the drawbacks and limitations of each model and some potential research lines in this field are also presented.     

An Intelligent Knowledge-Based System for Product Cost Modelling

An intelligent knowledge-based system for product cost modellingis presented in this paper. The developed system has the capability of selecting a material, as well as machining processes and parameters based on a set of design and production parameters; and of estimating the product cost throughout the entire product development cycle including assembly cost. The proposed system is applied without the need for detailed design information, so that it can be used at an early design stage, and, consequently, redesign cost and longer lead time can be avoided. Hybrid knowledge representation techniques, such as production rules, frame and object oriented are employed to represent manufacturing knowledge. Fuzzy logic-based knowledge representation is applied to deal with uncertainty in the knowledge of cost model to generate reliable cost estimation. This paper deals with cost modelling of both a machining component and an injection moulding component, which is a process that gives high production rates, excellent quality and accuracy of products, and low manufacturing cost. Based on the analysis of the moulded product life cycle, a computer-based cost model was developed which integrated the relationship between cost factors, product development activities, and product geometry. The estimated cost included the costs of material, mould and processing. The system has been validated through a case study.     

Concurrent optimization of machining process parameters and tolerance allocation

With the advent use of sophisticated and high-cost machines coupled with higher labor costs, concurrent optimization of machining process parameters and tolerance allocation plays a vital role in producing the parts economically. In this paper, an effort is made to concurrently optimize the manufacturing cost of piston and cylinder components by optimizing the operating parameters of the machining processes. Design of experiments (DoE) is adopted to investigate systematically the machining process parameters that influence product quality. In addition, tolerance plays a vital role in assembly of parts in manufacturing industries. For the selected piston and cylinder component, improvements efforts are made to reduce the total manufacturing cost of the components. By making use of central composite rotatable design method, a module of DoE, a mathematical model is developed for predicting the standard deviation of the tolerance achieved by grinding process. This mathematical model, which gives 93.3% accuracy, is used to calculate the quality loss cost. The intent of concurrent optimization problem is to minimize total manufacturing cost and quality loss function. Genetic algorithm is followed for optimizing the parameters. The results prove that there is a considerable reduction in manufacturing cost without violating the required tolerance, cutting force, and power.     

Quick decision-making support for inspection allocation planning with rapidly changing customer requirements

Manufacturing products with multiple quality characteristics is always one of the main concerns for an advanced manufacturing system. To assure product quality, finite automatic inspection systems should be available and employed. Inspection planning to allocate inspection stations should then be performed to manage limited inspection resources. Since product variety in batch production or job shop production is increased to satisfy the changing requirements of various customers, the specified tolerance of each quality characteristic varies from time to time. Except for a finite inspection resource constraint, therefore, manufacturing capability, inspection capability, and tolerance specified by customer requirement are considered concurrently in this research. A unit cost model is constructed to represent the overall performance of an advanced manufacturing system. Both the internal and external costs of a multiple quality characteristic product are considered. The inspection allocation problem can then be solved to reflect customer requirements. Since determining the optimal inspection allocation plan seems to be impractical as the problem size gets larger, in this research, two decision criteria (i.e., sequence order of workstation and tolerance interval) are employed concurrently to develop a heuristic method. The performance of the heuristic method is measured in comparison with an enumeration method that generates the optimal solution. The result shows that a feasible inspection allocation plan to meet changing customer requirements can be determined efficiently.     

基于检测状态模型的飞机结构件在线检测路径规划

针对飞机结构件在线检测路径规划中零件工艺模型伴随加工过程动态变化、检测工艺复杂的难点,提出了基于检测状态模型的飞机结构件在线检测路径规划方法。检测状态模型以特征为载体,以干涉特征和虚路径表达干涉规避、路径优化等知识和经验,并随着加工过程动态扩充。基于检测状态模型,按照检测操作级、检测特征级、特征自身级三级实现了在线检测路径规划。根据以上研究,基于CATIA V5开发的在线检测数据自动生成系统已在某大型航空企业中得到成功应用。     

我国高速加工技术现状及发展趋势

高速加工是以较快生产节拍进行加工 ,提高切削和进刀速度是高速加工技术的重要环节。高速加工技术的发展涉及到零件毛坯、刀具、机床、自动控制与检测等多种技术的综合优化 ,需要变革传统的机加工工艺路线。我国引进的轿车零部件数控自动生产线上已广泛应用高速加工技术 ,其主要目的是在确保产品质量的前提下 ,尽量缩短零件的机加工工艺路线 ,加快生产节拍 (轿车发动机生产节拍已缩短为 30秒 ) ,满足轿车高质量、高速率、低成本、大批量、社会化生产的技术要求。高速加工技术必将带动零件毛坯制造、刀具 (工具 )、数控机床、自动控制、在线检测、材料等技术的发展与进步。随着我国制造业加快融入全球化生产制造体系 ,预计高速加工技术将在信息化、柔性化机械加工领域得到进一步发展和推广应用     

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.     

基于QFD的数控加工工艺质量优化规划方法

提出了一种基于质量功能配置的确定工艺质量水平的建模方法,并建立了优化数学模型,其目标函数是总体工艺质量改进程度最大化,约束条件包括三个方面：①工艺质量水平变化区间。②工艺质量要素之间的相关性。③预算的工艺质量成本。应用实例表明,针对具体的工艺质量问题,运用该模型能够帮助工艺设计人员有效地规划出最优的工艺质量水平。     

Locating Error Considering Dimensional Errors Modeling for Multistation Manufacturing System

Multistation machining process is widely applied in contemporary manufacturing environment.Modeling of variation propagation in multistation machining process is one of the most important research scenarios.Due to the existence of multiple variation streams,it is challenging to model and analyze variation propagation in a multi-station system.Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality.In this paper,a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated.A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors,so the dimensional error accumulation and transformation within the multistation process are quantitatively described.A systematic procedure to build the model is presented,which enhances the way to determine the variation sources in complex machining systems.A simple two-dimensional example is used to illustrate the proposed procedures.Finally,an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method.The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.     

Simultaneous process mean and process tolerance determination with asymmetrical loss function

Process design involves process mean and process tolerance determination. Process mean determination is finding the best settings for product quality, without affecting manufacturing cost. However, process tolerance determination is a manufacturing process selection which generally affects manufacturing cost and product quality. In this study, asymmetric quality loss is considered in measuring product quality, and tolerance cost is adopted in representing manufacturing cost. To reflect the combined effect of process mean and process tolerance completely, failure cost is added to the category of manufacturing cost. Then, based on the sum of these three costs, a simultaneous optimization of process mean and process tolerance is determined for process planning in the early stages of development.     

面向工艺设计的制造过程建模

基于工艺设计对产品制造成本、质量和效率的重要影响,提出了一种基于工艺设计的制造过程建模方法,以通过对过程模型的仿真,预测、分析和优化工艺设计效果。基于对制造过程的特征分析,采用面向对象的方法,首先将制造过程定义为一组成对象,并划分为制造活动、过程控制和制造资源3类成分对象,建立了制造过程类结构模型和动态过程模型。分别定义了工序类、制造资源类和过程控制类的类结构模型,以及各类对象的方法和属性。基于这些模型开发了一种计算机辅助工艺设计系统,可快速、自动地构建工艺设计定义的制造过程模型,并对过程参数（成本、时间）、切削加工、工件物流进行计算和仿真。     

The study of cost-tolerance model by incorporating process capability index into product lifecycle cost

To reduce the cost of manufacturing systems, many studies of cost minimization have been performed. Since tolerance design significantly affects the manufacturers’ cost, the optimization of cost-tolerance allocation will be an important issue for reducing these costs. Costs incurred in a product life-cycle include manufacturing cost and quality loss. However, most cost-tolerance optimization models frequently ignore the concept of quality loss and may not lead to an accurate analysis of the tolerance. Until now, process capability analysis has been the tool used to evaluate the adequacy of a production tool in meeting a quality target. Hence, the concept of process capability analysis should be included into the cost-tolerance optimization model. In this study, a flexible cost-tolerance optimization model will be constructed by integrating the process capability index into the product life-cycle cost function. The constructed cost-tolerance optimization model simultaneously considers the manufacturing cost of the components, the process capability of the manufacturing operations, and the quality loss of products. The decision-maker can apply the proposed cost-tolerance optimization model to determine a reasonable tolerance with minimum total cost including consideration of the process capability .     

多工序质量检验计划的多目标优化蚁群算法研究

针对常见的串行多工序抽样检验方式，建立了工序间质量水平传递模型和质量检验成本模型，提出基于Pareto解评价的多目标优化蚁群算法；通过定义多目标解与理想解的相对距离为蚁群算法的启发函数，激励蚁群搜索可行解空间并发现最优解集；应用多目标优化蚁群算法解决质量检验计划优化问题取得了较好效果。