Computer aided manufacturing planning for mass customization: part 2, automated setup planning

Setup planning plays a crucial role in CAPP to ensure product quality while maintaining acceptable manufacturing cost. The tasks of setup planning include identifying manufacturing features and corresponding manufacturing processes, determining the number of setups, part orientation, locating datum and process sequence in each setup, and selecting machine tools and fixtures. An automated setup planning technique and system has been developed based on not only the tolerance analysis, but also the manufacturing resource capability analysis. The automated setup planning is divided into two levels: setup planning in single part level and in machine station level. Algorithms for setup generation and process sequencing have been developed and a case study of setup planning is presented.     

Optimisation of operations sequence in CAPP using an ant colony algorithm

Computer-aided process planning (CAPP) forms an important interface between Computer-aided design (CAD) and Computer-aided manufacturing (CAM). It is concerned with determining the sequence of individual manufacturing operations required to produce a product as per technical specifications given in the part drawing. Any sequence of manufacturing operations that is generated in a process plan cannot be the best possible sequence every time in a changing production environment. As the complexity of the product increases, the number of feasible sequences increases exponentially, and there is a need to choose the best among them. This paper presents an application of a newly developed metaheuristic called the ant colony algorithm as a global search technique for the quick identification of the optimal operations sequence by considering various feasibility constrains. A couple of case studies are taken from the literature to comparing the results obtained by the proposed method.     

Algorithms for computer-aided generative process planning

Process planning is the function within a manufacturing facility that establishes the machining processes and parameters to be used so as to convert a piece-part from its initial form to the final form predetermined on an engineering drawing. Computer-aided process planning (CAPP) has become a major focus of manufacturing automation as it forms the interface between computer-aided design (CAD) and computer-aided manufacturing (CAM). Issues in CAPP include part representation, process selection, alternative process-plan generation, intermediate surface and tolerance determination, and operation sequencing. This paper focuses on quantitative models for determining cutting dimensions and tolerances for intermediate surfaces, and on a heuristic for sequencing cutting operations.     

Integration of process planning and scheduling in a job shop environment

Today’s manufacturing systems are striving for an integrated manufacturing environment. To achieve truly computer-integrated manufacturing systems (CIMS), the integration of process planning and production scheduling is essential. This paper proposes a framework for integration of process planning with production scheduling in a job shop environment for axisymmetric components. Based on the design specifications of incoming parts, feasible process plans are generated taking into account the real time shop floor status and availability of machine tools. The scheduling strategy prioritizes the machine tools based on cost considerations.     

Integrated setup planning and operation sequencing (ISOS) using genetic algorithm

Process planning is an essential component for linking design and manufacturing process. Setup planning and operation sequencing are two most important functions in the implementation of CAD/CAPP/CAM integration. Many researches solved these two problems separately. Considering the fact that the two functions are complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved economically and competitively. This paper presents a generative system and genetic algorithm (GA) approach to process plan the given part. The proposed approach and optimization methodology analysis constraints such as TAD?(tool?approach?direction), tolerance relation between features and feature precedence relations to generate all possible setups and operations using workshop resource database. Tolerance relation analysis has a significant impact in setup planning for obtaining the part accuracy. Based on technological constraints, the GA algorithm approach, which adopts the feature-based representation, simultaneously optimizes the setup plan and sequence of operations using cost indices. Case studies show that the developed system can generate satisfactory results in optimizing the integrated setup planning and operation sequencing in feasible condition.     

Simultaneous process mean and process tolerance determination with adjustment and compensation for precision manufacturing process

Conventional process planning of manufacturing operations presets fixed process means and process tolerances for all operations and allows outputs to be distributed around these fixed values, as long as the final outputs meet acceptable specifications. Most of these approaches consider process means and process tolerances to be independent decision variables in process planning with the resultant process means equal or close to the design targets of the blueprint dimensions. Furthermore, these approaches assume that process variability is small in comparison to the quality requirement, and that the phenomena of process shifting or deterioration are not factors of manufacturing operations. For these reasons, conventional approaches to process planning are inappropriate for high value, and precision manufacturing process, particularly of a complex part. Hence, this study introduces a process optimization model which considers process means and process tolerances simultaneously, with sequential operation adjustment to reduce process variability, and with part compensation to offset process shifting.     

Cost based scheduling in a job shop environment

Scheduling is one of the most important issues in operations planning of a manufacturing system. In this paper a new scheduling strategy based on machine cost considerations has been proposed. A scheduling factor based on initial cost of a machine and its running cost has been developed. A scanning procedure has been implemented which prioritizes eligible workstations for each setup of a job based on the scheduling factor. Two measures of performance—idleness factor and idleness cost factor—have been developed. Computer simulation has been used to investigate the impact of various decision parameters on operating behavior of the system.     

An integrated fixture planning system for minimum tolerances

Fixture planning is an important aspect of process planning. The steps involved in automatic fixture planning are manufacturing feature recognition, setup planning and fixture configuration planning. In the present work, an integrated setup and fixture planning system is developed for minimum tolerances at critical regions using a data exchanged part model as an input. A platform-independent STEP-based automatic feature recognition system that can recognize both design and manufacturing features, including intersecting features is implemented. An automatic setup planning module is developed for generating setup plans for complete machining of a given component. A fixture planning module is developed applying the criteria of uniqueness, stability, accessibility and tolerance minimization. A case study is presented to demonstrate the capabilities and integration between the various modules of the system.     

Tolerance chart balancing with a complete inspection plan taking account of manufacturing and quality costs

This paper introduces a mathematical model of tolerance chart balancing for machining process planning under complete inspection. The criteria considered in this study are based on the combined effects of manufacturing cost and quality loss, under constraints such as process capability limits, product design specifications, and product quality requirements. Manufacturing costs include the machining cost, part cost, inspection cost, reworking cost, and replacement cost. The machining cost is expressed in geometrical decreasing functions, which represent tolerances to be assigned. Process variability is expressed in quadratic loss functions, which represent the deviation between the part measurement and the target value. An example is presented to demonstrate the proposed model. A comparison made with previous methods shows that the proposed model minimizes the total cost of manufacturing activities and quality-related issues in machining process planning, particularly in the early stages. Moreover, the applications are not be limited to machining process planning but can also be used in other forms of production planning.     

A Cascading Auction Protocol as a Framework for Integrating Process Planning and Heterarchical Shop Floor Control

A new contract net-style auction protocol is proposed as a framework for integrating process planning and shop floor control in heterarchical manufacturing systems. Process planning is partitioned into on-line and off-line activities; off-line process planning decisions are represented in a graph format and used as input for on-line process planning activities performed by machine controllers. Triggered by the opening round of an auction, the final on-line stages of process planning are dovetailed with the resource allocation process in the shop floor control system. The auction process allows final process planning decisions to be based on timely information, relying on the distribution of static process planning information rather than the distribution of a model of dynamic shop floor status and allowing a controller to identify all the primary and secondary resources and operations that must be provided for the incremental processing of a part.     

面向飞机装配的工艺设计与管理系统研究与开发

工艺是连接产品设计与制造的桥梁,是实现产品信息集成与管理的关键。在分析飞机装配特点和工艺管理特点的基础上,提出了面向飞机装配工艺设计和工艺管理的实现策略,阐述面向飞机装配工艺设计与管理系统应具有的基本功能,并对MBOM的生成和管理做了详细的说明,在此基础上为某航空企业开发了一套面向飞机装配工艺设计和工艺管理的应用系统,并取得了较好的使用效果。     

Computer-aided manufacturing planning for mass customization: part 1, framework

This paper introduces a comprehensive system for the production planning of the mass customization of non-rotational parts. Combined features are defined based on the concept of part families. The process parameters are associated with the feature parameters so that rapid production planning can be achieved for product design changes. Setup planning is carried out based on both the best practice knowledge in industry and the algorithmic generation of setups. Manufacturing resource, fixture design, and tolerance issues are considered in the production planning. The system also estimates cycle times and generates standard documentation.     

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.     

An integrated expert operation planning system with a feature-based design model

A framework of a knowledge-based expert operation planning system, TURNPLAN, is described. The system incorporates a feature-based part representation scheme to smooth the essential information flow from design intent to manufacturing practice. Its main functions initially consist of the determination of machining sequence, cutting parameters and cutting tools. To make this system a complete working module for full integration of CAD/CAM, its knowledge base has been further upgraded so that determination of work-holding methods, and generation of tool paths and the associated NC part programs, are included in the system. This integrated system is developed on a PC-based computer using PROLOG, which is found suitable in a batch-type job shop environment for industrial applications. A practical example is included to highlight certain features of the system and the paper concludes with implications for further research.     

An intelligent process planning system for prismatic parts using STEP features

This paper presents an intelligent process planning system using STEP features (ST-FeatCAPP) for prismatic parts. The system maps a STEP AP224 XML data file, without using a complex feature recognition process, and produces the corresponding machining operations to generate the process plan and corresponding STEP-NC in XML format. It carries out several stages of process planning such as operations selection, tool selection, machining parameters determination, machine tools selection and setup planning. A hybrid approach of most recent techniques (neural networks, fuzzy logic and rule-based) of artificial intelligence is used as the inference engine of the developed system. An object-oriented approach is used in the definition and implementation of the system. An example part is tested and the corresponding process plan is presented to demonstrate and verify the proposed CAPP system. The paper thus suggests a new feature-based intelligent CAPP system for avoiding complex feature recognition and knowledge acquisition problems.     

KBE-based stamping process paths generated for automobile panels

As automobile body panels are one kind of sheet metal part with groups of free form surfaces, the process planning is more complicated than common sheet metal stamping to implode effectively and practically. Based on KBE, new frameworks have been presented as intelligent master model at the system level and as procedure model at the activity level. In accordance with these frameworks, an intelligent CAPP system has been specifically developed. Based on feature technology, features have been extracted and represented by the object-oriented method. Stamping features and their parameters have been defined and extracted based on feature technology and stamping process rules. The whole product knowledge has been represented by frames which directly map to objects (or features) in the object-oriented sense. Relevant appropriate operations features have been assigned to stamping features of a product based on feature-operation criteria, parameters of the stamping feature and their correlativity. This assignment is a decision-making activity using a set of rules with a decision-making tree and model-based reasoning methods. With knowledge between operations, such as operations order constraint (do-after) and operations combination constraint, process paths have been improved based on relevant intelligent reasoning methods. Based on the relationships (preferred-to) between processes and machines/dies, the structure of die and machine for each process can be identified, since the process route has been determined. In this stamping process planning, the procedure and information have been controlled by a process control structure that is associative and integrated.     

Efficiency Measures of Process Plans for Machined Parts

This paper presents an overview of the authors’ rooted tree technique for process planning. The overview provides the foundation for the main part of the paper, which explains how the rooted tree can be used to develop efficiency measures of process plans. The efficiency measures are determined by comparing an actual tree and its subgraphs with an "ideal" tree. The "ideal tree" is one that minimises the number of manufacturing operations. The paper proves that the "ideal tree" is a directed design dimension graph plus one operation. Three measures of efficiency are presented: finishing efficiency, preforming efficiency, and overall efficiency. The practical value of the efficiency measures is demonstrated by presenting measures of plans for four industrial parts. It is also argued that the efficiency measures provide a quantitative assessment of process plans that can be used to improve them and manufacturing technology.     

Dimensional and geometrical tolerance balancing in concurrent design

In conventional design, tolerancing is divided into two separated sequential stages, i.e., product tolerancing and process tolerancing. In product tolerancing stage, the assembly functional tolerances are allocated to BP component tolerances. In the process tolerancing stage, the obtained BP tolerances are further allocated to the process tolerances in terms of the given process planning. As a result, tolerance design often results in conflict and redesign. An optimal design methodology for both dimensional and geometrical tolerances (DGTs) is presented and validated in a concurrent design environment. We directly allocate the required functional assembly DGTs to the pertinent process DGTs by using the given process planning of the related components. Geometrical tolerances are treated as the equivalent bilateral dimensional tolerances or the additional tolerance constraints according to their functional roles and engineering semantics in manufacturing. When the process sequences of the related components have been determined in the assembly structure design stage, we formulate the concurrent tolerance chains to express the relations between the assembly DGTs and the related component process DGTs by using the integrated tolerance charts. Concurrent tolerancing which simultaneously optimizes the process tolerance based on the constraints of concurrent DGTs and the process accuracy is implemented by a linear programming approach. In the optimization model the objective is to maximize the total weight process DGTs while weight factor is used to evaluate the different manufacturing costs between different means of manufacturing operations corresponding to the same tolerance value. Economical tolerance bounds of related operations are given as constraints. Finally, an example is included to demonstrate the proposed methodology.     

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.     

A cost-based algorithm for design of Cellular Manufacturing Systems

This paper describes a cost-based algorithm that deals with the design problems of Cellular Manufacturing Systems (CMS) associated exceptional parts and bottleneck machines. The developed algorithm employes explicitly the main elements of manufacturing costs, such as the fixed machine cost, the production cost, the setup cost, and the material handling cost. The algorithm is based on the minimization of sum of these costs, and considers three alternatives to solve exceptional issues. The first alternative is to try to eliminate the maximum number of intercellular movements from the presently configured manufacturing system by buying and installing extra bottleneck machines into the appropriate cells. The second alternative considers the alternative process plans available and tries to complete the job using the overtime basis in the small machine cells. The third alternative considers the possibility of subcontracting the processing operations of exceptional part(s) to outside vendors to reduce the overall cost for the manufacturing system. The total costs of the three cases are compared and the best alternative for any given problem is identified. In order to illustrate performance of the algorithm developed, a test example is provided.