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PDA后蓋塑料注塑模具設(shè)計【說明書+CAD+PROE】,說明書+CAD+PROE,PDA后蓋塑料注塑模具設(shè)計【說明書+CAD+PROE】,pda,塑料,注塑,模具設(shè)計,說明書,仿單,cad,proe A Branch and Bound Algorithm Based Process-Planning System for Plastic Injection Mould Bases （ Int J Adv Manuf Technol (2001) 18:624-6322001 Springer-Verlag London Limited） P. Y. Gan, K. S. Lee and Y. F. Zhang （ Department of Mechanical Engineering, National University of Singapore, Singapore） This paper describes the use of artificial intelligence in the process planning of plastic injection mould bases. The computer-aided process-planning system, developed for IMOLD will extract and identify the operations required for machining.These operations are considered together with their precedence constraints and the available machines before the process plan for the mould base plate is generated. The process plan is optimised by a branch and bound based algorithm. Overallmachining time has been proposed as the objective function for optimisation. The ability of this algorithm to search intelligently for a feasible optimised solution is illustrated by an industrial case study. A brief comparison with a genetic algorithm based process planning system is also made. The result of this development will allow users to optimise process plans easily for any given mould base, with options to suit dynamic changes on the manufacturing shop floor. Keywords: Branch and bound algorithm; Computer-aided process-planning (CAPP); Optimisation; Plastic injection mould base 1. Introduction Computer-aided process planning (CAPP) has received much attention in recent years. It has long been identified as the bridge between computer-aided design (CAD) and computeraided manufacturing (CAM) systems to achieve a fully automated factory. Despite the need, insufficient CAPP systems have been developed for the different industries requiring them. This work focuses on developing a CAPP system for mould base makers. At present, most process planning for the production of mould bases is done manually. The process plans depend very much on the decisions of the process planner. The introduction of CAPP systems should ensure consistently good process plans with more comprehensive consideration ofthe manufacturing parameters. CAPP systems are required in industry for the following reasons: 1. Mould base companies are receiving an increasing number of requests to manufacture customised mould bases, in which additional features are added to a standard mould base. Therefore, extra operations are required to create these new features. Usually, standard mould bases have a predetermined process plan, which is optimised for the amount of machining required. As new operations are added, this optimised process plan is disrupted and manual process planning is unable to keep up with the changes. CAPP systems are able to re-optimise the process plan constantly to ensure optimality of the process plans used. 2. Overall shop floor conditions should be taken into accountduring process planning. Manual process planning is unableto consider all shop floor changes and apply them efficiently. Only CAPP systems allow rigorous consideration of optimisation. The goal of this work is to develop a CAPP system for process planning mould bases. PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 IMOLD (Intelligent Mold Design) is a knowledge-based application software developed at the Department of Mechanical Engineering, NUS to facilitate plastic injection mould design. The system is an addition to IMOLD , and it process plans the mould bases created using IMOLD . Databases of machines, tools, precedence constraints, and the model part file are read together with real-time inputs of machine availability during process planning. An operator is required to enter the customised features and a process plan is then generated using some form of artificial intelligence. The branch and bound technique is the chosen search algorithm here. This paper presents the operation of a flexible CAPP system aimed at assisting process planners in more comprehensive considerations during operations planning. A brief literature survey is provided of some forms of artificial intelligence used in process planning and related work in this field. Problem formulation and the branch and bound algorithm implemented are included in the following sections. Lastly, a case study demonstrates the usability and potential of this system. A comparison between branch and bound based CAPP and genetic algorithm based CAPP is shown in a second case study. 2. Background Process planning is the preparation of a set of detailed instructions for all the steps required to create the final product from a piece of raw material 1. The quality of a process plan depends very much on the skills of the process planner, as extensive knowledge of the available tools, the machines and the operations needed to create a part is required 2. A CAPP system is therefore seen as an important tool for assisting in process planning. A CAPP system should optimise a part for all possible methods of manufacturing. However, many reported CAPP systems are not able to generate globally optimised process plans 3. As a result, there has been an increasing use of artificial intelligence to search for global solutions 4,5. Many of the reported methods involve only feature sequencing without including details of the operations required 6,7. Details of the operations are necessary for allocating shop floor resources for performing the operations. The performance measure is the objective function to be maximised or minimised in all optimisation problems. For process planning, the objective is either to minimise time, cost, or sometimes both. There is a variety of work done using cost as the performance measure 8. However, there is also a range of cost models that can be used to consider and calculate cost 9,10, but there is no universal method to account for costs. It is known that to minimise work-in-progress and the flowtime of jobs in a job shop, process plans with the least overall machining time should be used 11. We therefore use time, as it is a more definite basis on which to quantify the quality of generated process plans. This choice is further justified, as the delivery time of mould bases is very important in mouldmaking industries. An exhaustive sequential search for a process plan solution leads to unacceptable computation times when a large number of operations are required. This work uses a branch and bound algorithm to search intelligently for the optimal or near optimal process plan. The branch and bound algorithm is a well-known search algorithm for implicit enumeration of the search space 12. Its use as an artificial intelligence method has been reported widely in the areas of scheduling, process planning, and problem solving 13. Some work has been reported using the branch and bound technique for process PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 planning 14 16. However, the nature of process plans in those works is different from the process planning required for the mould making industry. This work uses the branch and bound technique to process plan all the operations considering all tool access directions on all the available machines and tools for each mould base plate. To the best of our knowledge, such a level of consideration has not been dealt with in other related studies. 3. Problem Formulation A process-planning problem is constrained to the number of operations, precedence relations, machines, machining direction, and tools. The optimised solution is a way to sequence the operations with their associated machines to produce a process plan, which takes the least possible production time. 3.1 Process Planning Model The information required for optimisation is extracted from mould bases modelled using IMOLD剖 . This database of operations, machines, machining direction, tools, and precedence constraints is used for process planning together with machine availability. A schematic representation of this model is shown in Fig. 1 and the following assumptions are made: 1. Only one operation can be processed by one machine at a time. 2. All the machines can access the part at only one particular face. If machining is to be done on another face, the part has to be taken down and set-up time has to be incurred to replace the part facing a different direction. 3. Cranes or robots are available at all times. No waiting time is allowed for time wasted while waiting for machinery or labour to move the parts. Customised features require the process planner to input the necessary data manually. This is because a single feature can be created by many possible methods and this allows the process planner more control over the system. The assigned operations and the final generated process plan should satisfy the following conditions: 1. The features of the mould base plate are recognised with the operations assigned to them. The operations assigned should produce the desired shape, dimension, tolerance, and finish to the feature. PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 2. The sequence of operations obtained from the process plan should not violate any precedence relations governing the operations. 3. Operations can only be carried out on available machines with the available tools, which are capable of machining that particular feature. The process plan obtained should include the number of operations to be carried out, the sequence of these operations, the machines, machining direction, and corresponding tools used. Such details are necessary so that time can be saved for operations to be carried out on a particular machine using the same set-up. For example, a blind hole must be drilled in the x direction whereas a through hole can be drilled from the x or x directions. It can be seen by considering just thesetwo operations, that the process plan should try to perform these two operations on the same machine from the x direction so that extra set-up time is not incurred. 3.2 The Objective Function To quantify the objective function, which is the overall machining time (OMT), we use a calculation framework similar to that used by Zhang et al. 17. The objective function is calculated for each successive sequence of the process plans and the sequence that yields the minimum OMT will be taken as the final process plan. There are 3 areas which contribute to the calculation of OMT, and they are machine set-up times, machining direction set-up times, and machining times. 3.2.1 Machine Set-up Time Machine set-up time (MST) is considered whenever there is a change of machines between two operations. It is defined as the time required to move between machines and PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 the set-up time of the mould baseplate onto the machine in a particular direction. It is defined for a total of all n operations as Mi refers to the machine selected to process operation i,MSTIi refers to the machine set-up time index for the machine used in operation i, and n is the number of operations selected for the whole series of operations identified from the mould features. 3.2.2 Machining Direction Set-up Time Machining direction set-up time (MDST) is the time required to change the orientation of the mould baseplate on the same machine. MDST is calculated only when there is a change in machining direction, but no change of machine between the two operations. It is defined as, MDi is the machining direction selected to process operation i and MDSTIi is the machining direction set-up time index for the machine used in operation i. MDSTIi and MSTIi are related by the difference in time to move the part between the old and new machine. MSTIi = MDSTIi (4) + (Time to move part between machines) As no waiting time for the cranes or robots is assumed, we take MDSTIi and MSTIi to be the same. 4.Conclusions This paper illustrates a branch and bound based CAPP system It considers operation sequencing, machines, machining direc-tions, and tools, and is able to provide a detailed process plan. It can be customised easily to account for tool change time and to accommodate different environments. The system offers a comprehensive shop floor consideration in its optimisation of overall machining time. PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 The case study has achieved good process plans that are capable of readjusting operation sequences to accommodate any shop floor changes. The computation times required to achieve the solution for actual mould baseplates are found to be reasonable for process planning purposes. Comparison with the GA based system has proved that the branch and bound based system is able to match the GA based system for most problems, and obtains good solutions faster. The module offers an approach to suit dynamic changes and is more adaptable than approaches which assume a fixed shop floor environment. Development of the CAPP system will allow quantitative comparisons to be made between different generated process plans and help to evaluate manufacturing processes better. In the future, other performance measures such as costs and also the use of this module for more complex parts will be explored. References 1. C. B. Besant and C. W. K. Lui, Computer-Aided Design and Manufacture, 3rd edn, Ellis Horwood, 1986. 2.T. C. Chang, Expert Process Planning for Manufacturing, Addison- Wesley, 1990. 3. M. C. Kayacan, I. H. Filiz, A. I. So nmez, A. Baykasoglu and T. Dereli. “ OPPS-ROT: an optimised process planning system for rotational parts” , Computers in Industry, 32, pp. 181 95, 1996. 4. D. T. Pham and P. T. N. Pham, “ Artificial intelligence in engineering” ,International Journal of Machine Tools and Manufacture, 39, pp. 937 949, 1999. PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 5. C. Leung Horris, “ Annotated bibliography on computer-aided process planning” , International Journal of Manufacturing Technology” ,12, pp. 309 329, 1996. 6. Jo zsef Va ncza and Andra s Ma rkus, “ Experiments with the integration of reasoning, optimisation and generalisation in process planning” , Advances in Engineering Software, 25, pp. 29 39, 1996. 7. 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Weglarz, Scheduling in Computer and Manufacturing Systems, 2nd rev. edn, Springer-Verlag, PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建 1994. 13. J. L. Laurilere, “ Problem solving and artificial intelligence” , Prentice Hall, New York, 1990. 14. Y. M. Kyoung, K. K. Cho and C. S. Jun, “ Optimal tool selection for pocket machining in process planning” , Computers and Industrial Engineering, 33(3 4), pp. 505 508, December 1997. 15. J. Duflou, J. -P. Kruth and D. Van Oudheusden, “ Algorithms for the design verification and automatic process planning for bent sheet metal parts” , CIRP Annals, 48(1), pp. 405 408, 1999. 16. J. R. Duflou, D. Van Oudheusden, J.-P. Kruth and D. Cattrysse, “ Methods for the sequencing of sheet metal bending operations” ,International Journal of Production Research, 37(14), pp. 3185 3202, 1999. 17. F. Zhang, Y. F. Zhang and A. Y. C. Nee, “ Using geneticalgorithms in process planning for job shop machining” , IEEETransactions on Evolutionary Computation, 1(4), pp. 278 289,November 1997. 18. C. Y. Hung, K. S. Lee, M. Rahman and Y. F. Zhang, “ Mold base process planning by genetic algorithm” 1st International Conference on Die and Mold Technology, pp. 233 243 Beijing, P.R. China, 26 28 July 2000. PDF 文件使用 pdfFactory Pro 試用版本創(chuàng)建