GENERATIVE CAPP PDF

Geometry-based coding scheme Process knowledge in the form of decision logic and data to perform uniquely the main decisions for converting apart from raw materials to a finished state. Do a preliminary sorting of pockets in order of levels that clearly indicate the likely sequence in the final process plan Examine the pocket for any possibility of combining so that the machining operations could be reduced Select the machine tools that can be used for each of the identified pockets Identify the process sequence required for the machining of the pocket based on the technological requirements For each of the pocket and the operation decided, select the cutting tool required. Sort the operations on the basis of the machine tools and cutting tools. Sequence the operations on the basis of the machine tools and cutting tools by making use of heuristic rules Evaluate the machining time and idle time and select the final process plan based on the lowest cost and machining time Present the final results in a suitable form. Experienced process planners are still required to modify the standard plan for the specific component. If you have any doubts, feel free to ask from the comments section.

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Tight integration with a manufacturing resource planning system is needed to track shop floor status and load data and assess alternate routings vis-a-vis the schedule. A typical CAPP frame-work is shown in figure The geometry based coding scheme defines all geometric features for process related surfaces together with feature dimensions, locations, tolerances and the surface finish desired on the features. Since finite scheduling systems are still in their infancy, this additional dimension to production scheduling is still a long way off.

Routings which specify operations, operation sequences, work centers, standards, tooling and fixtures. The first step is the implementation of GT or FT classification and coding.

Prior to CAPP, manufacturers attempted to overcome the problems of manual process planning by basic classification of parts into families and developing somewhat standardized process plans for parts families Stage I. For example, details such as rough and finished states of the parts and process capability of machine tools to transform these parts to the desired states are provided.

The results of the planning are: The decision rules would result in process plans that would reduce the overloading on the primary work center by generatkve an alternate routing that would have the least cost impact. When comapred with manual experience-based process planning, CAPP offers following advantages; Systematic developemnt of accurate and consistent process plans Reduction of cost and lead time of process planning Reduced skill requirements of process planners Gdnerative productivity of process planners Higher level application progams such as cost and manufacturing lead time estimation and work standards can be interfaced.

In order to produce such things as NC instructions for CAM equipment, basic decisions regarding equipment to be used,tooling and operation sequence need to be made. The variant process planning approach can be realized as a four step process; 1. Computer-Aided Process Planning A number of methods have been developed for part family formation using coding and classification schemes of group technology GTsimiliarity-coefficient based algorithms and mathematical programming models.

The baseline process plans stored in the computer are manually entered using a super planner concept,that is, developing standardized plans based on the accumulated experience and knowledge of multiple planners and manufacturing engineers Stage III. This system can be used to generate process plan for rotational, prismatic and sheet-metal parts.

The nature of the parts will affect the complexity of the decision rules for generative planning and ultimately the degree of success in implementing the generative CAPP system. A further step in this stage is dynamic, generative Generativd which would consider plant and machine capacities, tooling availability, work center and equipment loads, and equipment status e.

The first key to implementing a generative system is the development of decision dapp appropriate for the items to be processed. As the design process is supported by many computer-aided tools, computer-aided process planning CAPP has evolved to acpp and improve process planning and achieve more effective use of manufacturing resources.

In addition, there has been significant recent effort with generative process planning for assembly operations, including Yenerative assembly. CAPP integrates and optimizes system performance into the inter-organizational flow. The planner will add the remaining caop percent of the effort modifying or fine-tuning the process plan. The planning begins with engineering drawings, specifications, parts or material lists and a forecast of demand.

CAD systems generate graphically oriented data and may go so far as graphically identifying metal, etc. This type of system uses work instruction displays at factory workstations to display process plans graphically and guide employees through assembly step by caapp. CAPP is a highly effective technology for discrete manufacturers with a significant number of products and process steps.

There are two major genrative of generative CAPP; a geometry based coding scheme and process knowledge in form of decision logic data. This type of purely generative system in Stage V will generatuve the use of artificial intelligence type capabilities to produce process plans as well as be fully integrated in a CIM environment.

Development of manufacturing knowledge base generayive backbone of generative CAPP. A second key to generative process planning is the available data related to the part to drive the planning.

Fabrication and assembly drawings to support manufacture as opposed to engineering drawings to define the part. In a detailed survey of twenty-two large and small companies using generative-type CAPP systems, the following estimated cost savings were achieved:.

In the generative CAPP, process cap are generated by means of decision logic, formulas, technology algorithms and geometry based data to perform uniquely many processing decisions for converting part from raw material to finished state.

Simple forms of generative planning systems may be driven by GT codes. For example, if a primary work center for an operation s was overloaded, the generative planning process would evaluate work to be released involving that work center,alternate processes and the related routings. The similiarities in design attributes and manufacturing methods are exploited for the purpose of formation of part families.

While CAPP systems are moving more and more towards being generative, a pure generative system that can produce a complete process plan from part classification and other design data is a goal of the future.

The majority of generative CAPP systems implemented to date have focused on process planning for fabrication of sheet metal parts and less complex machined parts. TOP Related Articles.

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Kazim For example, when one changes the design, it must be able to fall back on CAPP module to generate manufacturing process and cost estimates for these design changes. Simple forms of generative planning systems may be driven by GT codes. While CAPP systems are moving more and more towards being generative, a pure generative system that can produce a complete czpp plan from part classification and other design data is a goal of the future. The results of the planning are:. As the design process is supported by many computer-aided tools, computer-aided process planning CAPP has evolved to simplify and improve process planning and achieve more effective use czpp manufacturing resources.

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GENERATIVE CAPP PDF

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