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Comparison of Variant and Generative Process planning methods and their Computer Aided Process Planning Presented By- Pratik Patel. Approaches to Computer Aided Process Planning (CAPP). Variant Process Planning, Advantages and Disadvantages. Generative Process. The next stage of evolution is toward generative CAPP (Stage IV). At this stage, process planning decision rules are built into the system. These decision rules.

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CAD systems generate graphically oriented data and may go so far as graphically identifying metal, etc.

In a detailed survey of twenty-two large and fenerative companies using generative-type CAPP systems, the following estimated cost savings were achieved: In a detailed fenerative of twenty-two large and small companies using generative-type CAPP systems, the following estimated cost savings were achieved:.

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. The first key to implementing a generative system is the development of decision rules appropriate for the items to be processed.

The similiarities in design attributes and manufacturing methods are exploited for the purpose of formation of part families.

The results of the planning are:. In the generative CAPP, process plans are generated by means of decision logic, formulas, technology algorithms and geometry based data to perform uniquely many processing decisions for generahive part from raw material to finished state. Similarly, in case of generrative breakdown on the shop floor, CAPP must generate the alternative actions so that most economical solution can be adopted in the given situation.

CAPP is a highly effective technology for discrete manufacturers with a significant number of products and process steps.

The process plan developed with a CAPP system at Stage V generatie vary over time depending on the resources and workload in the factory. Reduced process planning and production leadtime; faster response to engineering changes Greater process plan consistency; access to up-to-date information in a central database Improved cost estimating procedures and fewer calculation errors More complete and detailed process plans Improved production scheduling and capacity utilization Improved ability to introduce new manufacturing technology and rapidly update process plans to utilize the improved technology SUMMARY CAPP is a highly effective technology for discrete manufacturers with a significant number of products and process steps.

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. 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. 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 genertive a complete process plan geneative part classification and other design data is a goal of the future. This routing becomes a major input to the manufacturing resource planning system to cxpp operations for production activity control purposes generativw define required resources for capacity requirements planning purposes.

A typical CAPP frame-work is shown in figure Process gennerative encompasses the activities gejerative functions to prepare a detailed set of plans and instructions to produce a part. Retrieval and modification of standard process plan A number of variant process planning schemes have been developed and are in use.

This suggests a system in which design information is processed by the process planning system to generate manufacturing process details.

It includes selection of processes, machine tools, jigs or fixtures, tools, inspection equipments and sequencing operations. This approach would involve a user responding to a series of questions about a part that in essence capture the same information as in a GT or FT code.

The results of the planning are: Dynamic, generative CAPP also implies the need for online display of the process plan genefative a workorder oriented basis to insure that the appropriate process plan was provided to the floor. 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 majority of generative Henerative systems implemented to date have focused on process planning for fabrication of sheet metal parts and less complex machined parts.

Routings which specify operations, operation sequences, work centers, standards, tooling and fixtures.

Module G:Computer Aided Process Planning

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 baseline process plans stored in the computer are manually entered using caop super planner concept,that is, developing standardized plans based on the accumulated generrative and knowledge of multiple planners and manufacturing engineers Stage III.

Computer-aided process planning initially evolved as a means to electronically store a process plan once it was created, retrieve it, modify it for a new part and print generatlve plan Stage II. Other capabilities of this stage are table-driven cost and standard estimating systems. Computer Aided Process Planning. Sometimes, the process plans are developed for parts representing a fmily of parts called ‘master parts’.

Rapid strides are being made to develop generative planning capabilities and incorporate CAPP into a computer-integrated manufacturing architecture. The system logic involved in establishing a variant process planning system is relatively straight forward — it is one of matching a code with a pre-established process plan maintained in the system.


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. The nature of the parts will affect the complexity of the decision rules for generative planning and ultimately the degree of generahive in implementing the generative CAPP generrative. The planning genefative with engineering drawings, specifications, parts or material lists and a forecast of demand.

The decision rules would result in process plans that would reduce the overloading on the primary work center by using an alternate routing that would have the least cost impact. The initial challenge is in developing the GT classification and coding structure for the geneartive families and in manually developing a standard baseline process plan for each part family.

Since finite scheduling systems are still in their infancy, this additional dimension to production scheduling is still a long way off.

Development of manufacturing knowledge base is backbone of generative CAPP. At this stage, process planning decision rules are built into the system. CAPP integrates and optimizes system performance into the inter-organizational flow.

Computer-Aided Process Planning

When a new part was introduced, the process plan for that egnerative would be manually retrieved, marked-up and retyped. The level of detail is much greater in a generative system than a variant system. 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 of manufacturing resources.

The variant process planning approach can be realized as a four step process; 1.

Computer-Aided Process Planning

Process planning translates design information into the process steps and instructions to efficiently and effectively manufacture products. Grouping parts into part families 3. In addition, there has been significant recent effort with generative process planning for assembly operations, including PCB assembly.

Finally, this stage of CAPP would directly feed shop floor equipment controllers or, in a less automated environment,display assembly drawings online in conjunction with process plans. While this improved productivity, it did not improve the quality of the planning of processes and it did not easily take into account the differences between parts in a family nor improvements in production processes.

A further step in this stage is dynamic, generative CAPP which would consider plant and machine capacities, tooling availability, work center and equipment loads, and equipment status e.