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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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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 the plan Stage II. Fabrication and assembly drawings to support manufacture as opposed to engineering drawings to define the part. The level of detail is much greater in a generative system than a variant system.

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. 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.

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.

Process planning translates design information into the process steps and instructions to efficiently and effectively manufacture products. Rapid strides are being made to cappp generative planning capabilities and incorporate CAPP into a computer-integrated manufacturing architecture. Manufacturers have been pursuing an evolutionary path to improve and computerize process planning in the following five stages:.

Process plans which typically provide more detailed,step-by-step work instructions including dimensions related to individual operations, machining parameters, set-up instructions, and quality assurance checkpoints. Development of manufacturing knowledge base is backbone of generative CAPP. 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. In addition, there has been significant recent effort with generative process planning for assembly operations, including PCB assembly.

The process plan developed with a CAPP system at Stage V would vary over time depending on the resources and workload in the factory.

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. This system can be used to generate process plan for rotational, prismatic and sheet-metal parts. Similarly, in case of machine breakdown on the shop floor, CAPP must generate the alternative actions so that most economical solution can be adopted in the given situation.


This type of system uses work instruction displays at factory workstations to display process plans graphically and guide employees through assembly step by step.

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 converting part from raw material to finished state.

A number of methods have been developed for part family formation using coding and classification schemes of group technology GTsimiliarity-coefficient based algorithms gdnerative mathematical programming models.

CAD systems generate graphically oriented data and may go so far as graphically identifying metal, tenerative. This type of purely generative system in Stage V will involve the use of artificial intelligence type capabilities to produce process plans as well as be fully integrated in a CIM environment.

The baseline process plans stored in the computer are manually entered using a super planner concept,that venerative, developing standardized plans based on the accumulated experience and generxtive of multiple planners and manufacturing engineers Stage III. Process planning encompasses the activities and functions to prepare a detailed set of plans and instructions to produce a part. 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 first key to implementing a generative system is the development of decision rules appropriate for the items to be processed. At this stage, process planning decision rules are built into the system.

Generative Process Planning

The planner will add the remaining ten percent of the effort modifying or fine-tuning the process plan. 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. Retrieval and modification of standard process plan A number of variant fenerative planning schemes have been developed and are in use.

The initial challenge is in developing the GT classification and coding structure for the part families and in manually developing a standard baseline process plan for each part family. In a detailed survey of twenty-two large and small companies using generative-type CAPP systems, the following estimated cost savings were achieved:.

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. 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 Increased productivity of process planners Higher level application progams such as cost and manufacturing lead time estimation and work standards can be interfaced.


Simple geerative of generative planning systems may be driven by GT codes. The variant process acpp approach can be realized as a four step process; 1. Sometimes, the process plans are developed for parts representing a fmily of parts called ‘master parts’. The results of the planning are: 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.

A typical CAPP frame-work is shown in figure Since finite scheduling systems are still in their infancy, this additional dimension to production scheduling is still a long way off. The assembly is shown cqpp the screen and as a employee steps through the assembly process with a footswitch, the components to be inserted or assembled are shown on the CRT graphically along cappp text instructions and warnings for each step.

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. Computer Aided Process Planning. The system logic involved in establishing a variant geherative planning system is relatively straight forward — it is one of matching a code with a pre-established process plan maintained in the system.

Computer-Aided Process Planning

The tools that are widely used in development of this database are flow-charts, decision tables, decision trees, iterative algorithms, concept of unit machined surfaces, pattern recognition techniques and artificial intelligence techniques such as expert system shells. A second key to generative process planning is the available data related to the part generativw drive the planning. Dynamic, generative CAPP also implies the need for online display of the process plan on geherative workorder oriented basis to insure that the appropriate process cqpp was provided to the floor.

Other capabilities of this stage are table-driven cost and standard estimating systems. This routing becomes a major input genwrative the manufacturing resource planning system to define operations for production activity control purposes and define required resources for capacity requirements planning purposes.

These attributes allow the system to select a baseline process plan for the part family and accomplish about ninety percent of the planning work.

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

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