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.
|Published (Last):||9 October 2018|
|PDF File Size:||5.2 Mb|
|ePub File Size:||12.14 Mb|
|Price:||Free* [*Free Regsitration Required]|
Routings which specify operations, operation sequences, work centers, standards, tooling and fixtures. 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 similiarities in design attributes and manufacturing methods are exploited for the purpose of formation of part families. 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.
Definition of coding scheme 2. 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 a detailed survey of twenty-two large and small companies using generative-type CAPP systems, the following generatiive cost savings were achieved: This suggests a system in which design information is processed by the process planning system to generate manufacturing process details. CAPP is a highly effective technology for discrete manufacturers with a significant number of products and process steps. Ccapp planner will add the remaining ten percent of the effort modifying or fine-tuning the process plan.
Computer-Aided Process Planning
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. However, variant CAPP is based on a Group Technology GT coding and classification approach to identify a larger number of part attributes or parameters.
Process knowledge in form of in the form of decision logic and data matches the part geometry requirements with the manufacturing capabilities using knowledge base. Rapid strides are being made to develop generative planning capabilities and incorporate CAPP into a computer-integrated manufacturing architecture. Significant benefits can result from the implementation of CAPP.
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. When a new part was introduced, the process plan for that gnerative would be manually retrieved, marked-up and retyped.
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. 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.
This routing becomes a major input to the manufacturing resource planning system to define operations for production activity control purposes and define required resources for capacity requirements planning purposes. 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.
At this stage, process planning decision rules generattive built into the system. Since finite scheduling systems are still in their infancy, this additional dimension to production scheduling is still a long way off. The nature of the parts will affect the genrrative of the decision rules for generative planning and ultimately the degree of success in implementing the generative Gnerative system.
The first step is the implementation of GT or FT classification and coding. The results of the planning are:. 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.
There are two major components of generative CAPP; a geometry based coding scheme and process knowledge in form of decision logic data.
Computer-Aided Process Planning
Process planning encompasses the activities and functions to prepare a detailed set of plans and instructions to produce a part. The geometry based coding scheme defines gnerative geometric features for process related surfaces together with feature dimensions, locations, tolerances and the surface finish desired on the features. 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.
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.
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.
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. This type of system uses work instruction displays at factory workstations to display process plans graphically and guide employees through assembly step by step. Further,this graphically-oriented data can then be yenerative to manufacturing in the form of hardcopy drawings or work instruction displays.
This system can be used to generate process plan for rotational, prismatic and sheet-metal parts.
Generative Process Planning
The process plan developed with a CAPP system at Stage V would vary over time depending on the resources and workload in the factory.
CAPP integrates and optimizes system performance into the inter-organizational flow. These attributes allow the system to select a baseline process plan for the part family and accomplish about ninety percent of the planning work. Fabrication and assembly drawings to support manufacture as opposed to engineering drawings to define the part. A second key to generative process planning is the available data related to the part to drive the planning. 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.
Other capabilities of this stage are table-driven cost and standard estimating systems. The initial challenge is in developing the GT classification and coding structure for the part families and in geenerative developing a standard baseline process plan for each part family. The planning begins with engineering drawings, specifications, parts or material lists and a forecast of demand. Sometimes, the process plans are developed for parts representing a fmily of parts called ‘master parts’.
For geherative, 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. This is the function of CAPP.