Computer Aided Process Planning Capp Computer Science Essay

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INTRODUCTION

Process planning is common task in discrete manufacturing. It is performs the task of determining the sequence of individual manufacturing operations needed to process a given part or product. The resulting operation sequence is documented on a form typically referred to as a route sheet. The route sheet is a listing of the production operations and associated machine tools for a workpart or assembly. In traditional process planning, there arises a problem of variability among planners. In addition to this, there are often difficulties in the conventional process planning procedure. New machine tools in the factory render old routings less than optimal. Machine breakdowns force shop personnel to use temporary routings and these become the documented routings even after the machine is repaired. For these reasons and others, a significant proportion of the total numbers of process plans used in manufacturing are not optimal. Because of the problems encountered with manual process planning, attempts have been made in recent years to capture the logic, judgment, and experiences required for this important function and incorporate them into computer programs. Based on the characteristics of a given part, the program automatically generates the manufacturing operation sequence. A computer aided process planning (CAPP) system offers the potential for reducing the routine clerical work of manufacturing engineers. At the time, it provides the opportunity to generate production routing which is rational, consistent, and perhaps even optimal. (Groover)

CAPP

Modern manufacturing is characterized by low volume, high variety production and close tolerance high quality products. Computer Integrated Manufacturing (CIM) is recognized as an effective platform for increasing manufacturing competitiveness. Computer Aided Process Planning is an essential key for achieving CIM. The integration of design, computer aided process planning (CAPP) and production planning and control (PPC) is becoming essential especially in a concurrent engineering environment where many product life cycle factors are of concern. An overview of the major development thrust in CAPP is presented along with some of the evolving trends and challenges such as rapid, generic, dynamic and/or distributed process planning. Related issued of quality and evolving standards are also discussed.

CAPP works at the interface between CAD and Cam. It takes Cad data, converts it to production data, and feeds the later to a production system. Fig shows a CAPP model based on this interface concept. The CAPP model utilizes the flow shown in the fig. to convert Cad data into production data.

After the CAD model is created, it is prepared for transfer into CAPP model. This preparation step is performed by a preprocessor, and it could involve producing an IGES or STEP file that the CAPP model can read. This step is necessary because both the models are independent of each other. CAD data also needs to be prepared to obtain the proper product definition as required by the CAPP model.

The CAPP model applies its knowledge and rules to the prepared CAD data to produce its output, the process plan.

The CAPP model performs necessary post processing operations on its output to produce output that production and scheduling systems can read and utilize in their own activities.

Fig. shows that the components of the CAPP model are independent of both the CAD and production system. Thus the model requires two conversion steps: one to convert Cad data, and the other to convert the CAPP output itself. (Mastering CAD/CAM, Ibrahim Zeid)

CAD system

Pre-processor

Production planning and scheduling

Postprocessor

Planning rules

Input

Output

CAPP

Knowledge

CAPP model

CAPP Approaches:

(1) Variant CAPP (also called as Retrieval-type approach)

Retrieval type CAPP systems use parts classification and coding and group technology as a foundation. In this approach, the parts produced in the plant are grouped into part families, distinguished according to their manufacturing characteristics. For each part family, a standard process plan is established. The standard process plan is stored in the computer files and the retrieved for new workpart which belong to that family. Some form of parts classification and coding system is required to organize the computer files and to permit efficient retrieval of the appropriate process plan for a new workpart. For some new work part, editing of the existing process plan may be required. This is done when the manufacturing requirements of the new part are slightly different from the standard. The machine routing may be the same for the new part, but the specific operations required at each machine may be different. The complete process plan must document the operations as well as the sequence of machines through which the part must be routed. Because of the alterations that are made in the retrieved process plan, these CAPP systems are sometimes also called by the name "variant systems.''

Part family matrix file

Part family search

User enters part code number.

Machine routing file

Standard machine routing retrieve

Operation sequence file

Standard operation retrieve/edit

Other application programs

Process plan

Process plan formatter

Figure will help to explain the procedure used in a retrieval process planning system. The user would initiate the procedure by entering the part code number at a computer terminal. The CAPP program then searches the part family matrix file to determine if a match exists. If the file contains an identical code number, the standard machine routing and operation sequence are retrieved from the respective computer files for display to the user. The standard process plan is examined by the user to permit any necessary editing of the plan to make it compatible with the new part design. After editing, the process plan formatter prepares the paper document in the proper form.

If an exact match cannot be found between the code numbers in the computer file and the code number for the new part, the user may search the machine routing file and the operation sequence file for similar parts that could be used to develop the plan for the new part. Once the process plan for a new part code number has been entered, it becomes the standard process for future parts of the same classification.

In figure the machine routing file is distinguished from the operation sequence file to emphasize that the machine routing may apply to a range of different part families and code numbers. It would be easier to find a match in the machine routing file than in the operation sequence file. Some CAPP retrieval systems would use only one such file which would be a combination of operation sequence file and machine routing file.

The process plan formatter may use other application programs. These could include programs to compute machining conditions, work standards, and standard costs. Standard cost programs can be used to determine total product costs for pricing purpose.

A number of variant type CAPP systems have been developed. These include MIPLAN, one of the MICLASS modules, the CAPP system developed by Computer Aided Manufacturing-International, COMCAPP V by MDSI, and systems by individual companies.

(2) Generative process planning systems

Generative process planning involves the use of the computer to create an individual process plan from scratch, automatically and without human assistance. The computer would employ a set of algorithms to progress through the various technical and logical decisions toward a final plan for manufacturing. Inputs to the system would include a comprehensive description of the workpart. This may involve the retrieval of part code number to summarize the workpart data, but it does not involve the retrieval of existing standard plans. Instead, the generative CAPP system synthesizes the design of the optimum process sequence, based on an analysis of part geometry, material, and other factors which would influence manufacturing decisions.

In the ideal generative process planning package, any part design could be presented to the system for creation of the optimal plan. In practice, current generative-type systems are far from universal in their applicability. They tend to fall short of truly generative capability, and they are developed for a somewhat limited range of manufacturing processes.

Need for the integration of process planning and scheduling.

Existing CAPP systems fail to incorporate scheduling while generating a process plan. Scheduling is done separately after the process plan has been generated, and therefore, it is possible that process plans so generated may not be optimal from the scheduling point of view. If process plans are generated without consideration of job shop status information, many problems arise within the manufacturing environment. Some of the difficulties encountered are

as follows:

(Journal of Materials Processing Technology 138 (2003) 297-300

* Corresponding author.

E-mail address: mkumargupta@rediffmail.com (M. Kumar).

0924-0136/03/$ - see front matter # 2003 Elsevier Science B.V. All rights reserved.

doi:10.1016/S0924-0136(03)00088-8)

(i) Process planners assume an ideal factory with unlimited resources on the shop floor. They plan for the most recommended alternative process. Thus, desirable machines are selected repeatedly by various process planners. As scheduling follows the process planning, actual process plans when carried out result into queues at various workstations and thus these optimal process plans become infeasible.

(ii) Often process planning and scheduling have conflicting objectives. Process planning emphasizes the technological requirements of a task, while scheduling involves the timing aspects of it.

(iii) The throughput target of orders in a workshop often suffers from disruptions caused by bottleneck machines, non-availability of tools and personnel, or breakdown of machines and equipment. A readily generated schedule becomes invalid and has to be regenerated.

(iv) In most of the cases for both process planning and scheduling, a single criterion optimization technique is used for determining the best solution. However, the real production environment is best represented by considering simultaneously more than one criterion.

(v) The time delay between planning phase and execution phase may cause trouble. Due to the dynamic nature of a production environment, it is very likely that when a design is ready to be manufactured, the constraints that were used in generating the plan have already changed greatly, thus rendering, that plan sub-optimal or totally invalid.

Many researchers have attempted contributions to integrate process planning with scheduling. Some of the work done in this direction are by Torri et al. [11], Halevi and Weill [13], Chryssolouris and Chan [6], Sundaram and Fu [10], Tonshoff et al. [14], Khoshnevis [15], Khoshnevis and Chen [16], Liao et al. [5], Usher and Fernandes [17],Gu et al. [18] and Yang et al. [19].

Investigations have shown that 20-30% of the total shop

load in a given period has to be redirected to alternative

machines to attain the desired output target [5]. Only a small

part of the job shop orders actually comply with the production

plan. This implies that 20-30% of all process plans are

not valid and have to be altered when production starts.

There is thus a major need for an integrated process planning

and scheduling system. A process planning system should

interface with a scheduling system for generating more

realistic process plans and schedules. In doing so, the

efficiency of the manufacturing system as a whole is

expected to improve. Without the integration of process

planning and scheduling, a true CIM system, which strives to

integrate the various phases of manufacturing in a single

comprehensive system will not effectively materialize

[11,12].

Many researchers have attempted contributions to integrate

process planning with scheduling. Some of the work

done in this direction are by Torri et al. [11], Halevi and

Weill [13], Chryssolouris and Chan [6], Sundaram and Fu

[10], Tonshoff et al. [14], Khoshnevis [15], Khoshnevis and

Chen [16], Liao et al. [5], Usher and Fernandes [17],Gu et al.

[18] and Yang et al. [19].

However very few of these approaches reported above consider machine capacity and

the current status of the shop while generating a process plan. Scheduling is done separately after the process plan is generated and, therefore, it is possible that process plans so generated are either not feasible or sub-optimal from the scheduling point of view. In some of the cases where alternative process plans are generated in conjunction with

satisfaction of scheduling criteria, the solution search space increases. This increases the time required to generate an optimal plan and schedule and renders it impractical for real

time applications. This work tries to investigate the above highlighted points.

3. Methodology

This paper suggests a method for integrating scheduling with CAPP by considering the shop floor conditions of the machines, i.e., availability, initial cost, cost of operation,

cycle time and breakdown condition while assigning machines to various processes to develop process plan This helps in generating process plans that are feasible with

respect to the current availability of the production facilities. In this method real time status of shop floor is crucial and dynamic feedback is required for scheduling. This method

may be called on-line process planning [7,20].

4. On-line machine scheduling

This step involves modification of the process decision rule to ensure that the machine that is assigned to perform an operation is the best possible machine from among all the

alternatives in the shop, after the scheduling criteria have been taken into account. The machines that are capable of achieving the same tolerance or surface finish requirements

without violating the process planning criteria are the alternatives for a particular operation.

The scheduling criteria considered here are the mean flow time and the number of tardy jobs. The integration of CAPP and scheduling is expected to reduce both the mean

flow time and the number of tardy jobs. This results in rapid response to demand and closer adherence to deadlines.

In this system a scheduling factor, m, is developed as :

m ¼

X1C

X2CoX3TX4N

where C is the cost of the machine, Co the operating cost of machine per unit time, T the average cycle time for performing the operation on a machine, and N the number of

alternative machines that can prepare the job. X1-X4 are the important ratings given to respective variable on a scale of 1-10 (1-least important and 10-most

important). The machine with the highest value of scheduling factor is

selected for a particular operation. This factor is directly

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