The Computer Aided Process Planning

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)

Computer-Aided Process Planning (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


Production planning and scheduling


Planning rules





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.

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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.

The integration of process planning and scheduling.

Kumar & Rajotia, (2003, p.297) contend that existing CAPP systems fails to consider scheduling while developing a process plan. It is done separately after the process plan has been generated, and therefore, it is possible that process plans so obtained may not be most favourable from the scheduling point of view. If process plans are generated without careful thought of machine shop floor information, many problems arise within the manufacturing environment. Some of the difficulties encountered are as follows:

(i) Process planners assume that there are unlimited resources on the shop floor. Hence they plan for the optimum alternative process. Hence there is reputation in the selection of desirable machines by the process planners. When these process plans are executed, it results into an ideal machines and overloaded machines at shop floor and thus these optimal process plans become infeasible.

(ii) Basically process plans gives importance to the technological requirements of the task while scheduling involves the timing feature of it. This results into the conflicting objectives of the two.

(iii) The flow of the orders through the workshop suffers from disruptions caused by bottleneck machines, non-availability of tools and personnel, or breakdowns of machines and equipments. Hence the ready schedule becomes invalid and it has to be recreated.

(iv) In many cases for both CAPP and scheduling, a single criteria optimization should be used to obtain desirable solutions. However, the real time production surrounding is best represented by considering simultaneously more than one criterion.

(v) The time difference between the planning phase and execution may lead to difficulties. Due to the dynamic nature of production surroundings, it is very likely that when the design is prepared to manufacture, the constraints used in developing the plan have already been altered greatly, thus making the plan sub-optimal or totally disabled.

Many researchers have tried to integrate process planning with scheduling. Some of the important contributors are by Torri et al. Halevi and Weill , Chryssolouris and Chan , Sundaram and Fu, Tonshoff et al., Khoshnevis , Khoshnevis and Chen , Liao et al., Usher and Fernandes ,Gu et al. and Yang et al.


The method to integrate scheduling with CAPP by including the shop floor conditions of machines, i.e., initial cost, availability, operating cost, cycle time and breakdown conditions while allotting machines to various processes to obtain process plan is explained in this paper. This assists in developing feasible plan. This method may be called on-line process planning.

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On-line machine scheduling

This step involves the alteration of the process to ensure that machine assigned is the best possible option among the others to perform the task after the scheduling criteria is considered. The selected machine should not violate the process planning criteria i.e. it should be capable to achieve the required tolerance and surface finish for the particular operation.

The expected result of integration is to response rapidly and closer adherence to deadlines by reducing the mean time flow and the number of tardy jobs.

In this system a scheduling factor, µ, is obtained as:

Where C = cost of the machine,

Co= operating cost of machine per unit time,

T= the average cycle time for performing the operation on a machine,

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 proportional to C and inversely proportional to Co, T and N.

The rationale for the direction of proportionality in this equation is explained below.

Cost of machine (C): the purchasing value of the machine. It is important to utilize the company’s investment effectively. Thus, scheduling factor prefers the expensive machines more.

Operating cost (Co): the assignment of operating cost of the machine is an important factor and a machine with lower operating cost is preferred.

Cycle time (T): the number of machines with lower cycle time is preferred since they reduce the mean flow time and the number of tardy jobs. The scheduling factor optimizes when the cycle time for regarding machine decreases.

Number of alternative machines (N): the machine with lower number of alternatives improves the scheduling factor.

Initially, the ideal scheduling factor is calculated under ideal working conditions known as ideal scheduling factor (µI). Ideal working conditions includes ideal tools, machines, cycle time etc. However, in a real time, the working condition may be distinguishable. The scheduling must try to include the actual number of machines with their capacities and features, tools, etc. Based on actual conditions, the actual scheduling factor (µA) is calculated.


Ideal scheduling factor

Where CIo is the ideal operating cost, and TI the ideal cycle time Actual scheduling

Where CAo =actual operating cost

TA= actual cycle time.

The actual scheduling factor is calculated for all machines competent to do the required operation and the machine with larger value is opted for that operation. The procedure can be summarized as follows:

Step 1. Verify for the breakdown condition of machines. A machine under breakdown or maintenance is not selected for assignment.

Step 2. Check for the availability of each machine. A machine is considered unavailable when the cycle time of an operation (T) is longer than the time available on the machine (unassigned slots of time on the specific machine). Operation is not assigned for the unavailable machine.

Step 3. Check capability of available machines by verifying its accuracy and surface finish produced, available feeds and speeds, dimensional limits and attachments.

Step 4. Based on the scheduling factor, transform the ideal process plan into an actual process plan.

A hybrid approach to CAPP:

The various advantages, disadvantages, features, nuances of a certain type of system are a function of the application more than an inherent quality. This is primarily because we are trying to replicate the human brain of the production planner with an Artificial Intelligence unit. When a person designs the algorithm for a certain type of process, the same might not apply for another process or even the same process – but under a different circumstance. Thus this algorithm is clearly at a loss when we use any one structured and rigid format, and is extremely vulnerable to make critical mistakes to changes. This might very well be expensive enough a mistake to offset the cost of automation of the process. Hence, the Hybrid Approach was designed in an attempt to make the algorithm a bit more flexible. This might not have the outright simplicity and speed of a variant approach or the reliability of the generative approach, but it attempts to make up for that by incorporating a high degree of flexibility as far as adaptation is concerned.

The concept is that if we manage to eliminate the demerits of both or other approaches and form an adaptive approach with the merits of all, we should have basic layout of a much more efficient approach to planning of CAPP, or in effect the integration of the processes right from design (CAD) to manufacture (CAM).

This is attempted primarily by associating the work-piece in a family like the variant approach, however not as a rigid classification, but only as a generic classification. Here on the approach leans towards the generative approach and accesses predetermined information of all the aspects of manufacturing the particular family of parts. This leaves the designer to make the critical yet quick changes to the essential variables that are involved with the manufacture of the part. The goal is not to generate a definitive path or plan, but to quickly make available an efficient, reliable and feasible skeleton of the required ideal process plan.

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Hybrid approaches generally follow a heuristic approach where the critical input is the previous output, also known as discovery based decision making. This gives a good opportunity to learn from past experience and results. Thus, as the volumes of production are increased for similar parts, the data available is increased and as a consequence the efficiency of the hybrid approach also increases.

Hybrid CAPP Systems:

There are many different hybrid approaches applied to production processes in order to gain a seamless flow between CAD, CAM, CAPP and such elements of production process.

Pham and Gologlu (2005) designed a hybrid system of CAPP called Proplanner, which adapted the hybrid method of knowledge representation. According to Xun Xu (2009), “ProPlanner is restricted to prismatic parts with 2.5-dimensional features. Parts are also assumed to be machined from a near net form, and only simple geometric tolerance (straightness and parallelism) is implemented. Gologlu (2004) extended the ProPlanner system, by using an efficient heuristic algorithm (in the system operation sequencing module) for finding near-optimal operation sequences from all available process plans in a machining set-up. In the adopted approach, a four-level hierarchy was used: feature-level, machining scheme level, operation-level and tool-level”

“Liu, Duan, Lei and Wang (1999) used the analytic hierarchy process (AHP) – a mathematical decision modelling tool – to solve complicated process planning problems by decomposition, determination and synthesis.” (Xun Xu, 2009)

Future adaptations of CAPP related to Hybrid approach:

The future adaptations of CAD-CAM integration will be largely driven by the requirements of future and the remnant disadvantages of the present systems. The major current challenges that are attempted to be overcome are:

Requirement of many post processors for every level of local customization for a part

Lack of standardization of syntax

Lack of co-operation and common platform development due to commercial environment

The potential of the Hybrid Approach to overcome the above:

The inherent nature of hybrid systems gives us an advantage to bridge the gaps between non-standard communication lines and to force various independent systems to work together. This in itself is an advantage, however true synchronization can only be achieved with a common effort in the larger interest of more efficient CAPP frameworks.

Various efforts to overcome barriers of independent non-standard systems:


A general purpose language NC program that is independent of the manufacturer. This was a public domain code post-processor that is defined by the ANSI standard. APT was one of the early attempts to drive the machining process on the basis of geometry (Xun XU, 2009).


“BCL is the numerical control data format standard initiated by North American Rockwell

in the mid-1970s, and later became EIA Standard RS-494 in 1983″ (Xun Xu, 2009)

The co-ordinate system of a tool remains focused on the information that was originally used as the input. Though the system was relatively capable of achieving its goals, at was mainly restricted to the shopfloor.

Common platform languages for programming automation tools

There have been efforts to make CNC programs portable by use of coding languages that use basic G-codes, which in itself fail to match the merits of higher level languages. APL (Otto, 2000) and OMAC (Michaloski, Birla, Yen,Igou & Weinert, 2000) are examplesof such efforts.

This concept is based on the common platform on which all decision making processes are based on when planning a process, a typical example of which is entailed as follows:


The problem remains largely to be the lack of synchronization among independent hardware and software elements of the entire system and this force the prospective improvers of CAPP systems to again focus on the ideal framework of a production process and then work their way to try and develop a practical, economical and commercially viable system. It is our belief that in a hybrid approach, such a production engineer will be breaking down the entire integration of CAD and CAM into smaller ‘ideal flowcharts’. This ideal flow of processes would be similar to the following example of a post design flowchart –







(Figure 1, Ideal flow chart of post-design sequence)

Conclusions and Inferences:

This is not to say that the conventional approaches contain demerits and have to be phased out. In fact, the hybrid approach is based on the above for a foundation. It is merely adaptation of techniques based on past experience, changing situations and increasing research. The changes will be incorporated on to present techniques and the same will be done to the hybrid approach based on need. This heuristic approach of adapting continuously and seamlessly with the workflow that integrates design and manufacture is believed to be the future of process planning, which will surely continue to undergo many further changes. However the tendency of one defined system to dissociate itself with the algorithm of another will be drastically reduced in the future. This will make the production process act as one harmonic set of functions rather than various scattered processes which may do well in their own right, but are not functioning in symphony with the rest of the processes.

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