Why computer-aided process planning? As mentioned earlier, the primary purpose of process planning is to translate the design requirements into manufacturing process details. This suggests a feed forward system in which design information is processed by the process planning system to generate manufacturing process details. Unfortunately, this is not what is expected in a concurrent engineering environment, whose goal is to optimise the system performance in a global context. Therefore, there is a necessity of integrating the process planning system into the inter-organisational flow. For example, if changes are made to a design, one must be able to fall back on a module of CAPP to quickly re-generate the cost estimates for these design changes. Similarly, if there is a breakdown of a machine(s) on the shop-floor, the process planning system must be able to generate alternative process plans so that the most economical solution for the situation can be adopted. Chapter VII gives a detailed account of such an integrated environment. In such a setting of a multitude of interactions among various functions of an organisation and dynamic changes that take place in these sub-functional areas, the use of computers in process planning necomes essential (Singh, 1996).
By comparison with manual experience-based process planning, the use of computers in process planning also helps to achieve the following:
• Systematically producing accurate and consistent process plans;
• Reducing the cost and lead-time of process planning;
• Reducing the skill requirements of a process planner;
• Increasing productivity of a process planner;
• Being able to interface and integrate with application programs such as cost and manufacturing lead-time estimation and work standards.
Two major methods are used in CAPP. They are the variant method and generative method.
Variant.CAPP.Method
In the variant process planning approach, a process plan for a new part is created by recall-ing, identifying and retrieving an existing plan for a similar part and making necessary modifications for the new part (Figure 3.4). Quite often, process plans are developed for families of parts. Such parts are called master parts. The similarities 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. Among them, GT (Group Technology) is the most commonly used. Figure 3.5 shows different rotational parts that can be machined on the same lathe. A change of parts in this family would only require a new part program to generate a new contour. A tool change in this case probably
Figure 3.4. The variant CAPP approach
would not be necessary. Figure 3.6 shows cubical parts that are not very similar any more;
however, they also form a production family as they can be made on the same multi-axis machining centre, requiring the same tools.
Figures 3.7 and 3.8 show two part families for electrodes that are used in an EDM (Electrical Discharging Machining) process. Note the difference and similarity between these two part families. Both families of parts have the same base. The parts in family A however, have side-faces that are not vertical, whereas those in family B are.
Thus, the variant process planning approach can be realised as a four-step process,
• define the coding scheme;
• group the parts into part families;
• develop a standard process plan; and
• retrieve and modify the standard plan.
Figure 3.5. Rotational part family requiring similar turning operations
Figure 3.6. Similar cubical parts requiring similar milling operations
Figure 3.7. Electrode part family A
There are different types of coding methods for classification of parts in Group Tech-nology. These methods present a systematic process of establishing an alphanumeric value for parts on the basis of selected part features. Classification is then done through grouping of parts according to code values. Generally speaking, the following code structures are used,
• Hierarchical: The interpretation of each symbol depends of the value of the preced-ing symbols
• Chain:.The interpretation of each symbol in the sequence is fixed
• Hybrid: Use of combination of the hierarchical and chain-type structures Figure 3.8. Electrode part family B
Figure 3.9. Monocode structure
T otal p arts population
M achined par ts
0 Form ed par ts
1 S heet m etal
2 R aw m aterial
3
R otational m achined par ts
0
N on -rotational m achined par ts
1
0 < L/D < 0.5
0 0.5 < L/D < 1
1 3 < L/D < 4 4
0 < L/W < 1
0 5 < L /W < 8
1 < L/W < 3 3 1
L – length; D – d iam etre; W - - width
The hierarchical code structure (called a Monocode) (Figure 3.9), divides all parts of the total population into distinct subgroups of about equal size. The number of digits in the code is determined by the number of levels in the tree. The advantage of the hierarchi-cal structure is that a few code numbers can represent a large amount of information. The singular disadvantage is the complexity associated with defining all the branches.
The chain structure, called a polycode, is created from a code table or matrix like the example shown in Figure 3.10. The type of part feature and digit position is defined by the left vertical columns. The numerical value placed in the digit position is determined by the feature descriptions across each row. The major advantages of polycodes are that they are compact and easy to use and develop. The primary disadvantage is that, for comparable code size, a polycode lacks the detail present in a hierarchical structure. A hybrid code captures the best features of the hierarchical and polycode structures.
Although variant process planning is quite similar to manual experience-based plan-ning, its information management capabilities are much superior because of the use of computers. Advantages of the variant process planning approach include,
• Efficient processing and evaluation of complicated activities and decisions, thus reducing the time and labour requirements;
• Standardised procedures by structuring manufacturing knowledge of the process planners to company’s needs;
• Lower development and hardware costs and shorter development times. This is es-pecially important for small and medium-sized companies whose product variety is not high.
The obvious disadvantages of the variant process planning approach are,
• Maintaining consistency in editing is difficult;
• Adequately accommodating various combinations of material, geometry, size, preci-sion, quality, alternative processing sequences and machine loading, is difficult;
Figure 3.10. Polycode structure
• The quality of the final process plan generated depends to a large extent on the knowledge and experience of the process planners. This dependence on the process planners makes automation impossible and is considered as one of the major short-comings of the variant process planning approach.
Generative.CAPP.Method
In the generative approach, process plans are generated by means of decision logic, for-mulas, technology algorithms and geometry-based data to uniquely perform processing decisions. The knowledge-based CAPP system is most commonly used. It refers to a computer program that can store knowledge of a particular domain and use that knowledge to solve problems from that domain in an intelligent way. In such a system, computers are used to simulate the decision process of a human expert.
There are two major problems to be solved: knowledge representation and inference mechanism. The knowledge representation is a scheme by which a real-world problem can be represented in such a way that the computer can manipulate the information. For example, in defining a part, the presence of a hole may be sought for. Given that there is a hole, we then define the attributes of the hole, such as the type of hole, the length and the diameter. The reason for this is that the computer is not capable of reading the design from blueprints or databases as humans are. The inference mechanism is the way in which the computer finds a solution. One approach is based on IF-THEN structured knowledge. For example, IF there is a hole, THEN a drill may be used. When more technical information is considered, a rule for finish-machining a hole may be written as,
“.nishing_operation for a hole:
which read, “if the tolerance grade of the hole is between IT8 and IT9, surface finish between Ra0.8 and Ra1.6, roundness between 0.003 and 0.01, cylindricity between 0.0003 and 0.008, and straightness between 0.0008 and 0.0012, then a finishing cut is needed proceeding a rough cut.
Through this type of knowledge, the computer can infer what operations are needed.
Once the operations are known, it is easy to calculate other details and the process plan can be developed. Other aspects of a knowledge-based system include the interface, which contains the user interface, the interface with the CAD database and the inquiry facility that explains why a decision is made.
Decision tables provide a convenient way to facilitate a knowledge-based CAPP system.
The elements of a decision table are conditions, actions and rules. They are organised in the form of an allocation matrix as shown in Table 3.1, where the conditions state the goals we want to achieve and the actions state the operations we have to perform. The rules, formed by entry values according to the experience of experts, establish the relationship between conditions and actions. Entries can be either Boolean-type values (true, false and do not care) or continuous values. The decision-making mechanism works as follows: for
a particular set of condition entries, look for its corresponding rule, and from that rule determine the actions. Table 3.2 illustrates a decision table for the selection of lathes or grinding machines for jobs involving turning or grinding operations (Singh, 1996). Given the condition that the lot size of the job is 70 units; diameter is relatively small; the surface roughness desired is 30 µm; and the tolerance range required is ± 0.005 mm, it is easy to see from the table that rule 3 matches this situation. The action, therefore, is obviously turret lathe; that is, the operation is performed on a turret lathe. Chapter XVII presents a host of technologies that have been developed and employed in the development of various CAPP systems.