**3. Variant process planning**

Variant process planning consists of completing a certain scheme of indexing a designed part, which allows to find the most structurally and manufacturing similar component and take over its manufacturing process it with an insignificant number of adjustments. Such approach to process design shows its benefits when it is possible to classify manufactured machine parts in groups of parts, which are structurally and manufacturing similar. VCAPP is therefore closely linked to the group technology of machines and use of flexible manufacturing cells.

The effective use of flexible, robotized manufacturing cells is guaranteed by completion in such group technology idea systems. Hence, similarity of the machine parts processed there should be considered both at the stage of design, equipment and software configuration and during everyday use of the production cells. The Group Technology (GT) method has reached its mature form at the beginning of the 1990s [23]. Currently, GT is considered as a concept of production, in which production resource is functionally grouped in production cells for the purpose of processing machine parts with similar features in order to achieve a high level of production reproducibility and artificially extend the size of a production batch. GT is related to the cellular production [24] concept, which means production both in flexible manufacturing cells and in autonomous flex-cell. GT therefore involves a range of various operations of a design, production and organizational nature, which requires coherence and synchronization. Many of them, such as determining production similarity of machine parts, grouping and classification of machine parts, variant design, parametric programming of computer numerical control (CNC) machine tools, developing group manufacturing processes, designing group processing equipment, configuration of manufacturing cells [25] and the issue of planning and controlling the manufacturing process are still readily raised subject of development works.

The aforementioned class is therefore a temporary Petri network with a binary marking function and inhibitor arcs. Inhibitor arcs make the model simpler, more transparent, therefore, easier to build and analyze. The suggested module structure allows for automation in generating the model. Modules for replacement of tools in the number of tools used for the process control the need to replace a tool. Topologically identical modules of control of calling the Workpiece Coordinate System (WCS) should be identified as the position required by the production process and the orientation of a processed object in a machine coordinate system. A module of complex operations is the core of the model. Each transition in the module calls a tool and WCS for the subsequent complex operation. A subsequent module is a sequence of operations conducted using the same tool on subsequent features. The modules is an area for structural optimization of the process by way of minimizing the number of tool changes. The model is supplemented by modules classifying simple operations for individual features. A marker on the last item of a module means ending processing of a

The aforementioned issue of optimizing the structure of multi-tool production operations might be solved using two simple heuristics: give preference to the tool that might currently process the largest possible number of areas and give preference to the tool that might currently complete all the operations that have been assigned to it. The suggested approach allows for a satisfying sequence of simple operations with a small number or iterations equal to the number of tools used. It is an optimal sequence in more than 95% cases. In order to appreciate the benefits of this method, one can compare it to the full browsing algorithm. The advantages of this method also include a very simple method of transferring its results in the

The sequence of processing individual features might be conditional on their technological nature. An opportunity to automatically classify the conducted operations then requires initiating the optimizing procedure. A function of priorities assigned to each transition is used for this purpose. Example use of this method based on genetic algorithm is shown in the work [22].

Variant process planning consists of completing a certain scheme of indexing a designed part, which allows to find the most structurally and manufacturing similar component and take over its manufacturing process it with an insignificant number of adjustments. Such approach to process design shows its benefits when it is possible to classify manufactured machine parts in groups of parts, which are structurally and manufacturing similar. VCAPP is therefore closely linked to the group technology of machines and use of flexible manufacturing

The effective use of flexible, robotized manufacturing cells is guaranteed by completion in such group technology idea systems. Hence, similarity of the machine parts processed there should be considered both at the stage of design, equipment and software configuration and during everyday use of the production cells. The Group Technology (GT) method has reached its mature form at the beginning of the 1990s [23]. Currently, GT is considered as a concept of production, in which production resource is functionally grouped in production cells for the

form of an organized sequence of complex operations to a formal network model.

given feature.

42 Petri Nets in Science and Engineering

**3. Variant process planning**

cells.

Technical implementations of VCAPP systems most frequently include one of the two solutions: building a system based on finding a similar part of a previously manufactured machine part and adopting its production process plan or developing a group production process for the so-called synthetic representative of the group. In both cases, it is possible to use a process model developed in the Petri network technique; however, the second method is more natural in using its potential.

Feature precedence network (FPN) defined as a directed graph representing precedences that result from limitations imposed by the features is a precondition for designing a correct manufacturing operation. For complex parts, with a large number of processed features and relations between them, FPN might be very complex and very difficult to manually process. In [26, 27] has developed a system generating FPN based on the analysis of interactions between the features and verification of FPN using the Petri network model. The developed structure involves generating features by way of mapping from CAD system, analysis of interactions between the features and an algorithm automatically creating a Petri network corresponding to a given FPN. An analysis of interaction between the features involves comparing each pair of features with reference to the defined set of rules. These rules include heuristic preferences of processing sequence, which guarantee its effectiveness. The rules take geometric, production and economic factors into account.

In case of variant approach to production process design FPN represents a model developed for the synthetic representative of a given group of machines. The synthetic representative represents an abstract object that includes all types of features that can be found in the group of parts with production similarities. The process model should allow for an explicit definition of a processing task only by way of correct positioning of initial marking vector M0 . The sequence of processing individual features is defined based on the FPN. Subsequent, structurally unified modules of the model supplement the remaining functions of the model. The work [28] elaborates on this issue and gives an example of the variant approach for axially symmetrical parts.
