An integrated process planning and robust fixture design system 5

Chapter Optimal Set-up Planning 5.1 Introduction Set-up planning is a function of both process planning and fixture design (Ong and Nee, 1994). Its task is to determine the number and sequence of set-ups, the features to be machined in each set-up, and the part orientation and locating features of each setup. The purpose of a set-up plan is to locate and fix a part in a specific manner on a machine tool so that machining can take place according to design specifications. Two factors have to be considered in set-up planning, design specifications and manufacturing resources. Design specifications include workpiece geometry, dimension, tolerance, and features which can be both functional and aesthetic. Manufacturing resources include production requirements, available machines, cutting tools, and fixtures. A set-up plan which considers all these factors optimally can ensure to deliver the product with not only high quality but also high throughput rate and low cost. From published work, these two factors of set-up planning are treated separately. Most research attempted to satisfy the first factor, i.e., analysis of the design specifications, including tolerance analysis, precedence constraint satisfaction, geometric data analysis, and tool access direction verification. The main objective of these studies is 81 Chapter Optimal Set-up Planning to reduce the locating error and minimize the number of set-ups. The second factor was normally considered at the optimization stage in terms of cost, quality and lead time, and under an assumption of the availability of certain machine tools. Different set-up plans can be generated in a different manufacturing environment. Different set-up plans may also lead to different locating methods and manufacturing cost, and different fixture configurations can result in different locating stack-up errors and stability. Machining accuracy and the capability of available machine tools would need to be considered simultaneously during set-up planning in order to achieve a higher level of optimization. An optimized set-up plan can eliminate unnecessary machining error stack-up, improve product quality and reduce production cost. In this chapter, an optimized set-up planning approach which considers machining error stack-up and the capability of available machine tools simultaneously is addressed. It is assumed that a machining environment contains several machine resources which include 3-, 4- or 5-axis machine centers, and can be distributed and located in different places. A tolerance cost factor, which will be applied in the case of a stack-up, has been introduced. The strategies are achieved by minimizing a cost model among the distributed machine resources. 82 Chapter Optimal Set-up Planning 5.2 5.2.1 Set-up Planning System Consideration of Design Specifications Set-up planning should satisfy the design specifications, i.e., geometric, dimensional and tolerance requirements, precedence constraint satisfaction, and tool approach direction (TAD) verification. Product design information in a CAD model would need to be recognized and extracted before set-up planning. In this research, hole and plane machining features, which commonly exist on a cast part, are considered. The heuristics used for reasoning the hole and plane features are shown in Table 3.2 in Chapter 3. The TAD of a feature is determined by searching for any intersection entities in the candidate direction with a ray which has a radius similar to the cutter. If the result is negative, the candidate direction can be considered as a TAD. Otherwise, this candidate direction should be discarded. For a hole feature, the candidate directions are the two directions of the hole axis. For a plane feature, the candidate direction is the direction of the face normal. Tolerances, which represent the characteristics and relationships of features on a part, serve as functional description of the design requirements which should be satisfied during manufacturing processes. Tolerances can usually be classified into selftolerances and relative-tolerances. Self-tolerance is the tolerance reflecting the size deviation of a feature. It is related to the operations, but not directly related to other features. The examples are the straightness for feature B and flatness for feature A in Figure 5.1. Both are typical casting features. The form tolerances described in Chapter are self-tolerances. Relative-tolerance reflects the position tolerance in relation to 83 Chapter Optimal Set-up Planning the other features, such as feature C, which is a machining feature having dimension tolerances with A and B respectively, which are shown in Figure 5.1. The dimensional tolerances described in Chapter are relative-tolerances. Relative-tolerance can be used to identify the locating datum of a feature. For example, in Figure 5.1, to guarantee the dimensions of C, it is logical to use A and B as the locating datum. Otherwise, tolerance stack-ups would arise and tolerance compression might happen. Figure 5.1 Self and relative tolerances Tolerance compression means a feature has to be machined with higher tolerances compared with the blueprint values, and therefore a more accurate machining centre or operation may be needed. Tolerance compression can happen between set-ups and within a set-up. The tolerance compression between set-ups usually happens due to tolerance stack-up. Figure 5.2 shows an example of how the compression of operational tolerances happens. In Figure 5.2, dimension 10±0.10 is to be obtained from the previous operation. To obtain dimension 5±0.05, if it is machined having B as the base, the tolerance for dimension 10 has to be compressed to less than 0.05 by 84 Chapter Optimal Set-up Planning considering the tolerance stack-up. For a process plan with multiple set-ups, this could happen quite frequently. For a CNC machine, no chain analysis is needed for the relative and positional relationships between the geometry surfaces in a set-up because they can be programmed accurately. If the specified tolerances cannot be obtained, nothing can be done in the sequence unless a machining method or a machine tool with a higher process capacity is adopted or a higher rate of scrap can be accepted. For example, assuming the two dimensions in Figure 5.2 have to be achieved in a set-up. A more accurate machining method may be used for dimension 10±0.10 comparing with obtaining it in separate set-ups. In a multi-axis machine tool environment where multiple operations can be carried out in a single set-up and the design datum cannot always coincide with the set-up datum, tolerance compression would occur quite frequently. Figure 5.2 Tolerance compression The compression of operational tolerances will lead to an increase of the manufacturing lead time and production costs and should be taken into consideration during set-up planning. 85 Chapter Optimal Set-up Planning 5.2.2 Consideration of Real-Time Machine Resources For set-up planning, the application of set-up datum may vary according to different machining environment, e.g., 3-, 4- or 5-axis machining centre, whether vertical or horizontal. The number of set-ups and the selection of the machining features in each set-up depend on the machine tool configuration, that is, the number of axes and the orientation of the axes. In set-up planning, features are grouped into set-ups according to the type of machining centres. For a 3-axis machining centre, the machining features are grouped based on their TADs. Features with the same TADs are assigned to the same group. In this case, the number of set-ups is determined by the number of TADs of the machining features. For a 4/5-axis machining centre, the machining features are grouped based on the Tool Orientation Space (TOS) of the machining centre. Features with TADs within the machining centre’s TOS are assigned to the same group. In this case, the number of set-ups is determined by both the TOSs of the machining centres and the TADs of machining features. To determine the locating features for a set-up, the position tolerances for the machining features in a set-up are verified. In this research, it is assumed that a machining environment contains several machining centres which could be distributed and located in different places. Each machine has different capabilities (rigidity, power, accuracy, etc.), schedule, tooling, operation cost, with unique machine type, configuration, table size, main axis direction, machine ID code and location. For a particular distributed environment, the database also includes the information of the traveling distance between the places where the 86 Chapter Optimal Set-up Planning machine resources are located. Among them, the schedules of machining centres are very important during set-up planning. From a technical viewpoint, a set-up plan may appear to be good, but by taking into account the schedules of candidate machining centres, it may not be the most economical. Machine resources are provided in a database in the managing module. A user interface is developed to provide a way for the user to configure and update the machining environment in real-time, i.e., the currently available machining resources along with their capabilities, attributes and their operating schedules. It is integrated with the database and therefore each time the user updates the manufacturing environment using this interface, the database will be updated accordingly. The process planning module will read information from this database when performing set-up planning. Therefore, the set-up planning is performed with the machining resources with real-time response, which takes into account the production schedule and some unexpected events, such as the machine tool breakdown and an urgent job which needs to be handled immediately. 5.2.3 Tolerance Analysis Depending on the accuracy of the machine tool, features machined in a single set-up can be maintained in accurate relationship with respect to the machine tool coordinate system. This position will be lost if the part is dismounted from the machine tool and remounted again in a different fixture. The errors in the alignment of the part and fixture on the machine tool can be equal to or even larger than the accuracy requirements of small-tolerance relations. As a result, the position accuracy of a feature machined in a previous set-up can be insufficient to realize the required 87 Chapter Optimal Set-up Planning accuracy in the relation to the features to be machined in the present set-up. Even in a single set-up, when the set-up datum is different with the design datum, the required position tolerances of a feature may not be guaranteed. It is necessary to check the blueprint tolerances during set-up planning to ensure the set-up to be used is a feasible one. Case 1: Dimension datum coincides with set-up datum If the set-up datum coincides with a feature’s dimension datum, it is not necessary to check the tolerance for this feature. It is based on the assumption that the selected machining process and fixturing method can guarantee the dimensions and tolerances. Case 2: Dimension datum does not coincide with set-up datum In this case, it is necessary to take into consideration the stack-up error. For example, in the workpiece illustrated in Figure 5.3, the position dimensions clearly state that the centre of the hole (a machining feature) should be at the distance X from face A and Y from face C. Consequently, face A and face C must be used as datum to locate the workpiece while drilling this hole. This would ensure that the hole is at the specified distances from face A and face C. If one uses face B as a stopper, the deviation in length X1 between faces A and B would cause inaccuracies in the position of the hole. If length X1 is oversized by 1mm, the centre of the hole will be at (X+1) mm away from face A. If the length X1 is undersized, the hole would shift towards face A and would be nearer than distance X from face A. However, if location is on face A, the hole would always be at the same distance from face A irrespective of the variation in length X1. Similarly, the same situation will occur when locating with face D instead of face C for dimension Y. 88 Chapter Optimal Set-up Planning To satisfy the dimension requirements, sometimes a more accurate process or even a more accurate operation has to be chosen, and it would be more expensive. To reflect the additional cost if a higher accuracy machining process/operation is required, a tolerance cost factor (f) is introduced, which will be applied when calculating the machining time. Each operation can achieve a typical tolerance, and it is always within a certain range (Figure 5.4). Machining processes operating under normal conditions would produce parts within the tolerances as indicated in Figure 5.4 (a). Figure 5.4 (b) indicates the ANSI B4.1 Standard Tolerances. According to blueprint tolerances specified on a workpiece, suitable machining processes will be selected to generate the machining features. Figure 5.3 Tolerance chain To calculate f, it is first assumed that the operation selection for a machining feature is according to the lowest tolerance which this operation can achieve. For example, if there is a hole with tolerance around 0.25mm, a drilling operation with the lowest tolerance 0.254 as shown in Figure 5.4 is chosen for this. The tolerance range is defined as grades, and a grade represents a cell in Figure 5.4 (a). For example, for the drilling process, the tolerance range can be divided into four grades: grade 10 to grade 89 Chapter Optimal Set-up Planning 13. f is calculated based on the grade. The initial value f is set to 1. If the tolerance jumps to a new grade, f is increased by the number of grades jumped. If the jump is in between the grades, half a jump is used. If a selected machining operation cannot achieve this higher tolerance, a more accurate process will be selected. (a) Tolerance grades (b) ANSI B4.1 standard tolerances Figure 5.4 Dimensional tolerance capabilities of operations (www.engineeringtoolbox.com) 90 Chapter Optimal Set-up Planning on their TADs and the TOSs from the available machine resources. During the tolerance planning stage, the machining features are grouped into set-ups based on the machine tool assigned and their TADs, and the machining datum for each set-up is determined. The determination is performed according to the two rules: 1) If there are more than two machining features sharing the same ideal datum, this datum is taken as the set-up datum. 2) If Rule 1) cannot be applied, choose the ideal datum of a machining feature with tighter blueprint tolerances. After that, the set-ups are sequenced. Next the blueprint tolerances of the machining features are checked based on their ideal datum and the set-up datum, and a tolerance cost factor is generated according to the rules described in Section 5.3.3. During the optimal set-up planning stage, the manufacturing cost of each set-up plan is evaluated based on the cost model described in Section 5.3.4. The set-up plan which has the least cost is taken as the final result. This set-up planning process is adopted in the ACO algorithm which is described as follows.   Pheromone structure During set-up planning, a machining feature on a given workpiece is assigned to a setup based on its TAD, operation type, and the TOSs of machine tools, linked to a specific operation for the processing of this feature on a chosen machine tool (M), using a suitable cutter (T) and fixture (F), and in a particular set-up orientation (TAD). It can be represented by the set of M, T, F and TAD. Given a particular job shop with available machine tools, cutters and fixtures, a set of alternative operation methods can be generated for a feature by traversing all the possible combinations of M, T, F and TAD that can be used to perform the operation. Thus, the method to process a machining feature can be represented as a set of feasible combinations of M/T/F/TAD. 100 Chapter Optimal Set-up Planning A set-up plan can be specified as a linking of the operation methods for machining all the features on a given part. Therefore, the pheromone dimension can be determined by the number of the machining features. In this study, it is assumed, when a machine tool is selected for a machining feature, its fixture is decided since a machine tool would correspond to a particular fixture in a set-up. The cutter would need to be selected among the available cutters. Thus, the pheromone has two levels. One is the machine tool level which contains all the information exclusive of the cutters, and the other is the cutter level. Initialize Pheromone The design information and machine resources are loaded. The pheromone dimension is assigned accordingly and the heuristic variables on the machine level and cutter level are initialized. Matrix structures M and T (Table 5.2 and Table 5.3) are used to represent the pheromone values at the machine tool level and cutter level respectively. They are initialized with a zero value and will be updated during the searching procedure. Table 5.2 Pheromone matrix at the machine tool level M1 M2 M3 … Mn M1 m12 m13 … m1n M2 m21 m23 … m2n M3 m31 m32 … m3n … … … … … Mn mn1 mn2 mn3 . 101 Chapter Optimal Set-up Planning Table 5.3 Pheromone matrix at the cutter level T1 T2 T3 … Tn T1 t12 t13 … t1n T2 t21 t23 … t2n T3 t31 t32 … t3n … … … … … Tn tn1 tn2 tn3 . Construct Solution Solution construction is the preliminary set-up planning. Each machining feature is taken as a region that an ant has to visit. At each region, the ant has to select a machine tool with a cutter from the loaded machine resource. The fixture information can be obtained from the attribute of the machine tool. Figure 5.7 presents a graph that an ant travels. It contains eight regions, i.e., eight machining features in the design space. Tool selection is based on the TAD of the machining feature and the TOS of available machine tools. The TAD of the machining feature must be inside the TOS of the selected machine tool. The cutter is selected according to the dimension and operation of the machining feature and the radius and type of the cutter. The radius of a cutter should be smaller than the dimension of the machining feature. The type of the cutter should also match with the operation of the machining feature. Refinement of Solution The constructed solutions are analyzed at this stage. Set-ups together with set-up datum are determined, and the set-ups are sequenced. A tolerance analysis is conducted, and a tolerance cost factor is generated for each machining feature. A setup plan is generated for each solution. 102 Chapter Optimal Set-up Planning F1  Start  F2  F3  M,T M,T M,T M,T F4  M,T F5  Machine  Resources  End  F8  M,T M,T M,T F7  F6  Figure 5.7 An example of traveling graph Upon satisfying the above rules, the machine tools and cutters are selected based on probability. The probability with which ant k on node i chooses the next node j at the current iteration h, is according to the State Transition Rule (Dorigo et al, 1996) equation 5.3. It is directed by both the pheromone amount and the heuristic value. pijk (h)  ( ij (h)) (ij )   ( ij (h)) (ij )  , j  N iK (5.3) where, h: iteration index  ij : pheromone value between nodes i and j  ij : heuristic value between nodes i and j pij : probability to travel from node i to node j N i K : nodes not yet traversed in the ant-tour thus far where, i, j  (1, n) , n is the number of nodes. Parameters α and β are used to tune the relative importance of the pheromone and the heuristic distance in decision making. 103 Chapter Optimal Set-up Planning The heuristic value at the machine level is determined from equation 5.4 and the heuristic value at the cutter level is determined from equation 5.5. ijm  /(MCPi  FCPi  TCP  d ij ) (5.4) ijc  / CCPi (5.5) Evaluate Solution The feasible solutions are evaluated based on the objective function equation 5.1 described in Section 5.3.4. The parameters in equation 5.1 are obtained as follows: • Ns : it is obtained from the set-up plan of each constructed solution. • Nc : the number of cutters selected in a solution is obtained first, and then the tool change number is obtained. • MCP/CCP/FCP/Distance/Schedule: these parameters are obtained from the attributes of the machined tools. • SCCP/TCCP/TCP: these parameters are obtained from the machine resource database. • Tolerance cost factor: it is obtained from the attributes of the machining feature, which have been stored in the machining feature data structure during the solution refinement stage. 104 Chapter Optimal Set-up Planning Update Pheromone After each iteration, an updating process is triggered if there are better solutions in the population which is used to store the global best results. The pheromone values are updated at both the machine level and the cutter level. It is based on equation 5.6. S  ij (h  1)   ij (h)   ij best (h),  ijbest (h)   C s (h) (5.6) s where, S is the number of solutions at the current iteration that are better than anyone in the population, Cs is the cost of a solution, and ρ is the pheromone evaporation rate. 5.4 5.4.1 System Performance Illustration of an Example Part An example part is presented in this section to demonstrate the proposed approach and present the test results. It is a simplified front knuckle of an automotive chassis system, and it is cast followed by machining. Figure 5.8 gives the details of the cast and machined parts. The input CAD model, which contains the dimensions and tolerance information, is constructed using Inventor®. 105 Chapter Optimal Set-up Planning a) Cast part b) Machined part Figure 5.8 Example part Design Information Extraction The design information, i.e., the geometric and dimensional specifications in the machined and cast CAD models, is recognized and extracted. By performing Boolean operations on the two models and using rules stated in Table 3.2 in Chapter 3, five machining features, i.e., Plane A, Hole B, Hole C, Hole D and Plane E, together with the machining depths, are obtained and shown in Figure 5.9. Other information listed in Table 5.4, which include TADs, operations, tolerances, design datum and machining length, are obtained by geometric reasoning using the API provided by Inventor®. 106 Chapter Optimal Set-up Planning 2.5 C D B E A Figure 5.9 Extracted machining features Table 5.4 Extracted design information Machining Features Cast Features Features TAD Operation Plane A Hole B Hole C Hole D Plane E X,Y,Z, Y’,A,B -z z z 45@ x +x milling reaming boring drilling milling Self Tolerance  .3  .1  .2  .3  .3 1.2 Relative Tolerance 1.0 1.0 0.8 0.8 0.8 Design Datum X/Y/Z X/Y/Z A/B/Z A/B/Z A/B/Y’ L (mm) 378 40 40 30 38 Machine Resource Configuration The specifications of machine resources available for the set-up planning are shown in Tables 5.5-8, which are configured through an interactive interface. Other parameters such as TCP is assumed to be $10 per hour, CCCP is $10 per change, SCCP is $20 per change, and SCP is $100 per hour. 107 Chapter Optimal Set-up Planning Table 5.5 Machine information Available Machine Center 3-axis machine M1 3-axis machine M2 4-axis machine M3 4-axis machine M4 5-axis machine M5 Feed f (mm) FCP 0.5 Rotation speed n (s-1) 70 100 480 0.5 100 150 120 0.5 150 220 0.5 150 200 180 0.5 180 250 600 Schedule (s) MCP Table 5.6 Machine Tool Orientation Space (TOS) Available Machine Center  3-axis machine M1 3-axis machine M2 4-axis machine M3 4-axis machine M4 5-axis machine M5 0 -135 -135 TOS Y X  A   A 0 +90 +45   B 0 -90 -90 Z   B 0 +90 +90   C 0 0  C 0 0 Table 5.7 Cutter information Cutter No. C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 CCP 3 3 10 10 12 12 15 Type Drill Drill Drill Drill Drill Drill Drill Mill Mill Mill Mill Mill Radius 10 12 18 24 30 10 15 20 30 50 108 Chapter Optimal Set-up Planning Table 5.8 Distance matrix between machine tools M1 M2 M3 M4 M5 5.4.2 M1 M2 M3 M4 10 M5 4 10 Results and Discussion During the set-up planning, the machining time is calculated for each machining feature according to equation 5.2 based on the machine tool selected. The depth of cut for drilling is 2.5mm and for milling/boring/reaming is 1mm. The results are shown in Table 5.9 using the feeds and rotation speeds shown in Table 5.5. Although the operation time for each machining feature is the same for each machine here due to the same values of the feed and rotation speed, it is usually different for different machining centres since their feeds and rotation speeds may be different. During set-up planning, the blueprint tolerances of the machining features in the candidate plans are checked. From Table 5.5, the design datum of feature C is A, B and Z and the relative tolerance with respect to A, B, Z is 0.8mm. While the design datum for feature A, B is X, Y, Z with relative tolerance 1.0mm. In this case, if machining C uses X, Y, Z as the set-up datum, the relative tolerance between C and A, B would be more than 1.0mm due to the tolerance stack-up. Therefore the relative tolerance between A, B and X, Y should not be more than 0.8mm, which should be ensured when machining A and B with datum X and Y. Since a more accurate method would be needed to achieve the tolerance of 0.8mm instead of 1.0mm, a tolerance cost factor is applied to A and B in this set-up. The same analysis would be conducted 109 Chapter Optimal Set-up Planning automatically for feature D and E if they are planned to be machined in the same setup with A and B. The set-up sequence is arranged according to the sequence of the design datum. The distances used to calculate the transport cost are distances between machines based on the set-up sequence. Table 5.9 Operation times for the machining features T Machining (s) Plane A 1890 Hole B 200 Hole C 80 Hole D 72 Plane E 95 The results based on the above machining environment are shown in Figure 5.10 and Table 5.10. The first (top) thick solid curve in Figure 5.10 shows the cost of the optimization results, and Table 5.10 shows the optimal set-up plans. There are one setup change and two cutter changes. The tolerance cost is applied to feature E since the set-up datum does not coincide with its dimensional datum. However there is a trade off by the other cost factors, making it the optimal one. general 780 case case case 670 case Cost 560 450 340 230 17 34 52 69 86 Number of Set-up Plans Figure 5.10 Cost of set-up plans 110 Chapter Optimal Set-up Planning Table 5.10 Optimal set-up plan Optimal Set-up Plan Set-ups Feature Set-up1 A B E Set-up2 C D Machine Cutter Datum M4 C11 X/Y/Z C5 C9 M3 C1 A/B/Z C1 Cost 527 To demonstrate the effects of some factors considered in the cost model, four different situations are considered, and the results are shown in Figure 5.10, Table 5.11, Table 5.12, Table 5.13 and Table 5.14 for the comparison. Case1: There is no tolerance consideration in each set-up plan, i.e., the tolerance cost factor for all machining feature is one. There is no waiting time based on the machine schedules in the set-up plans, and the distances between the machine centers are the same as hours away. The forth thin solid curve in Figure 5.10 shows the optimized cost results. Case2: The tolerance analysis is conducted for each set-up plan, and different tolerance cost factors other than one are assigned to each machining feature based on the analysis results. The other two conditions are kept the same as in Case1. The third thin dot curve in Figure 5.10 shows the optimized cost results. Case3: The schedules of the machining centers are considered, i.e., some machining centers may not be available, thus the waiting cost will apply to them accordingly. The 111 Chapter Optimal Set-up Planning other two conditions are kept the same as in Case1. The second thick dot curve in Figure 5.10 shows the optimized cost results. Case4: The machining centers are considered to be located in places with different travel times between them, and not the same distances as considered in Case1. This will result in different optimal results. The other two conditions are kept the same as in Case1. The fifth thick dotted curve in Figure 5.10 shows the cost results. Tables 5.11-14 shows the optimal set-up plans for each case separately. They show the differences in costs due to different machining situations. For case 1, the optimal one is using machine M5 to manufacture the five features in one set-up. Therefore, there is no set-up change, but there are three cutter changes. Although the cost factors have been applied to feature C, D and E, there is a trade off by no set-up change and less expensive machine tool cost. For case 2, the optimal solution has two set-up changes and two cutter changes, and the tolerance factor has been applied to feature C. It is the lowest machine tool cost without any transport cost which makes it the lowest one. For case 3, there is one set-up change, two cutter changes and the tolerance cost has been applied to feature C and E. Its lowest cost is due to fewer set-up changes, no transport cost and less waiting time. For case 4, the result is the same as case 1. This is because if all the features are machined in one set-up using one machine tool, the transport cost will not be incurred. In this case, it is the same situation as in case 1. The results show that different machining environments would result in different setup planning results, and this depends much on the dynamic situation of a company at a particular instant. 112 Chapter Optimal Set-up Planning Table 5.11 Optimal set-up plan for case1 Optimal Set-up Plan Set-ups Feature Machine A B Set-up1 M5 C D E Cutter C11 C5 C1 C1 C8 Datum Cost X/Y/Z 445 Table 5.12 Optimal set-up plan for case2 Optimal Set-up Plan Set-ups Feature A Set-up1 B C Set-up2 D Set-up3 E Machine M1 M1 M1 Cutter C12 C5 C2 C1 C9 Datum Cost X/Y/Z 460 A/B/Z A/B/Y’ Table 5.13 Optimal set-up plan for case3 Optimal Set-up Plan Set-ups Feature A Set-up1 B C E Set-up2 D Machine M4 M4 Cutter C10 C4 C1 C1 C8 Datum Cost X/Y/Z 519 A/B/Z Table 5.14 Optimal set-up plan for case4 Optimal Set-up Plan Set-ups Feature Machine A B Set-up1 M5 C D E Cutter C11 C5 C1 C1 C8 Datum Cost X/Y/Z 445 113 Chapter Optimal Set-up Planning 5.4.3 Performance Comparison This research considers dynamic machining environment as by Ong et al ( 2002), and the machine resources include not only the 3-axis machining centre as was considered by Zhang (1997) and Zhang et al (1999), but also 4- and 5- axis machining centres. Compared with the cost model in the studies of Ong et al (2002), Zhang (1997) and Zhang et al (1999), the cost model in this research takes more factors into account, and therefore the cost evaluation is more reliable. There are several improvements in the cost model. Firstly, it considers the machining cost based on the machining time of the machining feature. Dimension differences in the machining features will result in large differences in machining time thus the cost incurred. Secondly, it considers the distributed machining environment which is the current pervasive manufacturing scenario. This is reflected by considering the transport cost between machining centres located in different places. It also considers the cost arising from the current schedules of a machining centre. Another important factor which was not fully addressed in the cost is the tolerance cost factor. It is applied to situations where the set-up datum does not coincide with ideal datum of a machining feature, and a more accurate machining method will be needed, and hence the cost will be increased. Other factors taken into account include machine tool cost, cutter cost, fixture cost, set-up change cost and cutter change cost. The consideration of all the cost factors would make the cost evaluation of a set-up plan more accurate and reliable. To verify the presented approach, the case study and the cost model presented by Ong et al (2002) has been applied to the ACO-based optimization since they also considered 4- and 5-axis machining centres. To determine the heuristic value at the machine level which is used to calculate the probability in equation 5.3, some changes 114 Chapter Optimal Set-up Planning are made in equation 5.4, and only MCP is used to calculate the heuristic value. Table 5.15 shows an optimal result. There are one machine change, four set-up changes and two cutter changes. The optimal result proves that the presented ACO-based optimization is an efficient methodology to solve the set-up planning problem. Table 5.15 Optimal set-up plan for the case study in Ong et al (2002) Optimal Set-up Plan Set-ups Set-up1 Set-up2 Set-up3 Set-up4 Set-up3 5.5 Feature 12 10 11 Machine 2 Cutter 1 5 5 5 Cost 3270 Summary In this chapter, a set-up planning system, which focuses on the development of an integrated procedure for automatic set-up planning for machining features of a given cast part, is presented. It considers both machine tools selection and tolerance analysis, and is able to achieve an optimal set-up planning result by incorporating a cost model. ACO is employed to solve this NP-complete problem. Parts can be produced within designed tolerances and with the lowest cost in a particular production environment. 115 [...]... optimization is an efficient methodology to solve the set-up planning problem Table 5. 15 Optimal set-up plan for the case study in Ong et al (2002) Optimal Set-up Plan Set-ups Set-up1 Set-up2 Set-up3 Set-up4 Set-up3 5. 5 Feature 1 2 4 6 12 5 9 10 11 3 7 8 Machine 2 2 2 2 4 Cutter 5 1 1 1 5 1 5 5 5 5 5 1 Cost 3270 Summary In this chapter, a set-up planning system, which focuses on the development of an integrated. ..Chapter 5 Optimal Set-up Planning 5. 2.4 Cost Model One of the ultimate goals of an enterprise is to be profitable Hence, every company has the mandate to reduce cost and increase profit margin, which can be achieved more effectively at the design planning stage rather than the manufacturing stage In this research, set-up planning is performed based on a cost model and an optimization methodology... solution has two set-up changes and two cutter changes, and the tolerance factor has been applied to feature C It is the lowest machine tool cost without any transport cost which makes it the lowest one For case 3, there is one set-up change, two cutter changes and the tolerance cost has been applied to feature C and E Its lowest cost is due to fewer set-up changes, no transport cost and less waiting time... applied at the set-up level Table 5. 1 Distance matrix between machine tools M1 M3 … Mn M1 0 d12 d13 … d1n M2 d21 0 d23 … d2n M3 d31 d32 0 … d3n … … … … 0 … Mn 5. 3.2 M2 dn1 dn2 dn3 … 0 ACO Based Set-up Planning The set-up planning process can be divided into three stages: preliminary set-up planning, tolerance planning and optimal set-up planning During the preliminary setup planning stage, each machining... values of the feed and rotation speed, it is usually different for different machining centres since their feeds and rotation speeds may be different During set-up planning, the blueprint tolerances of the machining features in the candidate plans are checked From Table 5. 5, the design datum of feature C is A, B and Z and the relative tolerance with respect to A, B, Z is 0.8mm While the design datum for... the dimensions and tolerance information, is constructed using Inventor® 1 05 Chapter 5 Optimal Set-up Planning a) Cast part b) Machined part Figure 5. 8 Example part Design Information Extraction The design information, i.e., the geometric and dimensional specifications in the machined and cast CAD models, is recognized and extracted By performing Boolean operations on the two models and using rules... considered 4- and 5- axis machining centres To determine the heuristic value at the machine level which is used to calculate the probability in equation 5. 3, some changes 114 Chapter 5 Optimal Set-up Planning are made in equation 5. 4, and only MCP is used to calculate the heuristic value Table 5. 15 shows an optimal result There are one machine change, four set-up changes and two cutter changes The optimal... features, i.e., Plane A, Hole B, Hole C, Hole D and Plane E, together with the machining depths, are obtained and shown in Figure 5. 9 Other information listed in Table 5. 4, which include TADs, operations, tolerances, design datum and machining length, are obtained by geometric reasoning using the API provided by Inventor® 106 Chapter 5 Optimal Set-up Planning 5 2 2 .5 C D B E 6 A 5 Figure 5. 9 Extracted... Table 5. 9 Operation times for the machining features T Machining (s) Plane A 1890 Hole B 200 Hole C 80 Hole D 72 Plane E 95 The results based on the above machining environment are shown in Figure 5. 10 and Table 5. 10 The first (top) thick solid curve in Figure 5. 10 shows the cost of the optimization results, and Table 5. 10 shows the optimal set-up plans There are one setup change and two cutter changes... 5. 7 Cutter information Cutter No C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 CCP 3 3 3 4 3 3 4 10 10 12 12 15 Type Drill Drill Drill Drill Drill Drill Drill Mill Mill Mill Mill Mill Radius 2 4 10 12 18 24 30 10 15 20 30 50 108 Chapter 5 Optimal Set-up Planning Table 5. 8 Distance matrix between machine tools M1 M2 M3 M4 M5 5. 4.2 M1 0 2 4 5 6 M2 2 0 6 8 4 M3 4 6 0 3 4 M4 5 8 3 0 10 M5 6 4 4 10 0 Results and . 81 Chapter 5 Optimal Set-up Planning 5. 1 Introduction Set-up planning is a function of both process planning and fixture design (Ong and Nee, 1994). Its task is to determine the number and. d n3 … 0 5. 3.2 ACO Based Set-up Planning The set-up planning process can be divided into three stages: preliminary set-up planning, tolerance planning and optimal set-up planning. During. use A and B as the locating datum. Otherwise, tolerance stack-ups would arise and tolerance compression might happen. Figure 5. 1 Self and relative tolerances Tolerance compression means