practice, and to develop a knowledge-based design aid for injection molding mold design that accommodates manufacturability concerns, as well as product requirements. Researchers have been trying to automate the mold design process either by capturing only the deterministic information on the mold design process or the non-deterministic information, in various ways. This research uniquely attempts to develop a mold design application that captures information in both forms; deterministic and non-deterministic. 2.2 Approach Adopted In order to develop an intelligent mold design tool, the conventional method of designing molds is studied. The application developer and the design engineer work together in designing a mold for a particular plastic part. During this time, the approach adopted by the engineer to select the mold base is closely observed and aspects of the selection process that require his knowledge/experience are identified. Also, there will be times when the engineer will refer to tables and handbooks in order to standardize his selection process. This time consuming process is also recorded to incorporate it later in the application. Formulating the problem for the application in terms of inputs and outputs is the next stage. This involves defining what information about the mold layout is most required for the user and also the minimum number of inputs that can be taken from him to give those outputs. Based on the information gathered in the mold design exercise, the conventions followed by the engineer are transformed into if-then rules. Decision tables are used to account for all possible cases that arise when dealing with a particular aspect of the mold design process. The rules so framed are then organized into modules interacting with each other, using an application development environment. Finally the application is tested for its validity when it comes to designing molds for plastic parts manufactured in the industry. 2.3 Selection of Appropriate Mold Base Typically, selection of appropriate mold base for manufacturing a plastic part involves Estimating the number of cavities The number of cavities is decided depending on the number of parts required within a given time. There are also other issues like the plasticizing capacity of the machine, reject rate etc that affect the number of cavities to be present in the mold base. Deciding on the presence of inserts and their dimensions Inserts facilitate the reusability of the mold base and therefore help in reducing cost of manufacturing. When it comes to selecting the dimensions and the number, a decision is made depending on the reusability of existing old inserts and cost of ordering new ones. Determining the size and location of runners The runner size depends on the material being molded. Although there are other considerations material properties determines the channel size required for its flow. Location of runners mainly depends on the topology of runners being used. Though a circular runner system is always preferable, the branched runner system that avoids runner balancing is the one most widely used. Determining the diameter of sprue The diameter of the sprue is decided based on the size of the mold, number of cavities, or the amount of plastic that is to be filled within a given time. Locating gates Plastic enters the cavity at a point where it can uniformly fill the cavity. A gate can be located at any point on the perimeter of a circular cavity but has to enter at the midsection when it comes to filling rectangular cavities. Determining the size and location of water lines Water lines are located at standard distances form each other and from any wall in the mold. The convention is not to locate a waterline within one diameter range on the mold wall. Deciding mold dimensions based on above conclusions Based on all the above decisions the approximate mold dimensions can be estimated and rounded off to the nearest catalog number. Considering all the above aspects before even modeling the mold base reduces the cost and time that go into redesigning. 2.4 Formulation of the Problem Based on issues that require human knowledge/experience, and aspects of mold design that consume time referring to tables, data sheets etc., the problem for developing the application is defined as shown in Figure 2. Figure 2. Organization of the Mold Design Module. While most of the input, like the number of cavities, cavity image dimensions, cycle time are based on the client specifications, other input like the plasticizing capacity, shots per minute etc., can be obtained from the machine specifications. The output of the application contains mold dimensions and other information, which clearly helps in selecting the standard mold base from catalogs. Apart from the input and output, the Figure 2 also shows the various modules that produce the final output. 2.5 Framing rules At this stage, the expert’s knowledge is represented in the form of multiple If-Then statements. The rules may be representations of both qualitative and quantitative knowledge. By qualitative knowledge, we mean deterministic information about a problem that can be solved computationally. By qualitative we mean information that is not deterministic, but merely followed as a rule based on previous cases where the rule has worked. A typical rule is illustrated below: If Material = “Acetal” And Runner Length <= 3 And Runner Length > 0 Then Runner Diameter =0.062 End If When framing the rules it is important that we represent the information in a compact way while avoiding redundancy, incompleteness and inconsistency. Decision tables help take care of all the above concerns by checking for redundancy and comprehensive expression of the problem statement. As an example, in the process of selecting an appropriate mold base, the size of mold base depends on the number of cavities and inserts. To ensure that all possible combinations of cavities and inserts have been considered we use a decision table and subsequently use the decision table to frame rules. Table1 shows more than one case where the mold dimensions are the same. Number of 1 cavities(1,2,4) Number of 1 Inserts(1,2,4) Mold Dimensions 1 2 A* Table 1. Sample Decision Table 1 2 2 2 4 * 1 A 2 B 4 * 4 1 A 4 2 B 4 4 C Case A: Mold Width = (Insert Width + 2) Mold Length = (Insert Length + 2) Mold Thickness = Insert Thickness Case B: Mold Width = (2* Insert Width + 3.5) Mold Length = (Insert Length + 2) Mold Thickness = Insert Thickness Case C: Mold Width = (2*Insert Width + 3.5) Mold Length = (2* Insert Length+ 3) Mold Thickness = Insert Thickness Figure 3. Mold Dimensions for various combinations of Inserts and Cavities The case where the number of cavities is one and the number of inserts is one has the same mold dimensions as the case where the number of cavities is two and four. The three cases can be reduced to one single rule: If Number Of Inserts=1 Then Mold Width = (Insert Width + 2) Mold Length = (Insert Length + 2) Mold Thickness = Insert Thickness End If The rules are arranged in modular fashion using a standard programming language for the sake of convenience and clarity. Each module generates a set of outputs, which would be inputs for other modules. 2.6 Testing the application The intelligent mold design application is validated using various test cases. For each case the part information, mold information and the machine information are varied and a human expert validates the results of feeding this info into the application. Table 2 shows one such test case where the part requires two cavities and there are no inserts present. The application gives the approximate mold dimensions, runner dimension, sprue dimension and runner length based on the cavity image dimensions and other information. Input Number of insets 0 Insert Length 0 Insert Width 0 Insert Thickness 0 Cavity image Length 2.02 Cavity image Width 3.28 Cavity image Depth 0.5 Waterline Di 0.25 Number of parts to be produced 1000 Time Available 6 Cycle time 26 Reject Rate 0.1 Shots per minute 2.3 Material ABS Output Program Output Number of cavities 2 Mold Length 10.06 Mold Width 4.02 Mold Thickness 1.125 Runner Diameter 0.109 Runner Length 1.5 Big end sprue bush diameter 0.218 Table 2. Typical test case showing program input and output. The mold dimensions obtained are very close to a typical human expert design for the test case but do not suggest explicitly the use of a standard mold base, like a specific mold from the D-M-E mold base catalog. The mold dimensions are however useful in selecting appropriate mold base from the mold catalogs. The runner dimensions are based on the material being used and therefore are limited to a specific range of shot size. 3 Summary This paper presents the approach adopted towards developing an intelligent mold design application that performs mold base selection based on user input. The knowledge acquisition process is done by first designing a mold base in close consultation with an industry expert and also by collecting deterministic information from hand books and data sheets. The collected information, which can be both qualitative and quantitative knowledge about the mold selection process, is represented in the form of rules arranged in different modules.
模具专业毕业设计外文翻译注塑成型的智能模具设计工具模具设计
