Plastic Injection molding is one of the most popular manufacturing processes for making thermo plastic products and mold design is a key aspect of the process. Design of molds requires knowledge expertise and most importantly experience in the field. When one of these is lacking selection of an appropriate mold for manufacturing a plastic component is done on a trial-and-error basis. This increases the cost of production and introduces inconsistencies in the design. This paper describes the development of an intelligent mold design tool. The tool captures know ledge about the mold design process and represents the knowledge in logical fashion. The knowledge acquired will be deterministic and non-deterministic information about the mold design process. Once developed the mold design tool will guide the user in selecting an appropriate mold for his plastic part based on various client specifications.
The plastic injection molding process demands knowledge expertise and most important experience for its successful implementation. Often it is the molding parameters that control the efficiency of the process. Effectively controlling and optimizing these parameters during the manufacturing process can achieve consistency which takes the form of part quality and part cost. The level of experience of the manufacturers determines how effectively the process parameters are controlled. This sometimes leads to inconsistency introduced by human error. There is also the case where there is inexperience shortage of time resources and little scope for innovation. Knowledge-based engineering provides a feasible solution to all these problems by creating what is called an “intelligent model” of the problem.
Intelligent Knowledge based Engineering modules for the plastic injection molding process IKEM is a software technology that is a step ahead of the concurrent engineering and CAD/CAM systems. It integrates current knowledge about the design and manufacturing processes and helps to reduce several man-hours by reducing engineering changes in the design phase of product development by giving users instruction about various design aspects. The system will be used for injection molding design design iterations and process integration. The current process consists of many manual computations CAD graphical constructions and experience attained from previous projects. Once the engineer completes the design it will be evaluated for performance. The IKEM project has been divided into three major modules.
1. The cost estimation module
2. The mold design module
3. The Manufacturing module
Input to the IKEM system is of two forms. Input in the form of a CAD model Pro-E file and input given at the User Interface form. The manufacturer's level of experience will determine how to effectively control the process parameters. Sometimes this leads to inconsistency caused by human error. There is lack of experience, lack of time, lack of resources and innovative space. Through the creation of a "smart" model, engineering knowledge provides a feasible scheme to solve all user input form mold design and manufacture of the user output form of syntax analysis process CAD model cost estimation 2 Intelligent Mold Design Tool The mold design tool in its basic form is a Visual Basic application taking input from a textfile that contains information about the part and a User Input form. The text file containsinformation about the part geometry parsed from a Pro/E information file. The input is used toestimate the dimensions of mold and various other features.
2.1 Literature Review
Design of molds is another stage of the injection molding process where the experience of an engineer largely helps automate the process and increase its efficiency. The issue that needs attention is the time that goes into designing the molds. Often, design engineers refer to tables and standard handbooks while designing a mold, which consumes lot of time. Also, a great deal of time goes into modeling components of the mold in standard CAD software. Different researchers have dealt with the issue of reducing the time it takes to design the mold in different ways. Koelsch and James have employed group technology techniques to reduce the mold design time. A unique coding system that groups a class of injection molded parts, and the tooling required in injection molding is developed which is general and can be applied toother product lines.
A software system to implement the coding system has also been developed. Attempts were also directed towards the automation of the mold design process by capturing experience and knowledge of engineers in the field. The development of a concurrent mold design system is one such approach that attempts to develop a systematic methodology for injection mold design processes in a concurrent engineering environment. The objective of their research was to develop a mold development process that facilitates concurrent engineering-based 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 designthat consume time referring to tables, data sheets etc.. 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.