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A Systematic Approach to Diagnosing Mold Filling and Part Quality Variations
There is a lot of noise during most new mold startups as things pop up that were not caught during the mold design or building stages or even understood at all. Most often, the additional time required for debugging the processing and part quality variations are often a result of not being able to see the forest through the trees. And unfortunately, the proposed “solutions” to get parts out the door are often band-aid fixes and do not solve the root cause of the variations. Of course everyone says they will fix the mold right before production begins. But we all know what usually happens…other priority projects come up, time is never found, and the molder is forced to live with a mold that has band-aids falling off, revealing the scars of a poor startup/debug procedure. This all creates long-term issues throughout the production life of the product. However, some of this can be avoided. By taking a systematic five-step approach to mapping the mold and tracking the variations accordingly (whether filling imbalances or part quality variations), the root causes of the problems can more easily be quantified, diagnosed, and solved. After all, plastic flow is a science and variations can be identified and solved by putting the pieces of the puzzle together. Most molders today perform a short shot study during the initial mold sampling stage. This procedure is called a “mold balance analysis” and it usually consists of contrasting the heaviest cavity versus the lightest cavity and calculating a percent imbalance. Certainly this gives the user a number…a perceived imbalance percentage…but now what? How can the user use the information gathered from this method to help diagnose and correct those variations? Consider the fact that your mold may have 4, 8, 16, or 32 cavities or more. Now you are trying to isolate the source of variations between those cavities with that one number. Sounds like a pretty difficult and impossible task. One the other hand, if we take a more systematic and scientific approach in developing an “advanced mold balance analysis”, it is possible to isolate the noises inside of a mold and separate the possible sources of the variations. And all this can be done in five easy steps. This five-step process takes fundamental plastic flow characteristics and applies them to the layout of the mold in order to identify “Flow Groups”. By doing so, it becomes much easier to see the variations in the mold, what is causing them, and how to eliminate the sources of the variations. Sounds cool, right? So let me explain further… Consider that all filling and part quality variations from cavity-to-cavity within a mold are typically a result of a pressure drop difference to and/or within the cavities. By analyzing a simplified pressure drop equation for round channels (see Figure 1), we can separate out the variables into two main groups: (1) mold steel imbalances (l = flow length, r = radius of the flow channel), and (2) shear-induced viscosity imbalances (η = viscosity).
As such, if the pressure drop was the same to all cavities then all the parts should fill & weigh the same, even when doing a short shot analysis. But most molders and mold makers would agree that this rarely ever happens. So, digging into this further, we first need to separate the mold cavities into “Flow Groups”, or groups of cavities that have the same material shear history and therefore the same material viscosity conditions (η) (see Figure 2). This allows us to eliminate viscosity imbalances as a possible source of variation within the Flow Groups. Therefore, any imbalance from cavity-to-cavity within a given Flow Group has to be caused by the other variables (l, r), and as such those possible sources have been termed “Steel Imbalances”. It has also been proven through numerous studies that cavities of different Flow Groups receive different material properties. Thus the major source of variation between Flow Groups must be a result of “Shear Imbalances”, or viscosity (η) differences.
By now you are probably wondering what exactly is a Steel Imbalance or Shear Imbalance. So let’s continue to break it down further: 1. Steel Imbalances Explained: These variations are typically found within the mold steel dimensions. These variations may be caused by a non-geometric runner layout, differences in the machining of the part cavities, variations in gates sizes and/or gate land geometry, runner lengths, runner diameters, venting, or other sources. In addition, cold slugs can cause filling and part quality variations, and are considered a Steel Imbalance since they are easily solved through mold design modifications. Molding machine variations would also be considered a source of Steel Imbalance. Machine variations may include: broken heater bands, worn screws, and worn valves. Basically any variation that is non-shear related would be categorized under Steel Imbalances. Sometimes the Steel Imbalances are easily identified while others take more time. But regardless, by following this systematic approach the user can eliminate the possible sources one by one and the overall time to diagnose the mold and part variations will be greatly reduced. 2. Shear-Induced Viscosity Imbalances Explained: Despite the geometric balance on what has traditionally been referred to as a "naturally balanced" runner system, these runner systems introduce significant variations in melt conditions (i.e. temperature, pressure, and material properties) flowing through the mold and into the cavities. What must be recognized is that conventional, geometrically balanced runners actually create multiple flows, or Flow Groups, much like the old “tree” or “fishbone” branching runners. These Flow Groups in turn produce multiple families of parts in the mold, which create variations from cavity to cavity such as dimensions, warp, flash, sink, short shots, etc.• Fax: 814.899.7117 3. What About Cooling and Hot Runner Molds? The largest impact of cooling differences between cavities (i.e. surface finish, shrink, warp, and sink) occurs during the packing and cooling phases of the molding cycle. Since we are evaluating short shots (fill only parts), variations in mold temperature can be eliminated as a major source of imbalance since it has a minimal impact on the weight of short shot samples. Hot runner manifold systems add another level of complexity. One must understand that hot runners typically exhibit the same shear-induced viscosity imbalances seen in cold runner systems. However, hot runner molds also have many additional variables that are sometimes more difficult to isolate. These additional variations will be grouped under “Steel Imbalances” for the purpose of separating shear imbalances from other imbalances. Hot runner Steel Imbalances may include temperature fluctuation, gate size variations, mismatch of “plugs” in the melt channels, thermal expansion differences, and heater band and thermocouple placement. Summary of Test Data: Figure 3 is a summary of the data collected from studies consisting of 25 multi-cavity injection molds (8 cavities). The plot contrasts the average Steel Imbalances within Flow 1 and Flow 2, and the average Shear-Induced Imbalance between Flow 1 and Flow 2. From the figure, it can easily be seen that the shear-induced imbalances are the largest contributing factors to variations in multi-cavity molds.
Next month we will provide a case study which walks us through the process of collecting, organizing, and interpreting the data.
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