**2. Familiarization**

34 Some Critical Issues for Injection Molding

is important to lift the members into a mode where they are willing and motivated to work on the problem in an open, cooperative, and productive atmosphere. Beside this, because of its rules and structure, "team leading", "mediation skills", and "creativity tools" comprise an indispensable base to build up a mutual attitude towards the improvement process. Furthermore, these tools will lead the team from reflecting to describing a problem and to joint agreement on supported decisions, work-methods and actions. An additional advantage will

The DMAIC Cycle "which as a logical further development of the Deming cycle, provides a good structure to get into the "problem solving process". Within this approach, the question "what is the 'real problem'?" is asked. Two different symptoms form cause and effect, so it is helpful to discuss this in the team of experts, for instance, with the following tools and methods. After the "Real Problem" has been defined, it is necessary to find a way to measure cause and effect of the problem. This might sound straight forward and logical, but in most cases, it is not done. This means, for instance, that a check of the capability of the measuring equipment is often not requested for measuring the whole process variation range of the "Process working space". Measurement methods and also the equipment calibration and capability should be validated *(each time)* prior to execution of the experiments. Otherwise, it may happen that a lot expensive, time- consuming experiments are preformed and also a lot of measurements are taken, but these are not adequate to

The next step to get factor settings and systems- or product-attributes measurably defined is to analyze their correlation with a structured approach. Design of Experiments is a very powerful tool to do this. During the experiments, it is recommended to request every step in

It has to be verified whether the latest setup (factor variation) of the worksheet is

adequate for focusing on the desired responses of the targets (Fig. 18)

be a clear structure, such as, for instance, the "DMAIC Cycle".

Fig. 1. DMAIC Cycle (Lunau, 2006, 2007).

describe cause and effect. (Process space)

planning, such as:

But again where to start? The following small collection of tools is a good start to get the first steps done, to reflect and research the process setup or process problem.

### **2.1 Ask why 5 times! (Michael L. George, 2005)**

One of the easiest and most straightforward tools for getting familiar with a process setup or process problems is just to ask why, why and why again. Inquire if tree- or bubble diagrams can be used to document the root cause analysis. This and the following tools should be performed in a team only after it is certain that it follows the basic rules of good brainstorming / communication practice. This means: no direct "pointers" or school assignments should take place. Also there should be no criticism during the creative phase but rather only at the right time and then only constructively expressed.

#### **Small Example of constructive, drill-down questioning:**

**Why is the injection part not of sufficient quality?** 

Because it contained some color strikes and dells.

**Why does the part contain color strikes and dells?** 

Because the filling and cooling process are not as robust as they should be.

**Why are the cooling and filling process not robust?** 

Because the density of the melted polymer is not homogenous.

**Why is the melted polymer-density-distribution not as it should be?** 

Because the polymer granulate was not dry enough.

**Why did the drier not work as it was supposed to?** 

Because the service hadn't been properly done.

member the chance to write the numbers from one (very important) to ten (less important) behind the collected factors on a white board, or perform a simple hand-up voting (*each* 

After this is done, a maximum of ten factors of importance should be placed in the following matrix and weighted pairwise according to the importance of their influence. The direction of the questions is row versus column (Fig 4). Within the AHP, importance is leveled after

**Weighting Weights Weighting counterpart Weights**  Extremely more important 9 Extremely less important 1/9 Significantly more important 7 Significantly less important 1/7 More important 5 Less important 1/5 Somewhat important 3 Somewhat less important 1/3 Equal important 1 Equally important 1

In general, I recommend doing the weighting vice versa instead of filling the counterpart question automatically *(space below grey diagonal)*. Asking the questions "how much more is "Factor A" important than "Factor B"" and asking the opposite question staggered "how much more is 'Factor B' important than 'Factor A'"- again, will show the uncertainty of the knowledge and make it possible to reflect this fact within the grid diagram. In most cases, it is helpful to visualize the customers' demands prior to the factor ranking. A valuable input for defining customer values against product/process costs is for instance the "Kano model. If the prioritized quality criterion is not available, it needs to be developed because, in most cases, some target functions are more important to achieve then others, so compensating factor settings need to be developed after ranked target functions. On the grid-diagram (Fig. 5) the factors "holding pressure" and "nozzle temperature" are displaced a little bit laterally; this is because of the contradictorily ranked answers summarized in the matrix. Because of this inconsistency, influence of these factors should be discussed again. At some places, due

Fig. 3. Ishikawa diagram, (Rauwendaal).

the following scheme. (Vester, 2002) (Klein, 2007)

Table 1. Analytical hieratical process Weight basis.

*number only one time).*

#### **2.2 Cause effect diagram**

In addition to the "5xWhy", the cause effect diagram (Fig. 2), is very effective if there are people who already know a lot about the process. If they are used to it, they like thinking within cause and effect but still will be affected by suggestions from other team members to review their thought against the inputs from others and be motivated to think out of the box to find even more detailed reasons for product-rejects or process-failures. In combination with Brainstorming or the "5xWhy", it is even more focused and powerful.

Fig. 2. Cause and effect diagram(Rauwendaal).

### **2.3 Ishikawa diagram**

The Ishikawa diagram (Fig. 3) is the standard diagram to summarize cause and effect when concentrating on root cause and process-influence analysis. It is a good tool for discussing issues beyond the first impressions of why a process did and does not work or a product will not fulfill quality requirements. This is because this tool will guide the focus from different sources to a correlation of sources each time with a focus on a different rejectreason or process-failure. When meetings get stuck (because thoughts are spinning around) focus can be easily reset to another M-block1. In many cases, the output can be transferred to a FMEA "*Failure Mode and Effects Analysis"* or vice versa. The source of costs and process rejects are always defined by the product specification. Lowering these by adapting tolerances will instantly guide to lower costs, but may be critical for the next customer in a process line or the end customer who buys the product. The factor and its correlated target tolerances should be as wide as possible and as narrow as necessary.

#### **2.4 AHP: Analytical Hieratical Process**

Things are not always easy to interpret. Therefore, the AHP (combined with a grid analysis) is a very powerful tool to extract insights from a complex or fuzzy process. With process diagrams, Ishikawa diagrams or mind maps, the most influential factors are collected and can now be ranked according to Pareto's 20/80 law. This can be done by giving every team

<sup>1</sup> M-blocks are: Man, machine, management, measurement, method, material, milieu

36 Some Critical Issues for Injection Molding

In addition to the "5xWhy", the cause effect diagram (Fig. 2), is very effective if there are people who already know a lot about the process. If they are used to it, they like thinking within cause and effect but still will be affected by suggestions from other team members to review their thought against the inputs from others and be motivated to think out of the box to find even more detailed reasons for product-rejects or process-failures. In combination

**Cooling too fast**

**Vent flow**

**Plugged vent port Not enougth vacuum**

**Voids in products**

The Ishikawa diagram (Fig. 3) is the standard diagram to summarize cause and effect when concentrating on root cause and process-influence analysis. It is a good tool for discussing issues beyond the first impressions of why a process did and does not work or a product will not fulfill quality requirements. This is because this tool will guide the focus from different sources to a correlation of sources each time with a focus on a different rejectreason or process-failure. When meetings get stuck (because thoughts are spinning around) focus can be easily reset to another M-block1. In many cases, the output can be transferred to a FMEA "*Failure Mode and Effects Analysis"* or vice versa. The source of costs and process rejects are always defined by the product specification. Lowering these by adapting tolerances will instantly guide to lower costs, but may be critical for the next customer in a process line or the end customer who buys the product. The factor and its correlated target

**Inefficient venting**

Things are not always easy to interpret. Therefore, the AHP (combined with a grid analysis) is a very powerful tool to extract insights from a complex or fuzzy process. With process diagrams, Ishikawa diagrams or mind maps, the most influential factors are collected and can now be ranked according to Pareto's 20/80 law. This can be done by giving every team

tolerances should be as wide as possible and as narrow as necessary.

1 M-blocks are: Man, machine, management, measurement, method, material, milieu

with Brainstorming or the "5xWhy", it is even more focused and powerful.

**Volatieles**

**2.2 Cause effect diagram** 

**Degradation**

Fig. 2. Cause and effect diagram(Rauwendaal).

**Contamination**

**Air entrapment**

**2.4 AHP: Analytical Hieratical Process** 

**2.3 Ishikawa diagram** 

**Moisture**

Fig. 3. Ishikawa diagram, (Rauwendaal).

member the chance to write the numbers from one (very important) to ten (less important) behind the collected factors on a white board, or perform a simple hand-up voting (*each number only one time).*

After this is done, a maximum of ten factors of importance should be placed in the following matrix and weighted pairwise according to the importance of their influence. The direction of the questions is row versus column (Fig 4). Within the AHP, importance is leveled after the following scheme. (Vester, 2002) (Klein, 2007)


Table 1. Analytical hieratical process Weight basis.

In general, I recommend doing the weighting vice versa instead of filling the counterpart question automatically *(space below grey diagonal)*. Asking the questions "how much more is "Factor A" important than "Factor B"" and asking the opposite question staggered "how much more is 'Factor B' important than 'Factor A'"- again, will show the uncertainty of the knowledge and make it possible to reflect this fact within the grid diagram. In most cases, it is helpful to visualize the customers' demands prior to the factor ranking. A valuable input for defining customer values against product/process costs is for instance the "Kano model. If the prioritized quality criterion is not available, it needs to be developed because, in most cases, some target functions are more important to achieve then others, so compensating factor settings need to be developed after ranked target functions. On the grid-diagram (Fig. 5) the factors "holding pressure" and "nozzle temperature" are displaced a little bit laterally; this is because of the contradictorily ranked answers summarized in the matrix. Because of this inconsistency, influence of these factors should be discussed again. At some places, due

Besides the factor ranking, it is also important to get an understanding how these factors influence each other. For this reason, a similar matrix can be used in addition to a new question structure. Now the question should be: "Does factor 'A' reinforce the influence of factor 'B'?". In posing this question, one can get a better understanding of how the factors are correlated to each other or, in other words, how strong the interactions between these factors are. Thus the impact of potential contradictions can be exposed and documented. This is one of the most important project-management steps because of the necessary risk assumption. If the contradictions in the requirements are too stark to be compensated, the team needs to discuss whether the project should be stopped because of these "show stoppers" or "scope creepers". In any case, the risks should be displayed in a diagram which illustrates the probability of occurrence over the importance/impact of the risks. If there are any show-stoppers (i.e. risks with a large negative influence on the project and a high potential to occur) and they cannot be prevented, tools like TRIZ3 may be helpful in resolving the contradictions. "TRIZ is problem-solving, analysis and forecasting tool derived from the study of patterns of invention in the global patent literature". In English the name is typically rendered as "the Theory of Inventive Problem Solving", and

A more recent approach to understanding process and complexity is to model the system interaction or dynamic. One interactive, easy-to-use software is the Consideo Modeler, which was used for Fig. 6, 7, 8, 9. At the beginning, this approach works similarly to mind mapping but can calculate feedback loops later on in order to visualize the system's dynamic. After the most influential factors have been collected and ranked due to importance, those factors can be connected with arrows to describe their impact. These arrows can be defined with the intensity of the factor-effect, the cause-direction *(enhancing, reducing),* and the time-dependence of their effect (Fig. 6). One other advantage of this software-approach is that also "attributive" and "qualitative" factors can be embedded into the net-diagram. These factors are treated mathematically equally to quantitative factors in a first step. This is possible because the impact of the feedback loops of each factor *(factorarrowsfactor loops)* will be calculated iteratively. From this, the influence of the factors to a response can be interpreted. This method is also useful for visualizing what has been worked out in a "team problem discussion" by displaying the result of the extracted process on a net diagram (Fig. 6). After this, plots such as a "weighting matrix "(Fig. 9), in addition to the AHP (see 2.4) "root cause" and "cause and

Field "active": factors with strong influence Field "critical" : factors with ambivalent influence

Field " interactions" : factors with possible interactions

Field "less important" : factors with less impact

**Field Meaning** 

Table 2. Interpreting of the grid (Fig. 5).

occasionally goes by the English acronym TIPS.

<sup>3</sup> TRIZ / TIPS for more information see http://en.wikipedia.org/wiki/TRIZ

**2.6 System modelling** 

**2.5 Contradictions and correlation** 


Fig. 4. AHP Matrix2.

#### Fig. 5. AHP Grid.

to the complexity and a time reduction approach, it is sometimes recommended to do just a bilateral comparison-matrix with the part either below or on top of the grey diagonal. The other counterpart could also be filled out by asking or by being automatically computed. Often, therefore, the simplified schematic "2" = "more important"; "1" = "equal" and "0" = "less important" is used. This is also a good approach but will not be as differentiated as the previous AHP method.

In both cases, the factors can be weighted after importance by calculating the ranked row numbers at column "sum active ranked". This number and the calculated counterpart "sum passive rank" have to be plotted into the grid to visualize the factors' influence.

Now a new level of information has been extracted from the discussion. And the factors' importance can now be documented with the support of the whole team.

<sup>2</sup> Software Excel 2010, software operator S. Moser


Table 2. Interpreting of the grid (Fig. 5).

#### **2.5 Contradictions and correlation**

38 Some Critical Issues for Injection Molding

to the complexity and a time reduction approach, it is sometimes recommended to do just a bilateral comparison-matrix with the part either below or on top of the grey diagonal. The other counterpart could also be filled out by asking or by being automatically computed. Often, therefore, the simplified schematic "2" = "more important"; "1" = "equal" and "0" = "less important" is used. This is also a good approach but will not be as differentiated as the

In both cases, the factors can be weighted after importance by calculating the ranked row numbers at column "sum active ranked". This number and the calculated counterpart "sum

Now a new level of information has been extracted from the discussion. And the factors'

passive rank" have to be plotted into the grid to visualize the factors' influence.

importance can now be documented with the support of the whole team.

Fig. 4. AHP Matrix2.

Fig. 5. AHP Grid.

previous AHP method.

2 Software Excel 2010, software operator S. Moser

Besides the factor ranking, it is also important to get an understanding how these factors influence each other. For this reason, a similar matrix can be used in addition to a new question structure. Now the question should be: "Does factor 'A' reinforce the influence of factor 'B'?". In posing this question, one can get a better understanding of how the factors are correlated to each other or, in other words, how strong the interactions between these factors are. Thus the impact of potential contradictions can be exposed and documented. This is one of the most important project-management steps because of the necessary risk assumption. If the contradictions in the requirements are too stark to be compensated, the team needs to discuss whether the project should be stopped because of these "show stoppers" or "scope creepers". In any case, the risks should be displayed in a diagram which illustrates the probability of occurrence over the importance/impact of the risks. If there are any show-stoppers (i.e. risks with a large negative influence on the project and a high potential to occur) and they cannot be prevented, tools like TRIZ3 may be helpful in resolving the contradictions. "TRIZ is problem-solving, analysis and forecasting tool derived from the study of patterns of invention in the global patent literature". In English the name is typically rendered as "the Theory of Inventive Problem Solving", and occasionally goes by the English acronym TIPS.

### **2.6 System modelling**

A more recent approach to understanding process and complexity is to model the system interaction or dynamic. One interactive, easy-to-use software is the Consideo Modeler, which was used for Fig. 6, 7, 8, 9. At the beginning, this approach works similarly to mind mapping but can calculate feedback loops later on in order to visualize the system's dynamic. After the most influential factors have been collected and ranked due to importance, those factors can be connected with arrows to describe their impact. These arrows can be defined with the intensity of the factor-effect, the cause-direction *(enhancing, reducing),* and the time-dependence of their effect (Fig. 6). One other advantage of this software-approach is that also "attributive" and "qualitative" factors can be embedded into the net-diagram. These factors are treated mathematically equally to quantitative factors in a first step. This is possible because the impact of the feedback loops of each factor *(factorarrowsfactor loops)* will be calculated iteratively. From this, the influence of the factors to a response can be interpreted. This method is also useful for visualizing what has been worked out in a "team problem discussion" by displaying the result of the extracted process on a net diagram (Fig. 6). After this, plots such as a "weighting matrix "(Fig. 9), in addition to the AHP (see 2.4) "root cause" and "cause and

<sup>3</sup> TRIZ / TIPS for more information see http://en.wikipedia.org/wiki/TRIZ

This approach *(and also the shortly described preceding methods)* will not deliver a whole picture of the process or an ideal setup, but it will help to concentrate on the really important factors. Furthermore, these tools will help to document the problem-solving process and to support the team in working results oriented and step by step -- in order to do the right

So within difficult problems, tools are capable of raising the creative nouveau of generating innovative ideas or solutions. Instead of only endless problem-focused discussions, which only lead to "questions of power", "influence", "the problem history" and "particular blame" of team members, using supporting tools means the team can concentrate on solving problems by using the tools right! This helps to minimize distracting, time-consuming and

After the "root cause analysis", factor prioritization and response target definition are done, it is necessary to review these values with a focus on "good project management practice".

Fig. 8. Cause tree 4.

Fig. 9. Weighting matrix 4.

things right.

conflicted meetings.

**2.7 Restrictions within familiarization steps** 

**2.8 Reflecting the familiarization steps** 

effect" diagrams (Fig. 8) can be easily generated, as well as the "insight matrix" (Fig. 7), to show how the factors affect responses.

Fig. 6. Example "net diagram"4.

Fig. 7. Example Insight Matrix4 of factor "color steaks".

<sup>4</sup> Software Consideo Modeler, www.consideo.com , software operator S. Moser

Fig. 8. Cause tree 4.

effect" diagrams (Fig. 8) can be easily generated, as well as the "insight matrix" (Fig. 7), to

show how the factors affect responses.

Fig. 6. Example "net diagram"4.

Fig. 7. Example Insight Matrix4 of factor "color steaks".

4 Software Consideo Modeler, www.consideo.com , software operator S. Moser


Fig. 9. Weighting matrix 4.

#### **2.7 Restrictions within familiarization steps**

This approach *(and also the shortly described preceding methods)* will not deliver a whole picture of the process or an ideal setup, but it will help to concentrate on the really important factors. Furthermore, these tools will help to document the problem-solving process and to support the team in working results oriented and step by step -- in order to do the right things right.

So within difficult problems, tools are capable of raising the creative nouveau of generating innovative ideas or solutions. Instead of only endless problem-focused discussions, which only lead to "questions of power", "influence", "the problem history" and "particular blame" of team members, using supporting tools means the team can concentrate on solving problems by using the tools right! This helps to minimize distracting, time-consuming and conflicted meetings.

#### **2.8 Reflecting the familiarization steps**

After the "root cause analysis", factor prioritization and response target definition are done, it is necessary to review these values with a focus on "good project management practice".

important because the basis of an entire image of it can be mapped on the work-space. The screening-process starts to extract the most influential factors from the familiarization process. These factors will be used to start with the Design of Experiments method. But not necessarily all factors must be examined in light of variability. So, some of these less important factors should be frozen at a certain level, which still ensures a good product quality. This is because the number of factors substantially affects the sum of the experiments; the number of evaluation criteria (responses) is of secondary importance. In the best case, the factors are quantitative, and so simple geometric designs can be generated. It is more difficult when they are qualitative, e. g. "machine 1" or "machine 2". Such qualitative or attributive parameters increase the number of experiments because they hamper the generation of the design. Once the factors have been identified, it is necessary to assess their effect. The effect is that which is exerted on the target variable when the factor is varied from its minimum to its maximum setting. Since all the factors are changed

It is therefore useful to debate and determine the factor variations within a group of experienced staff. Some factors are even trickier to formulate than the qualitative factors, such as temperature or pressure profiles. Just as in the machine, in the factorial experiment, the profiles can be programmed with some nodes such as (initial value + 9 nodes). The start and end values of the profile are known. Moreover, the process specifies a sloping curve (Fig 12, 13). If the profiles were programmed with real numbers, the sloping profile would necessitate the use of a great many programmed extra constraints. These factor restrictions limit the choice of experimental models and greatly increase the number of necessary experiments. For this reason, a mathematical formulation of the profiles is recommended which allows restrictions to be dispensed with entirely. Thus, the pressure profile is calculated, for instance, from the

The following variation thus

Node (i +1) = node (i) – (min. 0, max. Δp) (2)

arises for each node in (2): (1)

b0 = bias ; � � ����� (3)

simultaneously in a factorial design, this effect is difficult to estimate.

given initial value and the maximum decrease in pressure (in bar) per node:

Another way to represent the profile is the use of a simple two point (FU 3).

value of factor setting��� � �� � �� � � m = *Cf. (*4) ; x = node of factor profile;

initial value �a�� � en� value �in� nu��er of no�es � �

Fig. 11. Process Black-Box.

�� �

Therefore, it has to be considered that doing a research on all desired functions will take time and will consume money and resources. In most projects, there is the sword of Damocles over the project team, which means that there is always not enough time, money and resources. In this context, one often hears a contradiction in terms such as, "We do not have the time for experiments ". This interaction is visualized in Fig. 10.

To briefly illustrate, it can be assumed that the functions to be examined need too much time. These circumstances can only be compensated by moving the timeline or tapping additional resources. Both options will impact the budget. Thus, it is always important to check at regular intervals if any (planned) actions are still result-related and necessary.

Fig. 10. Interaction between the main components of project management.
