Overview

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To understand Econ and Tech scores the main metrics enabling to sort, filter and prioritize parts within the platform, it is important to understand what information is considered and how it is processed to get to a result.

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The graph to the right describes exemplary the relation among a part’s properties, blackboxes, and scores.

• Each part is made up of a number of properties and corresponding values.

• Blackboxes are small functions that evaluate one or several part properties by reading their values and calculating a result.

• The blackbox results are fed into scores where they are aggregated and produce a score result.

Calculating an Econ Score

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• The potential of the part is related to its economic parameters. We evaluate the current part lead time, cost, potential savings to conclude if an economic opportunity arises.

• The feasibility is related to the technical parameters. We evaluate the part size, material, presence of holes, thin walls, aspect ratio and support structure for additive manufacturing suitability.

• The priority of the part represents a concatenation of the two above metrics. Depending on the result, it is classified as the following:

  • Highest - The part shows a high business opportunity and technical feasibility. The part should be realised.

  • High - The part shows either a high business opportunity or is technical feasible. The part should be considered for realisation but should be further assessed.

  • Medium - The part shows medium business opportunities and feasibly. The part should be further assessed as data might be missing.

  • Low - The part shows either a low business opportunity or is technical not feasible. The part should be put on-hold.

  • Very Low - The part shows a low business opportunity and is technical not feasibility. The part should be rejected.

Calculating the Potential

By convention, the evaluation of the potential results lie between 0 and 1, whereby 0 indicates poor suitability and 1 perfect suitability. The results in the [0, 1] interval are displayed as percentage values from 0% to 100% in the user interface.

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An econ score might consist of the following blackboxes - the properties that are evaluated by each blackbox - and a weight that informs how much impact an individual blackbox has in relation to the other blackbox results.

In the above example, the blackbox Selection logic lead time savings has the strongest lowest impact on the econ score.

The results of the score calculation are displayed for each part and each score in an overview:

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• Factor
  The blackbox - and thus the corresponding properties - that are considered for the score

• Score
  The individual result which is calculated by the corresponding blackbox - without applying weights.

• Impact
  The weight, or impact, this blackbox should have in the overall calculation

• Subscore
  The weighted result of each blackbox how it is considered for the overall score calculation

Calculating a Tech Score

The Tech score is calculated in a similar manner as the Econ score by applying the Weighted Average on a set of blackbox results.

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Blackbox

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Properties incl. Type

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Weight

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Geometry

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• Size

• Part geometry

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1.0

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Material

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• Material

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0.4

Profiles with Different Weights

It is possible to look at the same part from different angles. Two typical cases for optimization are cost reduction and lead time improvement. It is possible to set up different Econ scores by including different blackboxes or adjusting the weights by which blackboxes impact the overall results. Thus different Profiles can be created that score parts according to different measurements.

By default, we have configured three different profiles by which to assess parts:

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General

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Cost reduction

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part’s potential.

Calculating a Feasibility

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Purpose

The Feasibility Scoring System evaluates multiple technologies for compatibility with specific design requirements, providing a score that represents the best technology choice based on weighted criteria. This allows users to assess which technology most effectively meets their part’s requirements.

Parameter Weights in the Feasibility Scoring System

Each parameter in the Feasibility Scoring System is assigned a specific weight that reflects its importance to the overall manufacturing success. Higher weights indicate parameters that are more critical to determining the feasibility of a technology for a particular design, while lower weights suggest factors that are influential but less decisive.

Key Parameter Weights

1. Material Class (High Weight, 40%):
   Material compatibility is a crucial factor, as it impacts the overall manufacturability and end-use performance of the part. A high weight here means that a technology’s suitability heavily depends on its ability to work with the required material.

2. Size Limitations (Maximum Size) (Moderate Weight, 12%):
   Size constraints are important but secondary, impacting the feasibility based on whether a technology can accommodate the dimensions of the part.

3. Structural Needs (Support Structure) (Moderate Weight, 12%):
   This considers the ability to incorporate or avoid support structures. A 12% weight reflects its moderate impact on determining feasibility.

4. Design-Specific Requirements (Wall Thickness, Holes, Aspect Ratio) (Moderate Weight, 12% each):
   Design-specific factors such as wall thickness, holes, and aspect ratio affect the manufacturability in unique ways based on each technology's limitations. Each of these factors receives an equal weight, collectively contributing significantly to the total score.

Combined Impact

The weighting system ensures that more critical factors like material class contribute substantially to the final score, while also accounting for important but secondary factors like size and specific design features. This balanced approach allows for a comprehensive assessment, focusing on essential requirements without disregarding secondary aspects.

Best Technology Selection

After calculating the feasibility scores for all available technologies, the system identifies and selects the highest-scoring technology as the optimal choice for the given requirements.

Result

The system outputs a final score, reflecting the best technology for the specified parameters, supporting informed decision-making for technology selection.

Calculating the Priority

The priority assesses and classifies the combined results of Potential and Feasibility scores, producing a final status based on predefined conditions. Each score reflects a key aspect of a technology's applicability, and the classification indicates the overall suitability.

Key Steps and Considerations

1. Score Calculation:

   • Both Potential and Feasibility scores are derived from respective evaluation functions, providing values between 0 and 1.

   • Averages are calculated, with missing scores treated as 0 in this specific context, ensuring a fair total even if one score is unavailable.

2. Result Classification:

   • Scores are classified into status icons based on thresholds:

     • Highest: Both scores are 66% or higher.

     • High: One score is 66% or above, and the other is mid-range (33%-66%) or missing.

     • Medium: Both scores fall in the mid-range (33%-66%), or one score is mid-range while the other is missing.

     • Low: One score is below 33% and the other is mid-range or missing.

     • Lowest: Both scores fall below 33%.

   • The classification captures the overall feasibility and potential, even if only partial information is available, guiding decision-making through intuitive status icons.

Final Output

The results are found in the KPI cards found below.

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