Polymer Selection Using a Weighted Decision Matrix

Hello. Last lesson established the inputs to a defensible polymer decision: compare specific grades under stated temperature, humidity, loading, fluid-exposure, and molding conditions. You also created the beginnings of a material screening register. This lesson turns that evidence into a controlled selection method.

A weighted decision matrix does not “prove” that a polymer is correct. It makes the reasoning visible: which requirements matter most, which candidates fail non-negotiable requirements, what manufacturing risks remain, and what evidence is still needed before release. That is exactly the distinction needed in an automotive program, where a material choice affects CAD dimensions, tooling strategy, supplier capability, validation, cost, and eventual engineering changes.

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A material matrix is a decision record, not a spreadsheet popularity contest

The Material Selection Decision Board is a useful first-pass visual: it connects needs such as heat resistance, flexibility, chemical resistance, and cost to broad material families. Use such a board to generate candidates and questions, not to select a production resin. It cannot tell you whether a particular 30% glass-filled, flame-retardant grade meets your wall thickness, color, processing window, electrical, and durability requirements.

For your projects, a material decision should have four layers:

1. Requirements and constraints: what the part must do, including non-negotiable conditions.
2. Candidate definition: the exact grade or, early in development, a clearly labelled family-level placeholder.
3. Weighted comparison: a transparent way to balance competing desirable properties.
4. Risk and evidence plan: what must be validated before the selection can become approved or released.

The essential rule is:

A candidate that fails a true constraint is eliminated. It cannot “win back” eligibility by being cheap, light, or attractive.

For example, a high-voltage ECU-housing polymer without sufficient verified electrical and flammability performance at the actual wall thickness is not made acceptable by excellent stiffness. Likewise, a door-trim carrier material that cannot meet an approved appearance requirement cannot remain the preferred choice merely because it is low density.

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Step 1: turn the component brief into gates and trade-off criteria

Start from your controlled requirements baseline, not from a favorite polymer. A requirement can become either:

• a constraint gate, which the candidate must pass;
• a weighted criterion, where several viable candidates have different levels of performance;
• an open evidence item, where a requirement exists but the current information is too weak to judge it.

Consider an assumption-based example for an ECU base. This is not a claim about an actual Rivian or Amazon EDV design; it is a training scenario that illustrates the method.

Requirement area	Example requirement statement	Matrix treatment
Electrical safety	Selected grade shall have verified required electrical properties and flame behavior at the declared minimum wall thickness and conditioning state.	Constraint gate
Thermal durability	Housing shall retain required function for the defined lifetime at its estimated local service temperature.	Constraint gate plus weighted criterion for margin
Structural function	Housing shall preserve mounting and sealing-land alignment under declared loads and temperatures.	Weighted criterion
Moisture response	Material behavior after humidity conditioning shall remain compatible with dimensional and electrical requirements.	Constraint gate if critical; otherwise weighted criterion
Chemical exposure	Housing shall resist declared cleaners, coolant, oils, salts, and other relevant fluids under defined stress and temperature.	Constraint gate plus weighted criterion for margin
Injection molding	Production process shall be capable of molding the geometry within acceptable warpage, fill, cycle-time, and scrap-risk limits.	Weighted manufacturing-risk criterion
Cost and supply	Candidate shall be available from approved or feasible suppliers within target total component cost.	Constraint gate for supply feasibility; weighted criterion for cost

A useful gate table is deliberately simple:

Candidate	Electrical and flame evidence	Service-temperature feasibility	Chemical compatibility	Supplier feasibility	Eligible for weighted comparison?
PA66-GF30 candidate	Open	Likely, grade-dependent	Open	Open	No — evidence pending
PBT-GF30 candidate	Open	Likely, grade-dependent	Open	Open	No — evidence pending
Flame-retardant PC/ABS candidate	Open	Open	Open	Open	No — evidence pending

At the early concept stage, all three may remain in the screening register, but none should be called “selected.” The table prevents a family-level assumption from quietly becoming a production decision.

Criteria should be measurable and non-overlapping

A weak criterion is “good durability.” A stronger criterion identifies the relevant mode of failure and the required evidence:

• Long-term stiffness and creep resistance at the relevant temperature.
• Low-temperature impact margin at weld lines, bosses, or likely abuse locations.
• Dimensional stability and warpage risk for sealing lands, flat covers, or visible bezels.
• Chemical and environmental stress-cracking resistance under specified cleaners and stress.
• Molding robustness, including flow into thin sections, drying sensitivity, shrinkage variation, and process-window width.
• Appearance robustness, including sink, fiber read-through, weld-line visibility, grain replication, and color stability.
• Mass and total cost, considering geometry, cycle time, scrap, finishing, drying, and warranty risk.

Avoid double-counting. If “warpage risk” has its own criterion, do not give it equal hidden weight again inside a generic “manufacturing risk” criterion. Either separate risks clearly, or define a combined manufacturing criterion that excludes risks already scored elsewhere.

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Step 2: use real evidence, including the evidence that is missing

The score in each cell must have a source. During concept development, that source may be a supplier technical data sheet, a processing guide, an approved material database, previous validated application data, or a planned test. It should never be “common knowledge.”

Separate performance score from evidence confidence

It is tempting to hide uncertainty by assigning a middle score such as $3$. Do not do this. A score of $3$ should mean known, moderate performance against a defined criterion, not “we do not know.”

Use two separate fields:

Field	Meaning	Example
Performance score	How well the candidate meets a defined criterion, based on available evidence.	PBT-GF30 scores $4$ of $5$ for moisture stability.
Evidence confidence	Strength and applicability of the supporting information.	Confidence is low because the evidence is family-level rather than from an approved grade.
Decision status	What action follows from score and confidence.	Keep candidate in concept phase; obtain supplier grade data and conditioned test evidence.

A practical confidence scale is:

• High: controlled, grade-specific data under applicable conditions, ideally supported by relevant validation or established use.
• Medium: grade-specific data exists, but component geometry, environment, or aging conditions still require validation.
• Low: family-level knowledge, non-comparable data, or supplier claims without adequate conditions.
• Unknown: no usable evidence.

An unverified critical requirement remains a gate failure or an open risk. It is not solved by assigning a favorable score.

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Step 3: choose a scoring scale before looking at candidates

A matrix is more credible when the scoring rules are defined before candidate scores are entered. A $1$-to-$5$ scale is usually enough for an early engineering trade study.

Score	Meaning for a positive criterion, such as thermal margin or molding robustness
$5$	Clearly exceeds the requirement with meaningful margin and low residual risk.
$4$	Meets the requirement with useful margin; manageable validation or process work remains.
$3$	Meets the requirement nominally, but with limited margin or substantial controls required.
$2$	Likely weak against the requirement; a redesign, special process, or major mitigation is needed.
$1$	Poor fit even if not formally disqualified by a gate.
$0$	Fails a constraint or lacks required minimum evidence; eliminate or hold outside the comparison.

For criteria where less is better, such as density, shrinkage variation, cost, or residual manufacturing risk, reverse the interpretation: a score of $5$ represents the lowest acceptable cost or risk.

Where quantitative data are available, define score bands. For instance, a component requirement may define minimum flexural modulus at service temperature, and the score bands may correspond to increasing margin above that minimum. This is much more defensible than scoring a material as “high stiffness” by intuition.

For a continuous, higher-is-better measurement $x$, a normalized score can be calculated as:

$$s_{ij}=5\frac{x_{ij}-L_i}{U_i-L_i}$$

Here, $L_i$ and $U_i$ are the lower and upper bounds selected for criterion $i$, while $s_{ij}$ is the score for candidate $j$. In practice, clamp scores below $0$ to $0$ and scores above $5$ to $5$.

For lower-is-better measures:

$$s_{ij}=5\frac{U_i-x_{ij}}{U_i-L_i}$$

Do not normalize incompatible data merely because a formula permits it. First ensure that units, test standards, specimen conditions, temperature, humidity, and material states are comparable.

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Step 4: assign weights based on consequence, not preference

Weights represent the consequence of being weak in a particular area. They are not a declaration that every highly weighted requirement can be traded away.

A simple and readable convention is to assign weights totaling $100$. The total score is then also out of $100$:

$$T_j=\sum _{i=1}^n{w}_i\frac{s_{ij}}{5}$$

where:

• $T_j$ is the total for candidate $j$;
• $w_i$ is the percentage weight of criterion $i$;
• $s_{ij}$ is the $0$-to-$5$ score;
• the weights sum to $100$.

For the illustrative ECU-base scenario, the team might assign the following weights after reviewing the requirements baseline and preliminary DFMEA concerns:

Criterion	Weight	Why it matters
Long-term temperature capability	$20$	Loss of housing stiffness or integrity at temperature can compromise sealing and mounting.
Dimensional stability and warpage	$15$	Flatness and sealing-land alignment affect ingress performance and assembly.
Moisture-conditioned electrical and dimensional behavior	$15$	The housing supports electrical isolation and must remain stable after environmental exposure.
Stiffness and creep resistance	$15$	Mounts, inserts, fasteners, and sealing compression can introduce sustained loads.
Chemical and stress-cracking resistance	$10$	Service and cleaning fluids can interact with molded-in stress and assembly load.
Impact robustness	$10$	Handling, service, and vehicle vibration-related events require margin.
Molding robustness	$10$	Drying, fill, weld-line, anisotropic shrinkage, warpage, and scrap affect feasibility.
Total component cost and supply risk	$5$	Important, but not permitted to dominate safety and durability requirements.
Total	100

This allocation is not universal. For a visible door carrier, appearance and sink/read-through risk may deserve considerably more weight. For HVAC vanes and linkage components, wear, friction, dimensional stability, and audible rattle risk may become more significant than high-temperature structural capability.

Weights require review and approval because they contain engineering judgment. Record:

• decision owner;
• participants and functions represented, such as design, CAE, materials, manufacturing, purchasing, quality, and supplier engineering;
• requirements baseline revision;
• rationale for each weight;
• date and decision maturity;
• unresolved assumptions.

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Step 5: score manufacturing risk explicitly

Manufacturing risk should not appear as a vague comment at the bottom of the matrix. It needs an explicit criterion or sub-criteria linked to likely injection-molding failure modes.

For each candidate, document the chain of reasoning:

Risk topic	What to assess	Typical evidence
Flow and filling	Can the grade fill the minimum wall, long flow length, ribs, and feature transitions?	Melt-flow data under comparable conditions, molding simulation, supplier input, trials
Warpage	Does shrinkage directionality interact badly with flat surfaces, sealing lands, or visible surfaces?	Grade shrinkage data, fiber-orientation prediction, mold-flow evidence, trial measurements
Drying sensitivity	Can moisture control be maintained in production, and what occurs if it is not?	Supplier processing window, dryer requirements, supplier process-control plan
Sink and read-through	Are thick bosses, ribs, and B-side features compatible with visible-surface criteria?	DFM review, surface trials, mold-flow packing and shrinkage results
Weld lines and air traps	Are potential knit lines located away from high-load, sealing, or cosmetic regions?	Gate concept, fill analysis, prototype and tool trial evidence
Supply and color consistency	Is the approved grade, color, recycled-content specification, and regional supply chain stable?	Supplier qualification, specification, color approval, purchasing assessment

A matrix score should reflect residual risk after realistic controls, not wishful thinking. “We can solve it in tooling” is not a control unless there is a plausible tooling action, owner, cost and timing impact, and verification method.

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Worked example: an early ECU-housing family-level trade study

Suppose the early ECU study compares three screening candidates:

• PA66-GF30;
• PBT-GF30;
• flame-retardant PC/ABS.

The following scores are illustrative only. They are not grade-specific data and do not select any polymer for the future ECU project. Their purpose is to show calculation and interpretation.

Criterion	Weight	PA66-GF30	PBT-GF30	Flame-retardant PC/ABS
Long-term temperature capability	$20$	$4$	$4$	$3$
Dimensional stability and warpage	$15$	$2$	$3$	$4$
Moisture-conditioned electrical and dimensional behavior	$15$	$2$	$4$	$3$
Stiffness and creep resistance	$15$	$5$	$4$	$2$
Chemical and stress-cracking resistance	$10$	$4$	$3$	$2$
Impact robustness	$10$	$3$	$3$	$5$
Molding robustness	$10$	$2$	$3$	$4$
Total cost and supply risk	$5$	$3$	$3$	$4$

For PBT-GF30’s temperature criterion, the weighted contribution is:

$$20\frac{4}{5}=16$$

Applying the same calculation to all criteria gives:

Candidate	Illustrative weighted total	Interpretation
PA66-GF30	$64$	Strong stiffness and thermal potential, but moisture and fiber-related molding risks need careful control.
PBT-GF30	$70$	Best balance in this particular assumption set, especially for moisture stability and stiffness, but warpage, fill, chemical details, and flame performance remain grade-specific questions.
Flame-retardant PC/ABS	$65$	Favorable impact and dimensional tendencies, but thermal, chemical, creep, electrical, and flame performance need close grade-specific scrutiny.

The appropriate conclusion is not “PBT-GF30 has been selected.” It is:

Under the stated, assumption-based weighting and preliminary family-level evidence, PBT-GF30 is the preferred candidate for further investigation. Its suitability remains conditional on passing the defined gates using a specified grade and on closing listed manufacturing and validation risks.

That is a conclusion a design-review team can interrogate productively.

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Step 6: challenge the result before adopting it

A matrix is trustworthy only if it can survive reasonable challenge. Perform four checks.

1. Constraint check

Confirm again that the apparent winner passes every mandatory gate. If required data are unavailable, identify the decision as conditional rather than approved.

2. Sensitivity check

Change one or two influential weights within a reasonable range and observe whether the ranking changes. If a small change reverses the result, the decision is sensitive. That does not invalidate the matrix; it tells you where additional data or stakeholder alignment is required.

For example, if low-temperature impact is more critical than initially understood, PC/ABS may become more competitive. If humidity-conditioned dimensional stability is elevated in importance, a polyamide candidate may fall in rank unless its behavior is controlled and validated.

3. Evidence-quality check

Ask whether the leading candidate is leading because it has genuinely better properties or simply because it has better available brochures. A lower-confidence score must produce an evidence action, not an unexamined assumption.

4. Engineering-reality check

Review the winner against actual geometry and manufacturing concept:

• wall-thickness range;
• rib and boss design;
• expected gate locations;
• required flatness and gap-and-flush;
• welding, fastening, inserts, and gasket compression;
• appearance zones;
• supplier molding capability;
• service fluids and environmental conditioning.

The next module outcomes on cooling time, clamp force, wall transitions, ribs, bosses, draft, and molding defects will provide more specific evidence for this review.

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Make the matrix PLM-ready

For each component project, create a controlled decision record rather than leaving the matrix as an unnamed spreadsheet.

A practical record structure is:

Field	Example content
Decision ID	MAT-SEL-ECU-001
Object	ECU base housing, preliminary material selection
Applicable requirements	Requirement IDs from the approved requirements baseline
Candidate list	Exact grade identifiers, supplier, color, reinforcement, flame-retardant status, and revision where known
Constraint gate	Pass, fail, open, or not applicable for every mandatory requirement
Weighted matrix	Weights, score rules, source references, calculated totals, and confidence levels
Key risks	Warpage, moisture conditioning, chemical exposure, welding, sink, supply, or others
Verification plan	Required supplier data, coupons, mold-flow evidence, prototype trials, and component tests
Decision	Preferred candidate, backup candidate, conditionality, and rationale
Maturity and approval	Draft, reviewed, approved for prototype, released for production, or superseded
Change linkage	ECO or engineering-change identifier if later evidence changes the selection

In an ENOVIA-managed environment, this could be linked to the part, material specification, requirements object, simulation evidence, supplier package, drawing, EBOM, and change object. With Onshape, maintain the CAD material property and document revision deliberately, then link the controlled matrix, requirements register, risk log, and approval record through your project register.

The important principle is traceability: when a supplier proposes a substitute resin, you must be able to determine which requirements, scores, validation evidence, CAD properties, tooling assumptions, drawings, and BOM entries are affected.

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Key takeaways

A weighted polymer decision matrix is valuable because it exposes reasoning, trade-offs, and uncertainty. Used well, it supports engineering judgment rather than replacing it.

• Start with constraint gates. A failed safety, durability, regulatory, supply, or functional requirement cannot be compensated for by a high weighted score.
• Define measurable, non-overlapping criteria from component requirements and expected molding risks.
• Score material performance separately from evidence confidence.
• Use weights to represent program consequence and requirement importance; keep the weights visible, justified, and controlled.
• Include manufacturing risks such as warpage, drying, flow, weld lines, sink, and process-window capability explicitly.
• Treat an early family-level result as a conditional recommendation, not a released material selection.
• Record the matrix, risks, assumptions, evidence sources, approvals, and future validation actions as a controlled PLM-linked decision.

Next, you will move from comparative material judgment into an early quantitative manufacturing calculation: estimating injection-molding cooling time using a one-dimensional heat-transfer model and stated assumptions.