Manufacturing
DayIdeas become things.

Learning goal: use a written requirement and repeated measurements to judge consistency.

Materials per team: paper, a ruler marked in millimeters, pencil, child-safe scissors or prepared strips, and a recording sheet.

1. Set a shared requirement: six paper strips, each 100 mm long and 20 mm wide. Accept dimensions within ±2 mm. Model how to align the ruler’s zero mark.
2. Make three strips individually. Measure both dimensions, record the values and mark which pass. Keep every result, including rejects.
3. Create a template or simple positioning guide, then make three more strips. Test them with the same ruler and requirement.
4. Compare acceptable counts and the spread of measurements. Discuss why a template may help but still needs checking.

Evidence to keep: a six-row measurement record and one sentence naming a process change supported by the results.

Check understanding: ask why changing the acceptance limit after making the strips would weaken the comparison.

Extend: give another team the written requirement and compare how easily they reproduce it. Prepare strips in advance and let learners focus on inspection if cutting is a barrier.

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Learning goal: distinguish activity at one station from completed, acceptable output.

Materials per team: 20 paper rectangles, pencils, stickers or stamps, a timer and a tally sheet. Assign three makers and an observer; rotate roles.

1. Define a paper “product”: fold a rectangle in half, draw four circles on its front, and add a mark inside every circle. Write the acceptance rule before starting.
2. Assign one step to each station. Run for three minutes at a comfortable pace. The observer counts finished acceptable products, rejects and items waiting between steps.
3. Identify where work accumulates. Change one process condition—such as moving one drawing task to another station—while preserving the product requirement and team size.
4. Run another three-minute round. Compare acceptable output and queues, not just how fast individual people worked.

Evidence to keep: a before-and-after flow sketch, output totals and a reasoned explanation of the constraint.

Check understanding: would doubling the speed of the fastest step necessarily double finished output? Connect the answer to the online line lab.

Extend: compare batches of five with moving one item at a time, while holding other conditions constant. Let learners use prepared symbols or accessible tools.

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Learning goal: compare material use and protective performance using an agreed test.

Materials per team: the same small paper model to protect, scrap paper, cardboard, tape, ruler and a scale if available. Use a clear, supervised drop area; no fragile or valuable objects.

1. Choose an acceptance rule for the model, such as no visible bend after a 30 cm drop. Agree on the orientation, surface and number of trials before designing.
2. Build a package from a fixed starting quantity of paper, cardboard and tape. Record material mass, or count equal-sized sheets and tape lengths if no scale is available.
3. Run three trials using the agreed method. Record every pass and failure, along with damage to the package.
4. Redesign to use less material. Repeat the same test and compare the evidence. Explain whether the reduction was worth any change in protection.

Evidence to keep: a material-use table, trial results and a recommendation with one limitation.

Check understanding: less material is not automatically a lower overall environmental impact if more products are damaged. What else would you need to know?

Extend: investigate local recycling instructions for the materials used. Label this as a classroom comparison, not a validated shipping or life-cycle assessment.

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Learning goal: compare process variation and first-pass yield before and after one controlled change.

Materials per team: 20 index cards or equal paper rectangles, rulers, pencils, a cardboard alignment guide and a data sheet.

1. Set a requirement: a mark 20 mm from the left edge and 15 mm from the bottom edge, with ±1 mm allowed in each direction. Make and measure ten cards using a ruler for each card.
2. Record both dimensions for every card. Calculate first-pass yield: acceptable cards ÷ all cards × 100. Find the range of each measured dimension.
3. Use a simple alignment guide to position ten new cards and mark the same point. Keep the operator, materials and acceptance rule unchanged.
4. Compare yields and ranges. Inspect the guide itself: a repeatable process can still place every mark in the wrong location.

Evidence to keep: two small data tables, before-and-after plots and a claim that distinguishes consistency from accuracy.

Check understanding: can a sample of ten establish the long-term performance of a production line? Explain the uncertainty and what more data might reveal.

Extend: swap operators or repeat with a new guide, changing one factor at a time. Discuss when checking a process could prevent mistakes earlier than final inspection.

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Learning goal: Separate an observation from an inference while mapping how a product is made.

Materials per team: A notebook or cardboard package, paper, pencils and sticky notes. Use objects that can be inspected without taking them apart.

1. List the parts and materials you can actually see. Mark uncertain material identifications with a question mark.
2. Arrange cards for sourcing, shaping, joining, checking and packing. Draw arrows and explain the order you propose.
3. Choose one step and write a requirement, such as pages staying attached when turned. Describe a classroom-safe check.
4. Exchange maps. Label each claim as observed, inferred or still needing research; revise one unsupported claim.

Evidence to keep: An annotated process map with at least one observation, inference and unanswered question.

Check understanding: Which details could you establish by looking at the object, and which need a manufacturer’s explanation?

Extend: Compare two versions of the same product and identify a process decision that might explain a visible difference.

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Learning goal: Translate a user need into measurable success criteria.

Materials per team: Paper, pencils, rulers, scrap card, tape and five pencils for testing a desk holder.

1. Interview a partner about keeping pencils on a desk. Record the need without choosing a solution yet.
2. Agree on three criteria: hold five pencils, fit inside a 10 × 10 cm footprint, and remain upright for 30 seconds on a level desk.
3. Sketch two possibilities, choose one and build a card model. Test each criterion separately and record pass or fail.
4. Revise one feature and retest with the same pencils, surface and criteria.

Evidence to keep: A brief, labeled sketch and three-criterion test table for both versions.

Check understanding: How is ‘works well’ different from a requirement another team can measure?

Extend: Add a material limit and explain which design choice becomes more difficult.

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Learning goal: Communicate a simple part using dimensions, reference edges and views.

Materials per team: Squared paper, rulers, pencils and teacher-prepared L-shaped card pieces.

1. Measure an L-shaped piece and make a drawing with overall length, width and cutout dimensions. State millimeters as the unit.
2. Exchange only the drawing with another team. Have them draw the part on fresh squared paper without seeing the original.
3. Compare their drawing with the original piece. Record missing, contradictory or ambiguous information.
4. Revise the drawing and repeat the exchange. Use a shared ±2 mm acceptance limit for the comparison.

Evidence to keep: Two drawing versions and a record of the receiving team’s questions and dimensional differences.

Check understanding: Why does an attractive picture still need dimensions and a stated unit?

Extend: Add a side view of a folded card part and explain which information the top view cannot show.

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Learning goal: Compare assembly effort while holding a product’s function constant.

Materials per team: Scrap card, tape, rulers, teacher-prepared parts and a timer.

1. Build a small card display stand that holds the same index card upright for one minute. Count parts, joins and assembly steps.
2. Ask a partner to assemble a second copy from your instructions. Time the work at a comfortable pace and record questions or errors.
3. Redesign to remove a part or join while keeping the same stability requirement.
4. Repeat the assembly trial, then compare time, acceptable builds and ease of repair. A faster failed stand does not count as improvement.

Evidence to keep: A parts list, before-and-after assembly record and a recommendation tied to the test.

Check understanding: What else changed besides the number of parts, and could that affect your result?

Extend: Repeat with a new assembler to explore how practice influences timing.

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Learning goal: Use a cutting layout to compare material utilization.

Materials per team: Equal sheets of squared paper, rulers, pencils and card templates measuring 4 × 6 cm; cutting is optional.

1. Mark a usable sheet area of 20 × 24 cm. Arrange 4 × 6 cm rectangles without overlap and record the number that fit.
2. Try a second layout, allowing rotation. Leave a stated gap between parts if your imagined process needs one, and keep that rule constant.
3. Calculate total usable part area divided by sheet area. Shade the leftover regions.
4. Compare layouts and explain whether the scraps could make another useful part.

Evidence to keep: Two labeled layouts, part counts and utilization calculations with the gap assumption stated.

Check understanding: Why might the layout with the smallest leftover area be difficult to cut in practice?

Extend: Add a direction arrow to the sheet to represent material grain, prohibit rotation and compare the result.

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Learning goal: Choose a design using explicit criteria and comparable tests.

Materials per team: Paper, card, tape, rulers, a timer and three equal-size books for a tabletop bookend model; keep loads low and stable.

1. Set a brief for a bookend model with a fixed material allowance. Choose three criteria: stability, footprint and assembly time.
2. Build two different concepts. Test both with the same books on the same level surface; stop any unstable test before objects fall.
3. Score each criterion on a written 1–3 scale with observable anchors. Explain which criterion matters most for your user.
4. Choose a concept, revise one feature and repeat its tests. Record whether the revision addressed the evidence.

Evidence to keep: A decision table, test notes and a justified design choice.

Check understanding: Would a different user’s priorities change the decision? Explain using the same data.

Extend: Have another team apply your scoring rules and discuss disagreements.

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Learning goal: Select materials by testing properties relevant to a stated use.

Materials per team: Equal-size samples of paper, card and foil, a ruler, a small book and a recording sheet; smooth any sharp foil edges.

1. Describe the tray’s job and choose relevant properties, such as stiffness and ability to hold a fold.
2. Support each equal-size sample across the same 5 cm gap. Apply the same light load and observe bending without exceeding the material’s limits.
3. Make the same fold in a fresh sample of each material and compare how well it holds its shape.
4. Choose a material and name one drawback. Distinguish what your tests show from properties you did not test.

Evidence to keep: A property table and a recommendation supported by two observations.

Check understanding: Why is there no single ‘best material’ for every product?

Extend: Combine two materials in a tray model and identify what each layer contributes.

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Learning goal: Investigate how cross-sectional shape changes bending behavior.

Materials per team: Equal sheets of paper, two supports of equal height, a ruler and identical small counters. Keep the bridge close to the table.

1. Bridge a fixed 10 cm gap with a flat sheet. Add counters one at a time at the center and record the count before the sheet touches the table.
2. Fold a fresh equal sheet into an accordion shape. Repeat with the same span, counter placement and stop rule.
3. Test a third folded shape and repeat trials using fresh sheets where possible.
4. Compare counts and discuss variation. Keep paper quantity constant so shape is the main planned change.

Evidence to keep: Labeled cross-section sketches, trial counts and an explanation linking form to stiffness.

Check understanding: Why would changing both paper thickness and fold shape make the comparison harder to interpret?

Extend: Change only the span and predict how the result will change before testing.

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Learning goal: Compare a layered panel with a flat stack using the same amount of paper.

Materials per team: Paper, tape, two supports, rulers and identical light counters. Use low tabletop loads.

1. Make a flat three-sheet panel with a fixed amount of tape. Measure its span between two supports and choose a consistent loading point.
2. Use three fresh equal sheets to make a sandwich: two outer faces and one folded paper core. Use the same tape allowance.
3. Load each panel gradually and record the count at the same visible-deflection stop rule. Repeat or exchange panels with another group.
4. Discuss how spacing the outer layers changes the panel and note differences in construction quality.

Evidence to keep: Panel sketches, material quantities and comparable load observations.

Check understanding: Does a stronger classroom panel prove it is suitable for a real building or vehicle? What evidence is missing?

Extend: Change only the core’s fold spacing and compare stiffness and ease of construction.

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Learning goal: Compare joint performance against strength and disassembly requirements.

Materials per team: Equal card strips, removable tape, paper clips, pre-cut tab-and-slot samples and identical light counters in a paper cup. No sharp fasteners.

1. Join equal card strips using three methods, keeping overlap length constant. Define a light-load test and a stop rule with the teacher.
2. Apply the same gentle load to each joint over a clear tabletop and record movement or separation.
3. Open each joint carefully. Count damaged parts and note whether it can be assembled again.
4. Recommend a joint for a reusable package, explaining the trade-off between holding and reopening.

Evidence to keep: A joint comparison table with loading and disassembly results.

Check understanding: Why might the strongest permanent joint be unsuitable for a repairable product?

Extend: Repeat a joint’s open-close cycle five times and track any change.

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Learning goal: Relate part geometry to removal from a simple mold.

Materials per team: Reusable modeling clay suitable for the class, blunt plastic shapes, paper and pencils. Check material sensitivities and use no heat or chemical casting.

1. Press a simple tapered object gently into clay and remove it. Sketch the cavity and the direction of removal.
2. Compare it with a straight-sided object. Observe where clay grips, stretches or tears; keep pressing depth similar.
3. Draw a shape with a feature that would catch behind the mold opening. Propose a two-part mold with a clear parting line.
4. Use a clay model or drawing to explain the sequence for opening the two halves and releasing the part.

Evidence to keep: Two observations and an annotated two-part mold concept.

Check understanding: How can a part be easy to draw but difficult to remove from a one-piece mold?

Extend: Identify where a visible seam on a safe household plastic object might suggest a mold parting line.

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Learning goal: Connect waiting work to differences in station capacity.

Materials per team: Paper tokens, three labeled station mats, a timer and a tally sheet.

1. Use 10-second rounds. Station A may move three tokens, B two and C three; tokens move only one station per round and must already be waiting when a round starts.
2. Run six rounds, supplying A with enough tokens. Record each queue and the total completed at C after every round.
3. Repeat from an empty line with B allowed three tokens per round. Keep all other rules unchanged.
4. Graph the queue before B and compare completed output. Identify the effect of startup time.

Evidence to keep: Two round-by-round tables and a queue graph.

Check understanding: Why does keeping A busy create a larger queue without necessarily increasing finished output?

Extend: Limit the queue before B to four tokens and describe what A must do when that space is full.

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Learning goal: Redistribute tasks to reduce the longest station time.

Materials per team: Task cards labeled with simulated times of 10, 15, 20, 25, 15 and 5 seconds, three station mats and paper.

1. Place the six tasks in their written order. Allocate consecutive tasks among three stations and add each station’s times.
2. Calculate the starting line capacity using 3,600 divided by the longest station time, rounding down.
3. Try at least three new allocations while preserving task order and keeping every task intact. Seek the smallest possible longest station time.
4. Explain the best allocation you found and identify practical reasons a real task might not move between stations.

Evidence to keep: Three station-allocation diagrams with totals and calculated capacities.

Check understanding: Why is equal task count different from equal work time?

Extend: Add a rule that tasks three and four require the same machine and must stay together; solve again.

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Learning goal: Distinguish time to first completion from total batch completion time.

Materials per team: Ten paper cards, pencils, stamps or stickers, a timer and two station mats.

1. Define two short tasks for each card, such as drawing a border and adding three dots. Set a shared quality rule.
2. Run a batch-of-five process: station one finishes five cards before passing them together. Record first acceptable completion and completion of all ten.
3. Start again with fresh cards and move each card immediately after its first task. Keep people, tasks and quality rules the same.
4. Compare both timing measures and counts of acceptable cards; discuss practice effects and repeat if time permits.

Evidence to keep: A table of first-item time, total time and quality counts for both methods.

Check understanding: Could a method improve first delivery without improving every other measure?

Extend: Introduce a short setup activity between product types and discuss when batches may help.

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Learning goal: Separate preparation tasks from tasks that require a station to stop.

Materials per team: Two sets of colored pencils, card templates, paper, a timer and a checklist.

1. Create a station that switches from marking blue squares to red circles. List the retrieval, clearing, positioning and checking tasks needed for the switch.
2. Perform one changeover and time the interval from the last acceptable blue square to the first acceptable red circle.
3. Move appropriate preparation earlier, such as arranging the next template and pencil nearby. Keep the first-piece quality check.
4. Repeat and compare stopped time, total preparation work and first-piece quality.

Evidence to keep: A before-and-after task sequence with timing and quality results.

Check understanding: Which tasks became earlier, and which tasks actually disappeared?

Extend: Create a labeled setup tray another team can use without verbal coaching.

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Learning goal: Compare a work-in-progress limit with unrestricted starts.

Materials per team: Twenty paper tokens, three station mats, six release cards and a tally sheet.

1. Use eight rounds with station capacities of three, two and three tokens. A token can advance only one station each round; station B pauses during round four.
2. First run without a release limit and count starts, finished tokens and unfinished tokens after each round.
3. Reset. Attach one release card to each new token; a card returns to the start only when its token finishes. Keep capacities and the pause identical.
4. Compare unfinished inventory and completed output. Discuss why a limit that is too small could starve the line.

Evidence to keep: Two round-by-round records and an explanation of what the release cards control.

Check understanding: Does a smaller queue automatically mean every customer receives an item sooner? What timing data would you need?

Extend: Repeat with three release cards and compare the trade-off.

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Learning goal: Improve consistency by defining how a dimension is measured.

Materials per team: Five card strips of varied lengths, millimeter rulers, pencils and a table with space for repeated readings.

1. Have two learners independently measure each strip without comparing answers. Record every reading with units.
2. Compare differences. Agree on the reference edge, ruler zero point, viewing position and rounding rule.
3. Measure the same strips again in a mixed order. Compare the spread between inspectors before and after the shared method.
4. Identify remaining uncertainty, including unclear edges or ruler resolution. Do not change earlier readings to make them agree.

Evidence to keep: Two sets of measurements and a short written inspection method.

Check understanding: Why can two careful people disagree when the measurement method is vague?

Extend: Repeat with a ruler marked only in centimeters and explain which claims become less precise.

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Learning goal: Use upper and lower limits to make a repeatable acceptance decision.

Materials per team: Rulers, paper strips of varied lengths and a card sheet for drawing a gauge. Teacher-prepared samples can replace cutting.

1. Specify a strip length of 100 mm with ±2 mm allowed. Mark 98 mm and 102 mm from one reference edge on the gauge.
2. Align each strip to that reference and classify it as too short, within limits or too long.
3. Check classifications with a ruler. Examine samples close to each limit and discuss how line thickness affects the decision.
4. Exchange gauges with another team and compare decisions on the same strips.

Evidence to keep: The gauge, its stated limits and an inspection table including borderline cases.

Check understanding: What can go wrong if the gauge’s own markings are inaccurate?

Extend: Design a second limit check for width and explain why passing length alone is insufficient.

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Learning goal: Summarize defect categories and justify a first investigation.

Materials per team: Thirty fictional defect cards: 12 missing labels, eight bent corners, six wrong counts and four unclear marks; graph paper or a spreadsheet.

1. Check that the categories are defined consistently, then tally the cards without counting any card twice.
2. Draw a bar chart ordered from most frequent to least frequent. Calculate each category’s share of the thirty defects.
3. Choose a first investigation and propose a possible process cause. Keep the proposed cause separate from the observed count.
4. Now label one unclear mark as a potentially serious identification error. Discuss how severity can change the priority.

Evidence to keep: An ordered chart and two priority decisions with reasons.

Check understanding: Why does the most frequent defect not always deserve the first corrective action?

Extend: Create a second fictional week of data and compare whether the pattern persists.

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Learning goal: Recognize sampling variation and limits on conclusions from small samples.

Materials per team: Forty folded paper cards, eight secretly marked with a defect symbol, a bag and a tally sheet. Cards should feel identical.

1. Mix the cards. Draw five without looking, inspect them, record the defect count, then return all five and remix.
2. Repeat ten times, keeping the sample size and return rule constant. Graph the defect counts from each sample.
3. Reveal the full batch composition and compare sample estimates with the actual 20% defect share.
4. Repeat with samples of ten if time permits. Explain why finding zero defects does not prove the batch has none.

Evidence to keep: The sample results, graph and a statement about uncertainty.

Check understanding: How would taking only cards from the top of an unmixed pile bias the inspection?

Extend: Discuss why a classroom sampling activity cannot establish a real product’s safety or acceptance plan.

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Learning goal: Use time order to spot a possible process shift without overclaiming its cause.

Materials per team: Graph paper or a spreadsheet and this fictional sequence in millimeters: 20, 19, 20, 21, 20, 19, 20, 20, 22, 23, 22, 23.

1. Plot measurement against item number and draw the 20 mm target. Keep the sequence in its original order.
2. Calculate the overall average and compare what it communicates with what the chart shows.
3. Identify where the readings appear to shift. Propose questions about tools, setup or measurement that could investigate the change.
4. Explain what additional repeated measurements and context would be needed before deciding on a cause or adjustment.

Evidence to keep: A labeled run chart, average and investigation questions.

Check understanding: Why could sorting the values from smallest to largest hide useful process information?

Extend: Add the stated specification band of 20 ±2 mm and distinguish meeting a requirement from showing a stable pattern. This is not a formal control-chart analysis.

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Learning goal: Write and debug an unambiguous sequence of commands.

Materials per team: A tabletop grid, paper arrow cards, a token robot and two marked destination squares. No moving machinery.

1. Agree on four commands: move one square, turn left, turn right and pick up. Define the robot’s starting square and direction.
2. Write a sequence that visits a component square and reaches an assembly square. Predict the ending position before testing.
3. Have a partner execute exactly the written commands with the token, without guessing what was intended.
4. Mark the first mismatch, change the relevant instruction and rerun from the same start.

Evidence to keep: The original and revised command lists with one explained bug.

Check understanding: Why does ‘go over there’ fail as a reproducible instruction?

Extend: Add an obstacle square and compare two valid routes by command count.

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Learning goal: Build and test a decision tree including an uncertain case.

Materials per team: Paper shape cards in two sizes and colors, including two with deliberately unclear markings; paper and pencils.

1. Write a fictional sorting requirement: large blue cards go to bin A, other clearly identified cards go to bin B, unclear cards go to review.
2. Draw a decision tree with yes/no questions and an explicit review path.
3. Test every card and record the chosen bin. Include a missing-color and borderline-size case.
4. Exchange trees with another team, compare classifications and revise ambiguous rules.

Evidence to keep: A tested decision tree and a table showing ordinary and uncertain cases.

Check understanding: Why is a review route useful when a sensor or label cannot support a confident decision?

Extend: Count the number of questions asked per card and propose a more efficient ordering that preserves the same outcomes.

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Learning goal: Compare missed defects and false alarms using a simple threshold model.

Materials per team: Ten fictional sensor readings with known labels: acceptable 42, 46, 49, 53, 57; defective 51, 55, 60, 64, 70. Paper or spreadsheet.

1. Classify a reading of 55 or more as a defect alert. Count correctly flagged defects, missed defects and acceptable items incorrectly flagged.
2. Repeat at thresholds of 50 and 60. Keep the same readings and known labels.
3. Compare the trade-offs and choose a threshold for a stated fictional priority, such as minimizing missed defects.
4. Explain why this tiny invented dataset cannot validate a real inspection system.

Evidence to keep: Three classification tables and a reasoned threshold choice.

Check understanding: Why can reducing missed defects increase unnecessary alerts?

Extend: Add a review band around the threshold and count how many items need a person’s decision.

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Learning goal: Compare a gripping concept across objects and repeat trials.

Materials per team: Folded-card tongs, blunt kitchen tongs if available, large paper balls, card blocks and a shallow tray. Use hand-operated models only.

1. Define a successful transfer: lift an object 5 cm, move it across the tray and release it without damage.
2. Test two gripper designs on the same three objects, three transfers per object. Record successes and observed slipping.
3. Change one feature, such as contact-pad width, and repeat the same trials.
4. Recommend a design for one object type and explain where its versatility is limited.

Evidence to keep: A transfer-success table, sketches and one supported improvement.

Check understanding: How might making the grip stronger create another problem for a delicate component?

Extend: Add a positioning target and compare successful gripping with accurate placement.

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Learning goal: Model explicit operating states and a reviewed restart sequence.

Materials per team: Paper cards labeled Ready, Running, Paused, Review and Reset; event cards and a token. No real equipment or safety-control wiring.

1. Draw allowed transitions between Ready, Running and Paused in a fictional paper sorting station.
2. Add a missing-part event that moves the station to Review. Specify what information an operator must check before a reset.
3. Have one learner draw event cards while another moves the state token only along allowed arrows.
4. Try an event in the wrong state and decide whether to ignore it, record it or request review. Revise the diagram.

Evidence to keep: A state diagram and a log of at least eight event-response pairs.

Check understanding: Why should clearing a message not automatically restart an unexpected process?

Extend: Add a power-loss event to the paper model. Explain why a real machine requires qualified safety engineering beyond this activity.

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Learning goal: Create a parts list and calculate requirements for a batch.

Materials per team: A sample paper activity kit with one instruction card, two card shapes and three paper tokens; a table and pencils.

1. Inspect the sample kit and list each distinct part, its description and quantity per kit.
2. Calculate requirements for ten kits. Keep parts and units in separate columns so counts are easy to check.
3. Receive a fictional inventory of 12 instruction cards, 18 shapes and 35 tokens. Determine the maximum complete kits and the limiting part.
4. Write a shortage list for the ten-kit order and have a partner verify the arithmetic.

Evidence to keep: A bill of materials, batch calculation and shortage list.

Check understanding: Why do 65 total parts not necessarily make ten complete kits?

Extend: Add a second kit version that uses a different shape and explain how part identifiers prevent confusion.

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Learning goal: Evaluate a supplier choice using stated constraints and multiple criteria.

Materials per team: Three fictional offers for 100 paper parts: A costs 40 units, arrives in eight days and has 18 of 20 sample parts pass; B costs 50, arrives in four days and has 20 of 20 pass; C costs 45, arrives in six days and has 19 of 20 pass.

1. Set the order deadline at five days and require at least 19 of 20 sample parts to pass. Treat these as classroom decision rules; the small samples do not establish long-term quality.
2. Identify offers that meet both constraints. Separate an unacceptable offer from a merely less-preferred one.
3. Compare feasible offers on price, delivery confidence and quality evidence; state any missing information.
4. Move the deadline to nine days and explain whether the recommendation changes.

Evidence to keep: A constraint table and two purchasing recommendations.

Check understanding: Why is the lowest quoted price not always the lowest-risk choice for this order?

Extend: Add a fictional transport charge and compare total cost using consistent units.

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Learning goal: Use component-to-product records to identify a defined set of affected units.

Materials per team: Twelve paper product cards with unique IDs, three component-lot labels A/B/C and a log sheet.

1. Assign a component lot to each product and record the relationship. Have a second learner check for missing or duplicate IDs.
2. Receive a fictional notice that lot B needs review. Identify exactly which product IDs use it.
3. Exchange records with another team and ask them to repeat the lookup without verbal help.
4. Remove one record temporarily and discuss how the uncertainty changes the review scope; restore the record afterward.

Evidence to keep: A traceability log and a correctly identified review list.

Check understanding: Why do a product name and a unique product or batch identifier serve different purposes?

Extend: Give each product two components from separate lots and trace either component through the log.

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Learning goal: Design labels that support accurate identification and counting.

Materials per team: Three paper envelopes, fictional part cards, pencils and contrasting markers. Do not use real customer information.

1. Create three similar part types and assign each a plain-language name, part ID and quantity. Put them in separate envelopes.
2. Design labels with the same information order and readable contrast; do not rely on color alone.
3. Ask another team to retrieve a named part and verify the count using only the labels.
4. Record mistakes and questions, revise the labels and repeat with a new reader.

Evidence to keep: Two label versions and a retrieval-accuracy record.

Check understanding: Which label feature helps distinguish two similar parts for someone who cannot tell the colors apart?

Extend: Add a revision letter and explain how to prevent mixing old and new versions.

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Learning goal: Relate a simple reorder point to expected use during delivery time.

Materials per team: Paper tokens or a spreadsheet, an inventory table and fictional data: use 12 parts per day, delivery takes three days, buffer is 12 parts.

1. Calculate expected use during delivery: 12 × 3 = 36 parts. Add the 12-part buffer to propose a 48-part reorder point.
2. Start with 72 parts and simulate daily use. Place an order for 60 parts when the threshold is reached; define exactly when deliveries arrive.
3. Repeat with one 20-part demand day and then with a one-day delivery delay. Keep a day-by-day record.
4. Discuss what the simple rule handles and where it fails. Treat the buffer as a chosen assumption, not a universal recommendation.

Evidence to keep: Three inventory timelines and a revised rule with assumptions.

Check understanding: Why does a longer delivery time usually require an earlier order if demand is unchanged?

Extend: Compare the cost of a larger buffer with the consequences of running out, using invented costs.

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Learning goal: Account for usable output, reusable offcuts and discarded material.

Materials per team: One sheet of squared paper per team, rulers, pencils and teacher-prepared shape templates; cutting is optional.

1. Count the starting sheet’s grid squares. Draw a layout for a chosen set of rectangular parts.
2. Classify every square as part area, reusable offcut or other remainder. Check that the totals equal the starting area.
3. Redraw the layout to reduce the remainder while making the same acceptable parts.
4. Compare material use and explain what cutting losses or damaged pieces the paper model leaves out.

Evidence to keep: Two fully accounted layouts and an area balance for each.

Check understanding: Why is an uncounted leftover different from a demonstrated reduction in waste?

Extend: Invent a useful second part that fits an offcut and report how much material remains unused.

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Learning goal: Calculate energy use from power and time using fictional production data.

Materials per team: A calculator or spreadsheet and two scenarios: A uses 0.6 kW for two hours and produces 90 acceptable parts; B uses 0.8 kW for 1.5 hours and produces 100 acceptable parts.

1. Calculate each scenario’s energy in kWh by multiplying power by hours. Both use 1.2 kWh under these assumptions.
2. Divide energy by acceptable output and compare kWh per acceptable part.
3. Add a 0.2 kW idle period lasting half an hour to B. Recalculate its total and per-part result.
4. List what the scenarios omit, such as startup, rejected parts and how power varies during a cycle.

Evidence to keep: A calculation table with units, assumptions and a qualified comparison.

Check understanding: Why does a higher power rating alone not establish higher energy use per acceptable item?

Extend: Change one assumption and find when the preferred scenario reverses. Do not measure mains electricity or modify appliances.

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Learning goal: Distinguish fresh input, reused flow and discharge in a fictional process.

Materials per team: Paper arrows, counters representing liters and a diagram of a fictional nonfood washing process. This is a dry simulation; use no wastewater or chemicals.

1. Model a process using 10 fresh-water counters per batch, with all ten leaving after use. Account for every counter.
2. Propose returning four counters to an earlier stage. Draw fresh input, reuse and discharge as separate flows.
3. Calculate fresh input for five batches, stating whether the loop starts full or needs an initial fill.
4. List unanswered questions about contamination, treatment, product requirements and worker protection before any real reuse could be considered.

Evidence to keep: Two flow diagrams and a fresh-input calculation with startup assumptions.

Check understanding: Why does moving water around a loop not automatically make it suitable for reuse?

Extend: Add a treatment loss of one counter per cycle and revise the balance.

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Learning goal: Evaluate how joining and access choices affect repair.

Materials per team: Card, removable tape, paper clips, rulers and a simple model stand with one replaceable foot. Use blunt, classroom-safe parts.

1. Build a stand that remains upright for one minute. Identify its separate parts and joins.
2. Mark one foot as failed in a fictional scenario. Time a careful replacement and count other parts damaged during access.
3. Redesign the connection for easier replacement while keeping the stability requirement.
4. Repeat the same repair task and stability check. Record additional parts or material needed for the redesign.

Evidence to keep: Two assembly sketches and repair-time, damage and stability comparisons.

Check understanding: What trade-off might a removable connection introduce during normal use?

Extend: Write a repair instruction sheet and ask another team to follow it without help.

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Learning goal: Set a fair comparison boundary and identify missing environmental data.

Materials per team: Two empty, clean package types for the same purpose, paper and pencils. No environmental-impact database is required.

1. Define the shared service, such as protecting and delivering one identical classroom model. State whether reuse is included.
2. Map material sourcing, manufacture, transport, use and end-of-life for both options. Mark known facts and assumptions separately.
3. List data needed for a quantitative comparison, including mass, damage rate, travel distance and number of actual reuses.
4. Explain how leaving out one stage could change the conclusion. Make a research plan instead of declaring an unsupported winner.

Evidence to keep: Two boundary diagrams and a prioritized list of missing data.

Check understanding: Why is ‘recyclable’ alone insufficient to establish lower overall environmental impact?

Extend: Use clearly labeled invented data to explore a reuse break-even calculation, without presenting it as a real assessment.

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Learning goal: Produce a clear sequence with a visible quality check.

Materials per team: Paper, pencils, rulers and a simple paper-folding task. Offer written, pictorial or spoken instruction formats.

1. Choose a three- or four-step paper product and define its acceptance rule before drafting instructions.
2. Write or illustrate each step, name the starting materials and show what the finished item should look like.
3. Give the instructions to another team. Observe questions and errors without coaching during the first attempt.
4. Revise the unclear steps and repeat with a new reader. Check the product using the same acceptance rule.

Evidence to keep: Two instruction versions, learner questions and acceptable-output counts.

Check understanding: How do you know the instructions improved rather than the original reader simply remembering the task?

Extend: Add a version number and date so teams can identify the current instruction.

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Learning goal: Identify task barriers and test accessible alternatives without simulating a disability.

Materials per team: Paper part cards, two trays, pencils, a tabletop layout sheet and optional large-print labels. Invite voluntary preferences; do not ask for diagnoses.

1. Map a seated sorting task and ask participants which reach distances, label sizes or instruction formats help them work comfortably.
2. Create two layouts within the same tabletop area. Keep parts and the sorting rule identical.
3. Let participants choose comfortable methods and compare accuracy, questions and self-reported ease. Speed is optional and should not drive uncomfortable movement.
4. Revise the layout using feedback and describe who was consulted and what remains uncertain.

Evidence to keep: Before-and-after layouts and anonymous task feedback.

Check understanding: Why is one person’s preferred setup not proof that it will work for everyone?

Extend: Add a non-color cue to every bin and test whether the instructions remain understandable.

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Learning goal: Communicate current status, unresolved issues and the next action clearly.

Materials per team: A fictional order for 20 paper kits, a handoff sheet and status cards: 12 complete, three awaiting inspection, five not started and one component shortage.

1. Write a handoff covering completed quantity, work in progress, the shortage, current instruction version and the next check.
2. Give the sheet to a second team without explaining it aloud. Ask them to identify what they can safely plan next.
3. Compare their interpretation with the intended state. Look for double-counted quantities and unclear ownership of the shortage.
4. Revise the sheet with an explicit next action and responsible role, then repeat the handoff.

Evidence to keep: A reconciled quantity record and a revised handoff sheet.

Check understanding: Why should ‘three awaiting inspection’ be kept separate from ‘three complete’?

Extend: Add a changed customer requirement and specify how the next team confirms which version applies.

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Learning goal: Connect roles to tasks, evidence and possible learning pathways.

Materials per team: Paper, markers and the career-resource links on this page; printed public profiles can replace internet access.

1. Choose a familiar manufactured object and map design, sourcing, production, quality, maintenance and delivery tasks.
2. Use current occupational or training profiles to identify four roles connected to those tasks. Record the source and access date.
3. For each role, note one problem it solves, one tool or skill and a learning route described by the source; requirements vary by employer and location.
4. Draw where the roles exchange information and write two questions to ask a visiting professional.

Evidence to keep: A sourced career-team map with task and training notes.

Check understanding: How does a task description reveal more than a job title alone?

Extend: Compare two routes into a related role without assuming either route guarantees a job.

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Learning goal: Track the effect of a revised requirement across connected documents.

Materials per team: A fictional paper kit specification, drawing, parts list, instruction sheet and inspection checklist, all marked version A.

1. Receive a request to change a card from 80 mm to 90 mm long while preserving its width. Identify every document and activity affected.
2. Revise the drawing and acceptance check, recalculate material needs and inspect whether packaging still fits.
3. Mark the revised set version B and record who checked each change. Separate old examples from the current set.
4. Give mixed A and B papers to another team and ask them to find the inconsistency before starting work.

Evidence to keep: A change-impact list and a consistent revised document set.

Check understanding: Why can updating only the drawing leave a team making or accepting the wrong part?

Extend: Plan how to handle already-made version A parts using a fictional customer decision; do not assume they should be discarded.

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Learning goal: Create a feasible plan that checks both time and material constraints.

Materials per team: A fictional order for 120 kits, a 60-minute period, six minutes of setup, 30 seconds per kit after setup, and materials for 100 kits; calculator and paper.

1. Calculate available production time: 54 minutes. Convert the 30-second cycle into a maximum of 108 completed kits before quality losses.
2. Compare time capacity with the 100-kit material limit and identify the current constraint.
3. Assume 95% first-pass yield and calculate expected acceptable output under the simplified model. State that real outcomes vary.
4. Propose two feasible responses, such as changing the promised quantity or arranging additional time and materials. Recalculate each proposal.

Evidence to keep: A constraint table and a plan with explicit assumptions and a delivery quantity.

Check understanding: Why does adding material alone not make the original 120-kit order feasible in this time window?

Extend: Add a ten-minute planned pause and update the plan without hiding the shortfall.

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Learning goal: Compare fixed and variable costs while recognizing model limits.

Materials per team: Calculator or spreadsheet; fictional making cost of 120 cost units setup plus two per item, and buying cost of five per item with no setup charge.

1. Write total-cost expressions for making and buying. Calculate each at quantities of 10, 40 and 100.
2. Find where 120 + 2q = 5q; both equal 200 cost units at 40 items.
3. Graph both expressions and explain which is cheaper below and above that quantity under the stated assumptions.
4. Add a fictional quality, delivery or capacity constraint and discuss whether the cheapest option is feasible.

Evidence to keep: A cost table, graph and qualified make-or-buy recommendation.

Check understanding: Which costs or risks are absent from this small model?

Extend: Add a 30-unit delivery charge to the buying option and find the new break-even quantity.

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Learning goal: Turn a suspected cause into a controlled, observable comparison.

Materials per team: Paper cards, rulers, pencils, an alignment guide and a log. Use the fictional problem ‘marks frequently fall outside the target box.’

1. Define the problem with a measurable requirement and a count, avoiding blame or an assumed cause.
2. List possible causes involving instructions, materials, positioning and measurement. Choose one that can be tested safely.
3. Make ten cards under the current method and ten with only the chosen condition changed. Keep the same target and record every result.
4. Compare acceptable counts and describe whether the evidence supports further investigation. Consider practice effects and the small sample.

Evidence to keep: A problem statement, hypothesis, test record and cautious conclusion.

Check understanding: Why does asking ‘why’ several times not by itself demonstrate a cause?

Extend: Repeat in reversed order with another team to examine whether the apparent improvement persists.

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Learning goal: Interpret several process measures before choosing an improvement.

Materials per team: Fictional daily data: Monday 100 made/90 acceptable/10 waiting; Tuesday 120/96/30; Wednesday 110/104/12. Paper or spreadsheet.

1. Calculate first-pass yield for each day as acceptable divided by made, and keep acceptable count as a separate measure.
2. Create a dashboard with made, acceptable, yield and waiting work. Use consistent labels and scales.
3. Write one question raised by each day’s results. Explain why the data do not reveal the cause of the changes.
4. Choose a next investigation and state which measures would indicate progress without hiding a decline elsewhere.

Evidence to keep: A four-measure dashboard and a proposed follow-up supported by the data.

Check understanding: Why would rewarding only the highest ‘made’ count favor a different day from rewarding the highest acceptable output?

Extend: Add operating hours and compare acceptable units per hour rather than raw daily totals.

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Learning goal: Combine requirements, process design, measurement and improvement in one documented project.

Materials per team: Paper, card, pencils, rulers, classroom-safe fasteners, a timer and recording sheets. Choose a low-risk product such as a paper bookmark or activity kit.

1. Session one: agree on the customer need, written specifications, material allowance and quantity. Build a sample, define inspection and assign rotating roles.
2. Draw the process and run a small pilot. Record starts, acceptable finishes, rejects and waiting work without pressuring anyone to work uncomfortably fast.
3. Session two: identify one constraint, make one documented process change and repeat an equal-length run using the same quality rules.
4. Present the before-and-after evidence, account for materials and explain one limitation. Invite questions from another team acting as the customer.

Evidence to keep: A brief, parts list, process map, inspection record, material account and improvement presentation.

Check understanding: Which evidence demonstrates a better process, and which claim still needs another trial?

Extend: Add a customer change request or a fictional supplier delay and revise the plan while preserving traceable records.

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