PYTHON · NUMPY

Assembly sequencing

Step 4 places the left finger, but the servo horn it fits onto has not been placed. What kind of constraint is this?

Produce a feasible assembly order for a multi-part product and explain at least one constraint (access, fastening, fit) that forbids an alternative order.

01Challenge

Sequence a 6-part robot gripper (base_plate, servo, servo_horn, finger_left, finger_right, cover) into slots 1..6 and Run Assembly. Fill all six with an order that runs to completion: no blocked-access, no-fit, no-fastening failure. Put the cover before the screws it hides, or a finger before the horn its slot engages, and the twin throws a concrete physical failure. That failure is the lesson.

Predict firstStep 4 places the left finger, but the servo horn it fits onto has not been placed. What kind of constraint is this?

02Model

You can't bolt through a lid you already closed: obvious, and it's the whole idea behind assembly sequencing. Six parts is six factorial, 720 orders, and most are impossible. Every forbidden order traces to one of three things: ACCESS (a later part blocks the tool that fastens an earlier one), FIT (a part mates with a feature that must already be there), or FASTENING (the fastener needs both parts present and reachable). Each is an arrow: this before that.

Collect every arrow and you get a precedence graph; a feasible order is any path that never points backward, a topological sort. There's always at least one, unless you've drawn a cycle, which means you've designed something that can't be built.

A feasible order to assemble the parts.

03Guided practice

Step A (worked): with three given constraints, construct base_plate → servo → servo_horn → finger_left → finger_right → cover and it passes.
Step B (completion): full constraint list, empty tray; use Lint-my-order to find the first backward arrow before running physics.
Step C (independent): the cover becomes bolted through the finger tabs (a hidden new constraint: fingers before cover); discover it by running and reading the failure, then re-sequence and name the constraint's reason-class.

04Feedback

PASS WHEN is_feasible(order) True for the perturbed precedence set, all three failure counters 0 on Run Assembly, and the named constraint is a true edge with a correct reason-class (ACCESS/FASTEN), on seed 4001.

If your run fails, check:

Step 4 places finger_left, but servo_horn (its FIT parent) isn't placed yet. Move servo_horn earlier.
cover at step 3 blocks tool access to the M2 screws (still un-fastened); the screws need servo+base_plate seated first; place the cover last.
servo has no body to drop into: base_plate must be placed before servo (ACCESS).
Order is feasible, but the new cover constraint isn't FIT: nothing mates into a feature; the bolts pass THROUGH the finger tabs (ACCESS/FASTEN). Re-classify.

05Retrieve & space

From M3.3: shaft Ø4.00±0.02 vs horn bore Ø3.97±0.02. Is the worst-case fit guaranteed interference? Compute the worst-case clearance.
From M2.3: what is the analogue of a 'datum surface' in an assembly precedence graph? → a part with no incoming arrows / the base part.
From M1.1: name one DFM change to the cover that removes the finger→cover arrow (decouples it). → snap-fit, or bolts into base_plate not through tabs.

06Mastery & project

In sim, submit a feasible order for the perturbed 6-part gripper (is_feasible True, all failure counters 0) AND state one true constraint with a correct reason-class (ACCESS/FIT/FASTEN). Unlocks 4.2.

Feeds the capstone by making each product an ordered set of assembly operations with known cycle costs: the per-station work content that 4.2/4.3 distribute across a line and M5 turns into yield and cost.

GO FURTHER · THE LIVE PLAYGROUND

Sequence an assembly in the live bench ↗ · drag the build order and watch feasibility.

← Tolerance stack-up Throughput & the Bottleneck →

PYTHON · NUMPY

Assembly sequencing

The precedence feasibility checker from the Bench spec: a part is placeable iff all its precedence-parents are placed. Edit your order and run.

You read

the arrays and values already in scope

You change

the code you write in each cell

Fixed

the dataset and the checks that grade you