4. Case Study B — Structural Steelwork Supply, Fabrication & Erection
The figures, rates, and project parameters used below are illustrative — constructed to demonstrate how the calculation engine behaves, not drawn from a specific tender or client project. The mechanics and the resulting cost curves are representative of real project behaviour; the specific dollar figures are not sourced data.
Case Study A showed the engine operating at strategic, project-planning scale. This case study shows the identical computational mechanism — formulas, scoped variables, and dependency-graph recalculation — operating inside a single bill item, proving the model holds at both ends of the estimate.
4.1 The Parent Item
At the top of the Bill of Quantities, the client schedule needs one consolidated figure:
Item Code | Description | Quantity | Unit | Direct Rate | Extended Total |
|---|---|---|---|---|---|
| STR-04 | Supply, Fabricate & Erect Structural Steelwork (Levels 1–20) | 850 | tonne | Dynamic | Dynamic |
That direct rate isn’t a typed-in number. It’s the evaluated output of the resource assembly and formula tree below it — the real-time quotient of total underlying resource cost divided by total unit output — recalculated by the dependency engine whenever anything beneath it changes.
4.2 Resource Assembly Beneath the Line Item
Structural Steel Erection Assembly | ├──Labour Crew (Loaded Hourly Rate: $310.00/hr) │ ├──Erection Foreman (1.0 FTE) │ ├──Riggers (2.0 FTE) │ ├──Steel Erectors / Connectors (4.0 FTE) │ └──Bolt-Up Crew (2.0 FTE) | ├──Heavy Plant Fleet (Operational Cost: $780.00/hr) │ ├──Tower Crane (1.0 unit, shared allocation) │ ├──Mobile Crane, 50T (1.0 unit) │ ├──Elevating Work Platforms (2.0 units) │ └──Welding & Bolting Sets | └──Material & Logistics │ ├──Structural Steel, Fabricated & Delivered ($/tonne) │ └──Temporary Bracing & Site Handling ($/tonne) |
Each branch of this tree is itself a resource node with its own formula: the Labour Crew node sums FTE × loaded rate across four sub-resources; the Heavy Plant Fleet node sums unit count × operating rate across four more. When a labour agreement, crane hire rate, or steel mill price changes, updating the single underlying resource — not the tree above it — recalculates the direct rate across every dependent item in the estimate that consumes that resource, not just this one.
4.3 Production Rates: the Formula Beneath the Rate
Crew and crane cost per hour mean nothing without a deterministic yield calculation sitting under them, authored the same way as any other resource formula in Methvin.
Crane lift cycle time:
T_lift = t_hook + D_lift / S_hoist + t_position + t_connect + t_release
where D_lift is average vertical/horizontal hook travel distance, S_hoist is hoist speed, and the t terms are fixed operational delays for hooking, positioning, connecting, and releasing each piece — each one a named variable in the project scope, not a hardcoded constant.
Daily output — a MIN() function over three constrained resources, exactly as described in Section 2.2:
Daily Output (t) = min(Crane Lift Capacity, Connection Crew Capacity, N × Avg. Piece Weight / T_lift) × Shift Hours × η
where η is a site efficiency factor — e.g. 0.80, reflecting crane time shared with formwork and façade trades on a live floor.
Because the line item’s rate is derived from this formula tree rather than typed in, changing one physical input — reducing tower crane availability from a dedicated allocation to a 60% share, for instance — propagates through T_lift, into the MIN() function governing Daily Output, and into the direct rate on the parent item, automatically recalculating required erection crew size, daily production yield, and the final unit rate, in that order, without the estimator touching a single downstream cell.
Case Study A’s formwork trade-off and Case Study B’s crane-lift-cycle formula are both expressions on nodes in the same dependency graph, evaluated by the same engine — one at project-planning scale, one at line-item scale.