#manufacturing

What manufacturers in each economy are actually reporting about their order books, output, prices, exports and hiring — the OECD business tendency surveys as an API, live, no key. Every month national statistics offices ask factory managers whether order books are full or thin, whether they expect to raise or cut production, whether they plan to put prices up, whether export demand is strong, and whether they will hire or fire. The OECD harmonises the answers into balances — the share answering up/good minus the share answering down/bad, on a scale around zero (positive = expansion/optimism, negative = contraction/pessimism). These survey balances are pure soft data that move before the hard numbers, which is why they are watched as one of the earliest reads on the manufacturing cycle — and the selling-price balance, in particular, is a leading signal of pipeline inflation. This API exposes the manufacturing survey components themselves, not just the composite confidence index: order books (current demand), production expectations, selling-price expectations, employment expectations and export order books. The country endpoint returns one economy's full survey panel with the month-on-month change in each balance. The orderbooks endpoint ranks every economy by its order-books balance (who has the fullest order books right now). The sellingprices endpoint ranks by the selling-price balance — the pipeline-inflation gauge, where firms are planning the biggest price rises. Each reading carries its own month and discontinued series are excluded, so the board is genuinely current. The business-survey-components cut — distinct from the composite Business & Consumer Confidence board (which gives only the headline index), the leading-indicator board, and the generic multi-provider data aggregator. Balances are in percentage points; figures are monthly.

api.oanor.com/businesssurvey-api

How much each economy's factories, mines and utilities are actually producing, and which way output is turning — the OECD industrial production index as an API, live from the OECD's official statistics, no key. The industrial production index is one of the headline monthly hard-data prints: it measures the real volume of output across industry (mining, manufacturing and utilities, excluding construction), and its year-on-year change is a direct read on whether the real economy is expanding or contracting — it moves markets and feeds straight into GDP nowcasts. Manufacturing, the largest and most cyclical part, is broken out separately. The OECD publishes a seasonally-adjusted production-volume index for each economy; this API turns it into the number people use — the year-on-year and month-on-month growth of industrial output. The board endpoint ranks every economy by its industrial-production growth (industry excluding construction), with manufacturing alongside, so you can see where factories are humming and where they are stalling. The manufacturing endpoint ranks by manufacturing output growth on its own. The country endpoint gives one economy's industrial and manufacturing growth, year-on-year and month-on-month. Each reading carries its own period and discontinued series are excluded, so the board is genuinely current. The industrial-output / hard-data cut — distinct from the leading-indicator and confidence boards (soft, survey-based, forward-looking), the annual IMF database, and the generic data aggregator. Figures are monthly, in percent.

api.oanor.com/industrialproduction-api

Metal-casting and foundry maths as an API, computed locally and deterministically — the solidification-time, shrinkage and melt-weight numbers a foundryman, patternmaker or casting designer works a job to. The solidification-time endpoint applies Chvorinov's rule, t = B × (V/A)², where V/A is the casting modulus (volume ÷ cooling surface area) and B is the mould constant (~2–4 min/cm² for sand): a chunky part with little surface for its volume freezes slowly, a thin one fast — and because a riser must stay molten longer than the casting it feeds, its modulus has to be larger, which is the number that sizes it. The pattern-shrinkage endpoint makes the pattern oversize for the metal that shrinks as it cools: pattern = casting dimension × (1 + shrinkage/100), the patternmaker's contraction rule — about 1.0–1.6 % for grey iron, ~2 % for steel and aluminium — so a 100 mm steel feature needs a 102 mm pattern. The melt-weight endpoint gives the casting weight = volume × metal density (iron ~7.2, steel ~7.85, aluminium ~2.70 g/cm³) and the metal to actually pour = casting weight ÷ the casting yield, because the sprue, runners and risers are remelted scrap — a 7 kg iron casting at 70 % yield needs about 10 kg in the ladle. Everything is computed locally and deterministically, so it is instant and private. Ideal for foundry and patternmaking tools, casting-design and estimating apps, and metalworking calculators. Pure local computation — no key, no third-party service, instant. 3 compute endpoints. For a part's weight from its dimensions use a metal-weight API; for welded joints a welding API.

api.oanor.com/casting-api

Welding settings and consumables maths as an API, computed locally and deterministically — the amperage, wire and gas numbers a welder or fabricator dials a machine in with. (For joint strength, that is a separate weld-strength calculation.) The amperage endpoint gives a starting current from material thickness using the mild-steel rule of thumb of about one amp per 0.001 inch — so an eighth-inch plate runs around 125 A, give or take ten percent — and suggests an electrode or wire size to match. The deposition endpoint does the MIG arithmetic exactly: deposition rate (lb/hr) = wire feed speed × the wire’s weight per inch × 60 × efficiency, where weight per inch = (π/4 · d²) × 0.284 lb/in³ for steel, so 0.035-inch wire at 300 in/min lays down about 4.9 lb/hr fed, 4.8 deposited at 98 % — and from a target deposit it returns the arc time and the pounds of wire to buy. The gas endpoint sizes shielding gas: gas used (ft³) = flow in CFH × arc time in hours, and a cylinder’s arc-time duration, so 35 CFH empties an 80 ft³ bottle in about 2.3 hours of actual arc time. Everything is computed locally and deterministically, so it is instant and private. Ideal for welding, metal-fabrication, manufacturing and shop-management app developers, job-costing and consumable-planning tools, and welding-education software. Pure local computation — no key, no third-party service, instant. Machine settings, not joint strength. Live, nothing stored. 3 compute endpoints.

api.oanor.com/welding-api

Overall Equipment Effectiveness (OEE) and lean-manufacturing maths as an API, computed locally and deterministically — the factory-floor productivity metric behind TPM and continuous improvement. The oee endpoint takes the planned production time, downtime, the total and good piece counts and the ideal cycle time (seconds per piece, or an ideal rate in pieces per minute) and returns the three factors and their product: Availability = run time / planned time, Performance = ideal time for the parts made / run time, Quality = good / total, and OEE = Availability × Performance × Quality — the textbook example of a 420-minute shift with 47 minutes down, 19,271 parts and 423 rejects lands exactly on 74.79 % (88.81 % × 86.11 % × 97.80 %). It also breaks out the six-big-losses view: availability loss, performance (speed) loss in parts, quality loss and the fully-productive part count. The takt endpoint gives the takt time = available time / customer demand (the drumbeat the line must match), the required rate, and — given a cycle time or a total work content — the line capacity, utilisation, whether it meets demand and the minimum number of workstations with the line-balancing efficiency. Everything is computed locally and deterministically, so it is instant and private. Ideal for manufacturing, smart-factory, MES, IoT-dashboard and lean/TPM app developers, production-line monitoring and continuous-improvement tools, and industrial-engineering training. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 2 compute endpoints. This is OEE and takt maths; for equipment reliability/MTBF use a reliability API.

api.oanor.com/oee-api

Machining cutting-speed and feed maths as an API, computed locally and deterministically. The speed endpoint converts between cutting (surface) speed and spindle rpm for a given tool or workpiece diameter, in both directions and in either unit system: metric uses N = Vc·1000/(π·D) with Vc in metres per minute and D in millimetres, and imperial uses RPM = SFM·12/(π·D) with the surface speed in feet per minute and the diameter in inches. The feed endpoint computes the table feed rate from the feed per tooth (chip load), the number of teeth or flutes and the spindle rpm for milling (feed = fz·z·N), or from the feed per revolution for turning and drilling, and reports it in millimetres or inches per minute. The materials endpoint lists typical carbide cutting speeds by material, from aluminium and brass through mild and stainless steel to titanium, with a note to use about a third for HSS tooling. Everything is computed locally and deterministically, so it is instant and private. An indicative aid — always confirm with the tool maker's data and adjust for depth of cut, coolant and rigidity. Ideal for CNC and machine-shop tools, CAM and feeds-and-speeds apps, maker and hobby machining, and manufacturing calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is machining feeds and speeds; for screw-thread pitch and tap drill use a thread API and for bolt-circle layouts use a bolt-circle API.

api.oanor.com/machining-api