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Country benchmark · 2026

OEE benchmark Singapore 2026: manufacturing data, sector targets and downtime cost

The short answer: Manufacturing is 18.5% of GDP in Singapore (2025). Robot density is 818 robots per 10,000 manufacturing employees (2024), against a world average of 132. Typical OEE in the country's leading sectors runs 35–45%; the sector world-class targets are in the table below.

Official manufacturing statistics for Singapore, the OEE ranges that apply to its leading sectors, a downtime-cost calculator preloaded with national labour and energy costs, and the incentives that can fund a monitoring project.

Key figures

Manufacturing share
18.5
% GDP
Manufacturing value added
132.8
SGD bn
2025 · edb.gov.sg
Manufacturing employment
not published in an official source we could read
Manufacturing enterprises
not published in an official source we could read
Labour cost (manufacturing)
not published in an official source we could read
Industrial electricity price
not published in an official source we could read
Robot density
818
robots per 10,000 employees
2024 · ifr.org
Enterprises using AI
not published in an official source we could read

Leading sectors and the OEE ranges that apply

The first columns are Singapore's own sector mix (Singapore Department of Statistics (SingStat) / EDB). The OEE columns are the oee-benchmark.org editorial ranges for that sector type: they are benchmarks for plants, not national statistics.

SectorWeightTypical OEEWorld-class targetDominant lossA × P × Q
Electronics, Chemicals, Biomedical Manufacturing, Precision Engineering, Transport Engineering, General Manufacturing
Pharmaceuticals
cluster split published in EDB 2025p release (largest cluster output SGD 57.4 bn; text extraction could not pair values to clusters reliably) (2025)35–45%70%Validation & changeover80% × 90% × 97%

Downtime cost calculator: Singapore defaults

Change any input and the result updates. The labour and electricity defaults are the national statistics quoted above, not your plant's figures; replace them with your own numbers for a real estimate.

Estimated downtime cost
–
per year · – per month
  • labour–
  • energy–
  • lost margin–

Industrial hubs

Regions ranked by official manufacturing employment or output. Each hub page lists the plants that set the local benchmark.

HubManufacturing employmentKey sectorsNotable plants
Jurong / Tuas (west Singapore industrial estates)
SG city-state
132.8 SGD bn (2025)
manufacturing value added (national)
semiconductors, chemicals, precision engineering

Funding and incentives for monitoring projects (status October 2026)

Programmes a production-monitoring or OEE project can use. Status was checked on the operator's page in October 2026; anything we could not confirm is marked unverified.

ProgrammeOperatorWhat it fundsStatusSource
Smart Industry Readiness Index (SIRI) — Official AssessmentEDB (framework owner); assessments by certified assessors; global deployment via INCIT/WEFSingapore's own Industry 4.0 maturity benchmark (16 dimensions); used as the gating assessment for EDB/EnterpriseSG transformation support. Important: SIRI is a readiness benchmark, not an OEE benchmark — an OEE page for SG should position against SIRI vocabularyopen
open (framework active; co-funding terms unverified)
edb.gov.sg
EDB Advanced Manufacturing programmesEDBIndustry development; page states manufacturing = 21.6% of nominal GDP in 2022open
open
edb.gov.sg

Trade shows and events 2026–2027

EventCityDatesSource
Industrial Transformation ASIA-PACIFIC (ITAP) 2026 — relaunch editionSingapore (Suntec Convention Centre)20–21 October 2026hannovermesse.de
ITAP 2027 — full-scale editionSingapore (Marina Bay Sands)20–22 July 2027hannovermesse.de

Editor's note

Singapore has the second-highest robot density in the world (818) and developed the Smart Industry Readiness Index, now used globally; note that SIRI measures readiness, not OEE. Manufacturing is 18.5% of GDP and grew 13.9% in 2025 on electronics. ITAP returns in October 2026 and July 2027.

How to use this benchmark

Measure first. Log availability, performance and quality per line for four weeks before comparing with the sector ranges; a benchmark without your own baseline is a guess.
Compare within your sector, not with the national average. A packaging line at 72% may be world-class; a bottling line at 72% has room.
Price the gap. Use the calculator with your own labour cost and margin, then check the incentives table: several programmes fund the sensors and software that close it.
Free download

Singapore OEE Benchmark Pack 2026

Excel workbook: country profile, hubs, sector OEE ranges, downtime-cost calculator and incentives, with every source linked.

  • Country profile and hub table with sources
  • Sector OEE ranges: typical, world-class, A×P×Q
  • Downtime-cost calculator preloaded with Singapore labour and energy costs
  • Incentives and 2026–2027 events

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Frequently asked questions

What is a good OEE in Singapore?

There is no national OEE statistic: OEE is measured per line, and the useful comparison is by sector. For Singapore's leading sectors the typical range is 35–45% and the world-class targets are listed above. Most plants that start measuring sit near 60%.

Where do these figures come from?

Manufacturing weight, employment, labour cost, energy price and robot density come from official statistics (Singapore Department of Statistics (SingStat) / EDB, Eurostat, the World Bank and the IFR); every figure links to the page it was read from. The OEE ranges are oee-benchmark.org editorial benchmarks.

What is in the Singapore benchmark pack?

An Excel workbook with the country profile and sources, the hub table, the sector OEE ranges, a downtime-cost calculator with the national defaults already filled in, and the incentives and events lists. It is free; we ask for a work email.

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Sources and method

2026 OEE Benchmark Data Pack
Real world-class targets and typical ranges across 15 sectors, plus a built-in calculator that scores your line in 2 minutes.
Get the Free Benchmark Pack →