Contact Us

17 December 2025

Why Production Downtime Happens in MENA — And How to Prevent It

A practical guide for industrial operators in the UAE and wider MENA region

For industrial operators, unplanned downtime is not only an operational event — it’s a reliability and risk issue with direct impact on production, cost, and schedule commitments. The most effective improvements usually don’t come from one major initiative, but from disciplined fundamentals applied consistently across critical assets. Below, we share four common root causes of downtime and a practical playbook to prevent failures, improve response, and reduce outage duration in MENA plants.
The real cost of downtime (and why it is often underestimated)
Many organisations only count “lost production hours” when thinking about downtime. In practice, the total cost usually includes at least five layers:
  • Direct production loss (missed throughput, yield loss, off-spec product)
  • Labour and contracting premiums (overtime, specialist call-outs, shutdown crews)
  • Logistics premiums (expedited shipping, customs delays, rentals, temporary bypass)
  • Quality and integrity impacts (rework, scrap, repeated failures)
  • Risk costs (safety and environmental exposure during abnormal operation)
This is why global studies put unplanned downtime into “strategic risk” territory. Siemens’ report frames the problem at board-level scale, while Deloitte highlights how maintenance strategy alone can quietly erode capacity even before major failures occur. [1][3]

A simple reality-check calculation

For a single critical production unit, estimate:
  • Gross margin per hour of production (or avoided-cost per hour in utilities/water)
  • Typical unplanned outage hours per year for the unit
  • Multipliers for knock-on effects (overtime, quality losses, logistics)
When leadership sees downtime expressed as “annualised margin loss” rather than “maintenance events,” investment decisions become easier — especially when the countermeasures are largely operational discipline and engineering fundamentals, not speculative technology.
Regional conditions that increase downtime risk in MENA
In MENA, downtime is often less about a single breakdown and more about the conditions that surround it. The following factors typically accelerate degradation and extend outage duration:
Harsh operating environments
High ambient temperature affects both mechanical and electrical systems. For electronics, higher operating temperature is a widely recognised accelerator of ageing; Texas Instruments provides a reliability-based methodology for estimating useful lifetime of embedded processors under temperature-driven wear-out mechanisms.[4] For corrosion, ISO 9223 establishes how temperature/humidity, pollution (e.g., SO₂), and airborne salinity combine into atmospheric corrosivity categories. [5]
High utilisation and low redundancy
In many sectors (power, desalination, upstream/downstream oil & gas, metals), assets often run close to capacity. Where redundancy is limited, a single failure can become a plant-level constraint and trigger multi-unit disruption.
Imported spares and long lead times
For many critical assets, especially legacy equipment, parts are sourced from overseas OEMs or a limited supplier base. Maintenance logistics research shows that lead time and repair-capacity constraints are central drivers of system availability and service levels. [6] In other words: the outage duration can be dominated by procurement lead time rather than the technical repair itself.
Talent constraints and time pressure
Reliability engineers, rotating equipment specialists, and planners are in high demand. Under staffing pressure, plants often fall back to restoration-first behaviour and postpone root-cause elimination.
Four root causes behind production downtime (and the countermeasures that work)
Root cause #1:
Equipment stress from heat, dust/sand, and corrosion
In MENA, equipment operates under combined stressors that accelerate degradation.

Typical failure modes include:
  • Rotating equipment degradation: bearings, seals, and lubrication systems are sensitive to contamination control and alignment/imbalance
  • Electrical/electronic degradation: thermal stress, enclosure selection, cooling, and component derating become more critical
  • Corrosion damage: coatings/material selection, inspection interval, and drainage/cleanliness matter more in coastal and polluted zones
For lubrication and hydraulics, contamination control is a well-known reliability lever; industry guidance explains how microscopic particle contamination can damage machinery and why cleanliness control practices are central to reliability. [7]
Practical countermeasures (high ROI)
  • Targeted contamination control on critical assets (filters, breathers, sealing, sampling discipline; track cleanliness codes where applicable).
  • Heat management for sensitive electronics (ventilation, shading, enclosure selection, conservative ratings).
  • Corrosion strategy aligned to environment (use ISO 9223 classification; choose coatings/materials and inspections accordingly). [5]
  • Focus on the “small causes” early: misalignment, imbalance, erosion/fouling, poor lubrication — before they become catastrophic failures.
Root cause #2:
Reactive maintenance culture
Deloitte highlights that poor maintenance strategies can reduce overall productive capacity by 5–20%, and that unplanned downtime costs industrial manufacturers an estimated US$50 billion per year. [3] A common pattern is time-based maintenance that is not linked to real risk, condition, or failure history.
What reactive maintenance looks like
  • Fixed interval tasks (“every 6 months”) regardless of duty, environment, or failure history
  • Treating all assets the same instead of prioritising critical equipment
  • Limited use of vibration, oil analysis, thermography, or process-based indicators
  • Little or no structured root-cause analysis; repeat failures become “normal”.
What leading plants do instead
Predictive and condition-based approaches do not require a full “AI platform” to start delivering value. McKinsey reports that predictive maintenance typically reduces machine downtime by 30–50% and increases machine life by 20–40%. [8] Many sites achieve early wins via discipline and prioritisation:
  • Criticality ranking (safety, environment, production, quality, cost, redundancy).
  • Condition monitoring on the top-critical set first (start small; scale what works).
  • Failure coding and repeat-failure tracking to identify where to do RCA.
  • Standardised RCA on high-impact events, with tracked corrective actions.
Root cause #3:
Drawings, data, and asset visibility gaps
Downtime is often prolonged not by the failure itself, but by uncertainty: teams cannot quickly answer “what exactly is installed, how is it connected, and what changed?” Common symptoms in brownfield plants include out-of-date as-builts, undocumented modifications, and fragmented asset history across spreadsheets and PDFs.

When engineering data is unreliable, outages expand through extra site visits, measurement errors, rework, and slower approval cycles. This is where 3D reality capture can help: NIST documents the establishment of ASTM E57 to develop standards for performance evaluation of 3D imaging systems, reflecting the industry need for repeatable, measurable quality in 3D capture. [9]
Practical countermeasures
  • Treat as-built accuracy as an operational control (update after every modification; not optional).
  • Create a minimum viable “single source of truth” for critical drawings, tags, and spares master data.
  • Use 3D scanning strategically for complex brownfield areas, tie-ins, and interference checking (especially ahead of shutdowns).
  • Link engineering data to work execution (CMMS/EAM work orders, asset registers, inspection plans).
Industrial 3D scanning
If outdated as-builts or hard-to-measure areas slow shutdown planning, 3D scanning can capture accurate geometry for tie-ins, retrofits, and modifications — with fewer site surprises.
Explore our 3D scanning services
Root cause #4:
Spare-part dependency and long lead times
For many critical assets—especially legacy equipment—spare parts are sourced from overseas OEMs or a limited supplier base. In practice, outage duration is often driven less by the hands-on repair and more by “maintenance delay”: waiting for parts, repair-shop capacity, or long procurement lead times. That’s why a relatively minor failure can keep a critical asset offline far longer than the repair itself.[6]
Practical countermeasures
  • Critical spares strategy tied to asset criticality and lead time (not a flat “stock everything” approach).
  • Repairable spares loops where feasible (exchange programs, local repair capability).
  • Reverse engineering workflows for obsolete parts where OEM supply is impractical — with verification and quality control built in.
Reverse engineering & local CNC manufacturing
When a critical part is obsolete or long-lead, we can scan the component, recreate the CAD, and manufacture a verified replacement locally in the UAE — reducing “waiting time” during outages.
See our CNC manufacturing & custom parts
A practical downtime-reduction playbook (what to do first)
Knowing the causes of downtime is only half the job. The difference comes from execution: prioritising the right assets, putting basic controls in place, and building routines that prevent repeat failures. Below is a practical phased plan that delivers measurable improvements without overwhelming the team.
Phase 1 (0–90 days):
Stabilise and prioritise
  1. Build a critical asset register: top 20–50 assets that drive. safety/environment/throughput risk.
  2. Baseline downtime: define what counts as an event, and track hours + causes consistently.
  3. Agree the “top failure modes” list for the critical assets (from history and expert judgement).
  4. Implement fast feedback: for any critical failure, require a short RCA and one permanent corrective action.
  5. Quick wins on basics: alignment, lubrication discipline, filtration/sealing, housekeeping, heat mitigation on sensitive cabinets.
Phase 2 (3–6 months):
Move from firefighting to control
  1. Introduce condition monitoring for the most critical rotating equipment (vibration + temperature; oil analysis for selected assets).
  2. Review maintenance plans for critical assets: remove low-value tasks; add risk/condition logic.
  3. Start a spares criticality review: identify long-lead, single-source, and obsolete items
  4. Repair the data foundation: verify tags and as-builts for the most critical systems first.
Phase 3 (6–12 months):
Engineer out repeat failures
  1. Establishа a repeat-failure elimination program (Pareto-driven; track savings and recurrence).
  2. Standardise modification control and as-built updates as part of work close-out.
  3. Use 3D scanning for high-risk retrofit/shutdown scopes to reduce surprises and rework [9].
  4. Formalise local repair / reverse engineering routes for selected components to reduce outage lead time.
Need extra engineering support on site?
During shutdowns and urgent reliability work, embedded engineering capacity can speed up investigations, redesign weak points, and support execution without long lead times.
Learn about Engineering as a Service (EaaS)
Final thoughts
Downtime in MENA is rarely caused by one dramatic failure. More often, it is the compound result of environment-driven wear, reactive work management, weak asset data, and long lead times for critical parts. The encouraging part is that these are manageable drivers. Plants that combine criticality-driven maintenance, disciplined data foundations, smarter spares strategy, and local engineering execution typically achieve meaningful reliability gains.

Important note on benchmarks: the quantitative ranges cited here are global estimates; the true value for your facility will depend on process economics, redundancy, asset age, and maintenance maturity. Use the cited studies as directional guidance, then validate against your own downtime and cost data.
References
  1. Siemens. The True Cost of Downtime 2024 (PDF). https://assets.new.siemens.com/siemens/assets/api/uuid:1b43afb5-2d07-47f7-9eb7-893fe7d0bc59/TCOD-2024_original.pdf
  2. Siemens. The True Cost of Downtime 2022 (PDF). https://assets.new.siemens.com/siemens/assets/api/uuid:3d606495-dbe0-43e4-80b1-d04e27ada920/dics-b10153-00-7600truecostofdowntime2022-144.pdf
  3. Deloitte. Asset Optimization: Predictive Maintenance (web). https://www.deloitte.com/us/en/services/consulting/services/predictive-maintenance-and-the-smart-factory.html
  4. Texas Instruments. Calculating Useful Lifetimes of Embedded Processors (SPRABX4B) (PDF). https://www.ti.com/lit/pdf/sprabx4
  5. ISO. ISO 9223:2012 — Corrosion of metals and alloys — Corrosivity of atmospheres (standard description). https://www.iso.org/standard/53499.html
  6. Driessen, M., Arts, J., van Houtum, G.-J., Rustenburg, J., & Huisman, B. Maintenance spare parts planning and control: a framework for control and agenda for future research. Production Planning & Control (2015). https://www.tandfonline.com/doi/abs/10.1080/09537287.2014.907586
  7. Machinery Lubrication. Taking Lubricant Cleanliness to the Next Level (web). https://www.machinerylubrication.com/Read/1291/lubricant-cleanliness
  8. McKinsey & Company. Manufacturing analytics unleashes productivity and profitability (web). https://www.mckinsey.com/capabilities/operations/our-insights/manufacturing-analytics-unleashes-productivity-and-profitability
  9. NIST. ASTM E57 3D Imaging Systems Committee: An Update (PDF). https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=860707