Deutsch: Ausfallzeit / Español: Tiempo de inactividad / Português: Tempo de inatividade / Français: Temps d'arrêt / Italiano: Tempo di inattività

Downtime is the period during which a machine, system, or production line is not operational or is out of service. In an industrial context, it refers to any time that equipment is not functioning correctly or at all, which can lead to delays in production, increased costs, and decreased efficiency.


In the industrial context, downtime is a critical factor that can significantly impact productivity and profitability. Downtime can be categorized into two main types: planned downtime and unplanned downtime.

  • Planned Downtime: This includes scheduled maintenance, inspections, and upgrades. It is usually arranged during periods that will cause the least disruption to production schedules.
  • Unplanned Downtime: This occurs due to unexpected equipment failures, power outages, or other unforeseen issues. It often leads to significant disruptions and can be costly.

The implications of downtime are vast, affecting not just production but also labour costs, delivery schedules, and customer satisfaction. Key metrics used to measure downtime include Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR).

Effective management of downtime involves several strategies:

  • Preventive Maintenance: Regularly scheduled maintenance to prevent equipment failures.
  • Predictive Maintenance: Using data and analytics to predict when equipment is likely to fail so that maintenance can be performed just in time.
  • Root Cause Analysis: Identifying and addressing the underlying causes of unplanned downtime to prevent recurrence.
  • Efficient Spare Parts Management: Ensuring that necessary spare parts are readily available to reduce repair times.

The cost of downtime can be substantial. For example, in the automotive industry, downtime can cost hundreds of thousands of dollars per hour. Therefore, minimizing downtime is crucial for maintaining operational efficiency and competitiveness.

Application Areas

Downtime affects various areas within the industrial context, including:

  • Manufacturing: Halting production lines can lead to delays in product delivery and increased labour costs due to idle workers.
  • Supply Chain Management: Downtime can disrupt the supply chain, leading to delays and increased inventory costs.
  • Maintenance Operations: Managing and reducing downtime is a primary focus to ensure continuous operation and longevity of equipment.
  • Energy Sector: In power plants, downtime can disrupt energy supply and result in significant financial losses.

Well-Known Examples

Notable examples of downtime in the industry include:

  • Automotive Industry: Assembly line stoppages at major car manufacturers like Ford and Toyota due to equipment failures or supply chain issues.
  • Aerospace Industry: Downtime in aircraft production at companies like Boeing, often resulting from complex supply chain logistics and stringent quality checks.
  • IT and Data Centres: Server downtimes at data centres, impacting companies like Amazon or Google, can lead to massive financial losses and service disruptions.
  • Oil and Gas Industry: Rig downtime in offshore drilling operations can be extremely costly, impacting companies like BP and ExxonMobil.

Treatment and Risks

Managing downtime involves several approaches and considerations:

  • Investment in Reliable Equipment: Ensuring high-quality and reliable machinery can reduce the frequency of breakdowns.
  • Regular Training: Training employees to handle equipment properly and perform basic troubleshooting can prevent unnecessary downtime.
  • Implementation of Advanced Technologies: Using IoT, AI, and machine learning for predictive maintenance can significantly reduce unplanned downtime.
  • Backup Systems: Having backup systems in place can help mitigate the impact of downtime.

However, managing downtime also comes with risks:

  • High Maintenance Costs: Preventive and predictive maintenance programs can be costly to implement and maintain.
  • Complexity: Advanced predictive maintenance requires sophisticated data analysis and can be complex to manage.
  • Initial Downtime for Upgrades: Implementing new systems or technologies can initially increase downtime due to the transition period.

Similar Terms

  • Idle Time
  • Outage
  • Shutdown
  • Breakdown
  • Interruption
  • Non-Operational Time


Downtime in the industrial context refers to periods when equipment or systems are non-operational, affecting productivity and profitability. Effective downtime management through preventive and predictive maintenance, root cause analysis, and efficient spare parts management is crucial. Minimizing downtime is essential to maintain operational efficiency and competitiveness, despite the challenges and costs associated with managing it.


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