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Mean Downtime (MDT)

ALCL 084
Alternate Definition

MDT is the average total downtime required to restore an asset to its full operational capabilities. MDT includes the time from reporting of an asset being down to the asset being given back to operations/production to operate. MDT also includes administrative time of reporting, logistics and materials procurement and lock-out/tag-out of equipment, etc., for repair or preventive maintenance.

Alternate Definition Source
General Information

The principal importance of MDT as a life cycle sustainment metric lies in its relationship to the Operational Availability (Ao) formula. Ao is one of the two components of the Sustainment Key Performance Parameter (KPP) defined in the Joint Capabilities Integration and Development System (JCIDS) Manual. Ao is defined as uptime/(uptime + downtime). The JCIDS Manual establishes Reliability (R) as a mandatory Key System Attribute (KSA) or Additional Performance Attribute (APA), and defines it as "a measure of probability that the system will perform without failure over a specific interval, under specified conditions." If reliability constitutes the "uptime" part of the Ao formula, MDT constitutes the "downtime." While not a formal KPP, KSA, or APA, MDT's importance in determining Ao is paramount.

MDT can also be seen as the average time an end item is unavailable to perform its assigned mission after it experiences unscheduled or scheduled maintenance actions. It includes all time where the system is not at the disposal of the force provider to initiate missions. In recently published update to DoDI 3110.05, Sustainment Health Metrics in Support of Materiel Availability, provides a slightly different method, than the traditional, of calculating operational availability (Ao).  The DoDI calculation for Ao, like the JCIDS Manual, is time-based, but uses different terms such as "available time" vs. "uptime" and "possible time" vs. "uptime + downtime." As additional policy and guidance updates are published, the differences between these formulas should be resolved.   In addition to the projected supply chain approach with its resultant logistics footprint, the impact of surge/deployment acceleration requirements should be determined for this and the Materiel Availability (Am) metric. As with most other high-level sustainment metrics, MDT is generally broken down into lower-level metrics.  For example in the DoD PBL Guidebook, Fig. 10 shows MDT decomposed into Logistics Response Time (LRT) and Mean Time to Repair (MTTR).

The DoD PBL Guidebook also provides a formula for MDT, which is the sum of Mean Preventive Maintenance (Mpt), Mean Corrective Maintenance (Mct), and Mean Logistics Delay (MLDT) divided by the total number of failures.  Mpt and Mct are essentially characteristics of system design. In other words, the design of the system will determine how much preventive maintenance is required and how long it will take. Similarly, system design will determine how much corrective maintenance is required (determined by the inherent R of the system) and how long it will take. On the other hand, MLDT is a function of process, a process that is the result of product support planning. MLDT is determined by such factors as adequacy and positioning of spare parts, transportation, operational issues—and many more. For this reason, the MDT metric is seldom part of a performance-based life cycle product support—or PBL—arrangement, since it would be highly unusual for one entity to control all aspects of MDT.

As with many other metrics, particularly those used in a Performance Based Logistics (PBL) environment, care must be taken to appropriately define the parameters of the lower-order MDT metrics and achieve a common understanding of that definition among the various stakeholders. The DoD Product Support Manager (PSM) Guidebook (Appendix B) states:

Metrics are mathematically and qualitatively described and should also be:

  • Linked to system level required sustainment metrics objectives
  • Appropriate to scope and responsibility
  • Specific in unit(s) of measure
  • Specific in acceptable range(s) or threshold(s)
  • Selected to motivate desired long-term behaviors
  • Understood and accepted
  • Easy to collect data and verify
  • Readily assessed/accessible
  • Analyzed to provide timely feedback