Time Management & Efficiency Flashcards

A maintenance technician has three simultaneous work orders: a conveyor bearing showing early-stage wear (non-critical line), a hydraulic leak on a press that is slowing—but not stopping—production by 15%, and a PM inspection due today on a critical air compressor that feeds three downstream lines. Production scheduling has 45 minutes of planned downtime on the press starting in 2 hours. What is the MOST efficient sequencing of these tasks?

Answer: Combine the hydraulic leak repair with the planned downtime window, complete the PM inspection now, then schedule the bearing for the next shift

The most efficient sequence uses the planned downtime window opportunistically for the hydraulic press repair (avoiding a second unplanned outage), completes the critical air compressor PM now before it becomes overdue and risks cascading line stoppages, and defers the non-critical bearing replacement to a scheduled slot. Option A is inferior because it delays the hydraulic fix past the optimal window. Option B ignores that the PM is on a critical shared asset. Option D wastes available action time.

A technician tracks that reactive (unplanned) repairs consume an average of 3.4× more labor-hours than the equivalent planned repair for the same fault type. If the site currently runs at 62% planned vs. 38% reactive maintenance and management wants to reach 80% planned, which metric BEST predicts whether the labor efficiency target will be met before re-baselining?

Answer: Ratio of PM compliance rate to emergency work order closure rate over the same period

PM compliance rate tracks whether planned work is actually being executed on schedule, while emergency work order closure rate tracks whether reactive demand is shrinking. Monitoring both together as a ratio directly measures the planned-vs-reactive shift being targeted. MTBF (A) reflects asset reliability but not labor allocation. Wrench-time ratio (C) measures productivity but not the planned/reactive split. Repeat failures (D) indicate root-cause gaps but lag the efficiency change by weeks.

During a time-study on a pump rebuild, a technician discovers that 28% of total job time is spent locating parts across three different storerooms. The plant has a kitting system for standard jobs but this rebuild is classified as 'non-routine.' What is the MOST direct intervention to recover that time on the next rebuild without reclassifying the job?

Answer: Create a shadow kit list attached to the equipment's BOM in the CMMS and pull it manually before the job is scheduled

Attaching a shadow kit list to the equipment's Bill of Materials in the CMMS preserves the non-routine classification while enabling pre-staging of parts before the job begins—directly eliminating the 28% search time. Reclassification (A) adds administrative overhead and changes workflows beyond the immediate problem. A verbal hold system (C) is unreliable and not auditable. A storeroom orientation (D) addresses technician knowledge but not the systemic absence of pre-staging for this job type.

A maintenance planner schedules a 4-hour electrical panel inspection during a Saturday shutdown. The electrician arrives and finds the panel requires thermographic imaging, which was not in the original scope and requires a separate certified thermographer. The thermographer is available but adds 90 minutes to the job. The next planned shutdown is 6 weeks away, and the panel serves a critical press. Which decision framework BEST supports the correct action?

Answer: Extend the Saturday job to include thermography, accepting the schedule overrun because the asset criticality and next window gap justify it

When an asset is critical and the next opportunity is 6 weeks away, the cost of a 90-minute overrun on an already-planned shutdown is far less than the risk of running a critical electrical panel without thermographic verification for 6 weeks. Asset criticality + window scarcity together justify scope expansion. Deferring the entire inspection (C) leaves the panel unchecked. A live-production scan (D) creates safety and operational risk. Strict scope adherence (A) is appropriate for non-critical assets with frequent windows, not here.

A technician averages 6.2 hours per shift on direct maintenance tasks (wrench time) against an 8-hour shift. Industrial benchmarks cite 55–65% wrench time as best-in-class for multi-craft sites. Analysis shows that 1.1 hours are lost daily to end-of-shift documentation and 0.5 hours to shift handover overlap. Which single intervention produces the HIGHEST sustainable wrench-time gain?

Answer: Migrate work order documentation to mobile devices used at the point of work, enabling real-time entry during task execution

Mobile point-of-work documentation directly attacks the largest time sink (1.1 hours/day) and is sustainable because it integrates documentation into task execution rather than adding a separate step. It also captures more accurate data. Eliminating handover overlap (A) saves only 0.5 hours and risks losing critical knowledge transfer, increasing repeat failures. Extending shifts (C) increases cost and doesn't improve efficiency—it just hides it. Dedicated planners for documentation (D) adds headcount cost and creates a data-accuracy bottleneck.

A facility implements Overall Equipment Effectiveness (OEE) tracking and finds that a CNC machine scores 71%: Availability 94%, Performance 82%, Quality 92%. The maintenance team is tasked with improving OEE to 80% within one quarter without capital investment. Where should maintenance effort be PRIMARILY directed?

Answer: Investigating speed losses and minor stoppages that are suppressing the Performance rate

OEE is multiplicative: 0.94 × 0.82 × 0.92 = 0.710. Performance at 82% is the weakest factor and has the greatest leverage. Raising Performance from 82% to 90% would yield 0.94 × 0.90 × 0.92 = 0.778—nearly reaching the 80% target from a single factor. Speed losses and minor stoppages (the Performance drivers) are typically addressable through maintenance-driven interventions like lubrication, tooling wear management, and sensor calibration without capital spend. Chasing Availability (A) requires large gains in an already-high metric for small OEE return. Equal effort distribution (D) dilutes impact.