OPS 574 Week 3 Capacity and Quality Example

Busy Is Not the Same as Capable: Capacity Planning and Quality Assurance for a Regional Jet Maintenance Base

[Student Name]

University of Phoenix

OPS/574: Creating Value Through Operations

Week 3 Assignment

[Instructor Name]

[Date]

Blue Ridge Regional Airlines, its staffing, demand and figures are composites written for a model paper.

Week 2 found that heavy checks in the Knoxville hangar are held up by inspectors' buy-back and engineering dispositions, both running above 90 percent utilization in peak periods. This paper asks how much capacity the base needs as demand grows and how quality can be assured as checks speed up.

Demand for Heavy Checks

Forty heavy checks were performed last year. Two changes will raise the number. One partner airline is adding six regional routes, requiring three more aircraft, and older aircraft in the fleet are reaching the interval for a more extensive check. The forecast is 43 checks next year and 46 the year after. Non-routine work grows with age: records show about 1,800 non-routine hours per check now, rising to about 2,100 for the oldest aircraft. Total heavy check work rises from about 188,000 hours to about 228,000 within two years.

Capacity by Resource

Productive hours per person per year, after training, leave and other duties, are about 1,550. Technicians, about 180 assigned to heavy checks, provide about 279,000 hours, so heavy check demand of 228,000 hours would use about 82 percent, comfortably within reach. Inspectors are different. Inspection and buy-back require about 0.08 inspector hours per routine hour and about 0.12 per non-routine hour, about 450 inspector hours per check. At 40 checks that is about 18,000 hours against about 18,600 available on heavy checks, roughly 97 percent, which matches the peak observations in Week 2. At 46 checks with older aircraft it would be about 21,700 hours, more than the inspectors can supply even after the Week 2 changes free about 15 percent of their time. Engineering dispositions take about one engineering hour for every 25 non-routine hours, about 2,900 hours a year now against 3,100 available, or 93 percent; at 46 checks the need rises to about 3,700 hours, and the triage rule from Week 2, which removes about a fifth of requests, still leaves the two engineers above 95 percent.

Why High Utilization Hurts

Kingman (1961) showed that in a single-server queue under heavy traffic, average waiting time rises in proportion to utilization divided by one minus utilization, scaled by the variability of arrivals and service. In practical terms, moving a resource from 80 to 95 percent utilization roughly quadruples waiting when work is variable. Findings arrive unevenly, in bursts after zones are opened, so inspectors and engineers at 92 to 95 percent utilization produce exactly the long queues observed. The base should plan inspector and engineering capacity for about 80 percent utilization in peak periods, a cushion of about 25 percent.

Shift Patterns

Capacity also depends on when people work. The base runs a full day shift, a smaller evening shift and only a skeleton crew on weekends, while aircraft sit in the hangar seven days a week. About 0.4 days of the average overrun came from weekend idle time. Moving four inspectors and eight technicians to a Wednesday-to-Sunday schedule would keep buy-backs and repairs moving through weekends without adding people, though it requires negotiation with the technicians' union and a weekend pay differential of about $90,000 a year. Spreading the same people across more of the week raises effective capacity at the constraint where it matters most, during the long middle days of a check.

Seasonality

Demand for checks is not even through the year. The partner airlines want the most aircraft flying in summer and around holidays, so checks cluster in late winter and autumn. The capacity cushion therefore matters most in those months; contracting outside inspectors only for the peak months is a reasonable supplement to the main option.

Capacity Strategy

Olhager et al. (2001) linked long-term capacity decisions to manufacturing strategy and to sales and operations planning, distinguishing strategies that lead demand, lag it or track it. With demand growth known two years ahead and the cost of delay so high, the base should lead: add capacity before checks increase. Three options were compared:

Hire and certify six more inspectors and one more engineer: about $780,000 a year, available within nine months.

Certify ten senior technicians to perform routine buy-backs, under the airline's approved program, and hire one engineer: about $420,000 a year, available within six months.

Contract outside inspectors during peaks: about $600,000 a year, with less control over quality and availability.

The second option, combined with two new inspectors in year two, gives the needed cushion at the lowest cost.

Running the inspectors at ninety-five percent saved a salary and cost the airline three days on every jet.

The Cost of the Cushion

A 25 percent cushion at the constraint looks expensive on a utilization report: inspectors and engineers will sometimes be idle. But each day saved on a check is worth about $38,000, and the added capacity costs about $420,000 a year in the chosen option. If the cushion saves even 11 hangar days a year across all checks, it pays for itself; the Week 2 analysis suggests it will save far more. The base's managers will need a new way to read utilization figures: for inspectors and engineers, a number near 100 percent is now a warning, not an achievement.

Quality: Where Defects Come From

Quality in maintenance means airworthiness and no repeat defects. The base's repeat defect rate, problems that reappear within 30 days of release, is about 1.6 per aircraft. Latorella and Prabhu (2000) reviewed human error in aviation maintenance and inspection and identified contributing factors such as time pressure, poor communication at shift handovers, inadequate procedures and fatigue. Reason (2000) argued that errors are best addressed through a systems approach that builds defenses into processes rather than blaming individuals. Analysis of last year's repeat defects showed that about 60 percent arose from close-up and functional checks performed in the last two days of late checks, under pressure to release.

Quality Assurance Built Into the Process

Four practices protect quality without slowing checks. Error-proofing: standardized fastener kits and torque-tracking tools make missing or under-torqued fasteners visible. Independent checks: a second qualified person verifies critical tasks such as flight control connections, as the approved program requires. Handover discipline: a short, structured handover at each shift change for every open card. Reporting culture: technicians report errors and near misses through the airline's safety management system without fear of punishment for honest mistakes, and trends are reviewed monthly.

How Capacity and Quality Interact

Adequate inspector and engineering capacity reduces late checks, which reduces end-of-check pressure, the main source of repeat defects. Quality practices, in turn, reduce rework that consumes technician and inspector hours. Treating the two together is why the base can raise speed and quality at once.

Conclusion

Demand for heavy checks will rise about 15 percent in two years, with more non-routine work per check. Technicians have capacity; inspectors and engineers do not, and queuing theory explains why running them near full utilization creates the waits that make checks late. Leading demand with certified technician buy-backs, an added engineer and later inspectors provides a cushion at modest cost. Quality assurance built into the process, focused on the rushed end of late checks, protects airworthiness as checks speed up.

References

Kingman, J. F. C. (1961). The single server queue in heavy traffic. Mathematical Proceedings of the Cambridge Philosophical Society, 57(4), 902-904. https://doi.org/10.1017/S0305004100036094

Latorella, K. A., & Prabhu, P. V. (2000). A review of human error in aviation maintenance and inspection. International Journal of Industrial Ergonomics, 26(2), 133-161. https://doi.org/10.1016/S0169-8141(99)00063-3

Olhager, J., Rudberg, M., & Wikner, J. (2001). Long-term capacity management: Linking the perspectives from manufacturing strategy and sales and operations planning. International Journal of Production Economics, 69(2), 215-225. https://doi.org/10.1016/S0925-5273(99)00098-5

Reason, J. (2000). Human error: Models and management. BMJ, 320(7237), 768-770. https://doi.org/10.1136/bmj.320.7237.768