OPS 574 Week 4 Supply Chain Workflows Example

The Bracket That Arrived on Day Fourteen: Evaluating Parts and Repair Workflows Behind a Heavy Maintenance Check

[Student Name]

University of Phoenix

OPS/574: Creating Value Through Operations

Week 4 Assignment

[Instructor Name]

[Date]

Blue Ridge Regional Airlines, its suppliers, parts data and figures are composites written for a model paper.

The Knoxville hangar depends on parts it does not make and repairs it does not perform. Weeks 2 and 3 addressed inspection, engineering and capacity inside the base. This paper follows the supply chain that feeds a check, because the Week 1 analysis attributed about 1.4 of the 3.4 days of average overrun to waiting for parts.

Three Parts Flows

Parts reach a check through three flows. Planned kits: about 4,000 expendable parts and consumables per check, such as seals, fasteners, filters and sealants, are picked from the base's stores and staged in carts before induction based on the routine task cards. Urgent orders: when inspection finds damage, the repair may need a structural part, a bracket, skin panel or fitting, that the base rarely uses and does not stock; these are ordered from the aircraft manufacturer or a distributor, sometimes as aircraft-on-ground orders at premium cost. Rotables: components removed during the check, such as actuators, valves and starters, are sent to outside repair shops; a serviceable spare from the airline's pool is installed if available, and the removed unit returns after repair.

Where the Parts Delays Come From

Records from 40 checks traced 214 parts-related delays of more than four hours. Urgent orders for finding-related parts caused about 55 percent of the delay time, with average lead times of five days and some over two weeks for structural parts. Rotable shortages, when the pool had no serviceable spare because the removed units were still at repair vendors, caused about 30 percent. Kit errors, missing or wrong items in planned kits, caused about 15 percent, usually quickly fixed but frequent. Information flows made each worse: urgent orders were placed only after an engineering disposition specified the part, often two days after the finding, and repair vendors learned of a needed unit only when it arrived on their dock.

Forecasting the Unforecastable

Finding-related parts look random check by check, but not across the fleet. Ghobbar and Friend (2003) evaluated forecasting methods for intermittent demand for aircraft spare parts and found that method performance depended on the demand pattern, with some methods well suited to lumpy, intermittent demand. Blue Ridge's records show that about 40 structural part numbers account for about 70 percent of finding-related orders, concentrated in a few zones, such as cargo door surrounds and lower fuselage frames, on aircraft past a certain age. Those parts can be forecast at the fleet level and stocked or kitted by zone, even if any one check's needs are uncertain.

The Rotable Pool and Repair Loop

Rotable availability depends on the number of spares in the pool and the time units spend in repair. Muckstadt (1973) developed models for managing multi-item, multi-echelon inventories of repairable items, showing how pool size and repair turnaround together determine availability. Blue Ridge's repair vendors average 21 days of turnaround, with wide variation, and contracts pay per repair with no turnaround commitment. Kilpi et al. (2009) analyzed cooperative strategies for providing availability services for repairable aircraft components, finding that pooling and cooperation among operators and service providers could reduce costs and improve availability. A shorter, more reliable turnaround would reduce shortages more cheaply than buying more spares.

A spare that sits on a repair shop's shelf for three weeks is a spare the airline paid for twice.

Redesigning the Workflows

Zone-based finding kits: for aircraft past the age threshold, the base pre-stages likely structural parts for high-finding zones before induction, based on the fleet forecast; unused parts return to stores. Consignment stock: the aircraft manufacturer keeps a consignment stock of the 40 most-ordered structural parts at the base, paid for when used, in exchange for a three-year purchase commitment. Earlier ordering: engineering issues a preliminary parts list with each finding before the full disposition, so purchasing can start sourcing. Repair vendor agreements: contracts move to turnaround commitments, 10 days standard and 4 days for expedited units, with incentives for on-time return and penalties for late return, plus advance notice of units coming off the aircraft. Shared check schedules: suppliers and repair vendors receive the 12-month check schedule and each check's expected removals two weeks before induction.

Information Flows Matter as Much as Parts

The redesign changes information as much as material. Today a finding becomes a parts order only after a chain of handoffs: technician to inspector, inspector to engineering, engineering to planner, planner to buyer. Each handoff adds hours and the chance of error, such as a wrong part number copied from a drawing. The new process sends the finding photo and preliminary parts list from the technician's tablet directly to engineering and purchasing at once, so the buyer can check stock and lead times while the engineer prepares the disposition. The order is confirmed, not started, when the disposition arrives.

Costs and Benefits

Zone kits and safety stock not covered by consignment add about $350,000 in inventory, about $70,000 a year in carrying cost. Turnaround incentives cost about $180,000 a year. Removing an estimated 1.0 day of the 1.4 days of parts-related overrun is worth about $38,000 per day across 46 checks, about $1.7 million a year, while premium freight for urgent orders falls by about $200,000.

What the Buyers and Planners Said

The base's two parts buyers described the urgent order process as a scramble: a technician calls stores, stores calls purchasing, purchasing waits for engineering's part number and then calls three distributors to find stock. Planners said they rarely knew which aircraft were past the age threshold when building kits. Both points shaped the redesign: the preliminary parts list gives purchasing a head start, and planners now receive a fleet age list with each check package so zone kits can be built for the aircraft that need them.

Kit Accuracy

Kit errors are the smallest share of parts delay but the most frequent. Most come from task cards revised after the kit list was printed. Linking kit lists to the current revision of each card in the maintenance system and having a stores clerk check each kit against a scanned list before it goes to the bay should remove most of these errors.

Making Suppliers Want the Change

Each supplier gains something: the manufacturer gets a committed volume, repair vendors get predictable inflow and incentives, distributors get forecasts instead of emergencies. Monthly scorecards shared with each supplier measure fill rate, turnaround and on-time delivery, and the results are discussed in a quarterly call with each supplier's account manager.

Conclusion

About 40 percent of the base's check overrun comes from its supply chain: urgent parts for findings, rotables stuck in repair and kit errors, each made worse by late information. Fleet-level forecasting of finding parts, zone kits, manufacturer consignment, earlier preliminary orders and turnaround-based repair contracts address each source. The redesign spends inventory and incentive money where it buys back hangar days, which in this operation are worth far more.

References

Ghobbar, A. A., & Friend, C. H. (2003). Evaluation of forecasting methods for intermittent parts demand in the field of aviation: A predictive model. Computers & Operations Research, 30(14), 2097-2114. https://doi.org/10.1016/S0305-0548(02)00125-9

Kilpi, J., Töyli, J., & Vepsäläinen, A. (2009). Cooperative strategies for the availability service of repairable aircraft components. International Journal of Production Economics, 117(2), 360-370. https://doi.org/10.1016/j.ijpe.2008.12.001

Muckstadt, J. A. (1973). A model for a multi-item, multi-echelon, multi-indenture inventory system. Management Science, 20(4), 472-481. https://doi.org/10.1287/mnsc.20.4.472