Simulation Analysis of Multi-Echelon Inventory for Repairable Items

Nie, Tao; Sheng, Wen

doi:10.1109/iciecs.2009.5364290

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…Abbott formula [1] is given by the expression as T = 6.8 × 10 -5 ×D 3 pn 2 , where T is propeller static thrust (unit N), D is diameter of propeller (unit m), p is propeller pitch (unit m) and n is number of revolution (unit rpm).…”

Section: Abbott Formula Methodsmentioning

confidence: 99%

Analysis of Propeller Static Thrust Estimation Method

Yang

Zhou

Zhang

et al. 2013

AMM

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Propeller thrust estimation method is convenient in selection of propellers. In this paper the Abbott formula method, Hamilton method and strip theory are introduced and then compared with the test value of propeller static thrust. The result shows that the three methods are all correct on the tendency of static thrust varies with revolution. Considered on the entire factor the Hamilton method is recommended.

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Section: Abbott Formula Methodsmentioning

confidence: 99%

Analysis of Propeller Static Thrust Estimation Method

Yang

Zhou

Zhang

et al. 2013

AMM

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“…The US military also has extensive repair systems (Kim et al ., 2007), including the Coast Guard (Basten and van Houtum, 2014) and Air Force (Slay and Sherbrooke, 1988). They are required when legacy capital equipment is out of production (Hollier, 1980), notably in radar systems (Nie and Sheng, 2009). They are also prominent in transportation systems, including public transportation (Díaz and Fu, 1997) and aerospace (Mabini, 2016).…”

Section: Literature Searchmentioning

confidence: 99%

“…Because computations can be excessive for repair kit problems (especially when lead times are nonzero), heuristic approaches are often employed. Prak et al ., (2017) and Kim et al ., (2007) developed a model assuming shortage cost only, and Nie and Sheng (2009) analyzed repair systems with two echelons concentrating on minimizing expected backorders. Heeremans and Gelders (1995) used a knapsack heuristic to solve a multi-period repair kit problem where they place a cycle service level constraint on the kit rather than individual parts.…”

Section: Literature Searchmentioning

confidence: 99%

Repair part service level differentiation based on holding other parts shortage costs

Maleyeff,

2024

JQME

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PurposeThe article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.Design/methodology/approachDemand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.FindingsThe results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.Social implicationsThe proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.Originality/valueThe optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

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“…Once the previous studies on inventory management and simulation models were explored through the literature review, a simulation model was built in Arena® 15.0 using the data collected from the case company. Arena® is a widely used and powerful simulation tool (Nie & Sheng, 2009).…”

Section: Simulation Modelingmentioning

confidence: 99%