Testing an AHP model for aircraft spare parts

Nariswari, Ni Putu Ayu; Bamford, David; Dehe, Benjamin

doi:10.1080/09537287.2018.1555341

Cited by 21 publications

(11 citation statements)

References 69 publications

(141 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the years, maintenance management researchers within the academia and industry have immensely contributed to the existing body of literature. A global keyword search ran by the authors of the current paper on industrial maintenance decision-making approaches for manufacturing systems (Goh et al, 2019;Roda et al, 2019;Ayu et al, 2019;Zhu et al, 2019;Cai et al, 2020;Nachimuthu et al, 2019;Lin et al, 2019;Dong et al, 2019;Li et al, 2019) reflects a very significant upsurge in the number of contributions directed towards this area which is anticipated to continue with the recent advances in computational technology as well as the increased realisation that real-life decision problems are seldom mono-criterion (Botti and Peypoch, 2013;Corrente et al, 2013;Wang and Triantaphyllou, 2008;Papadopoulos and Karagiannidis, 2008;Aguezzoul, 2014;Hartami-Marbini, 2011;Bumblauskas et al, 2017;Vujanovic et al, 2012;Yurin, 2012;Cassady et al, 2001;Carnero and Noves, 2006). Figure 2 details the search process adopted for identifying relevant studies.…”

Section: Historical Trends Of Knowledge Related To Maintenance Decision Making Theoriesmentioning

confidence: 99%

A hybrid of industrial maintenance decision making grids

Yunusa‐Kaltungo

Labib

2020

Production Planning & Control

View full text Add to dashboard Cite

It is fair to assume that the main challenge in maintenance decision making is the existence of a gap between theory and sustainable practice which is attributable to complexity, too much emphasis on development of new models that only serve to criticise earlier ones, underrepresentation of case studybased researches and lack of adequate incorporation of industry-based knowledge into most theoretical studies. In this paper, we revisited the application of the decision making grid (DMG) for maintenance optimisation but the main novelty here is to harmonise the strengths of the two most popular DMG approaches as opposed to the previous trends of advocating one over the other. Additionally, the current initiative limits assumptions associated with the process, since both DMG approaches depend on the main objective and nature of data involved. The data required for implementation are frequency of breakdown events and downtime for each event, which is readily available in all computerized maintenance management systems. This implies that we rely on just having access to some sort of a counter of faults and a timer for each event.

show abstract

Section: Historical Trends Of Knowledge Related To Maintenance Decision Making Theoriesmentioning

confidence: 99%

A hybrid of industrial maintenance decision making grids

Yunusa‐Kaltungo

Labib

2020

Production Planning & Control

View full text Add to dashboard Cite

show abstract

“…Ishizaka et al (2018) develop a method combining data envelopment analysis with AHP to minimise ABC rankings based only on percentage values. Ayu Nariswari et al (2019) develop and test a practical multi-criteria classification of aircraft spare part inventory using AHP.…”

Section: Multi-criteria Decision Making (Mcdm) and Ahpmentioning

confidence: 99%

“…Initially, it is important to identify relevant criteria affecting item criticality. To do so, the criteria selected for assessing the criticality of spare parts were based on previous studies (Botter and Fortuin, 2000; Suryadi, 2003, 2007; Braglia et al , 2004; Bosnjakovic, 2010; Molenaers et al , 2012; Roda et al , 2014; Stoll et al , 2015; Hu et al , 2018; Ayu Nariswari et al ., 2019). The result shows up 56 criteria.…”

Section: The Proposed Hybrid Approachmentioning

confidence: 99%

Spare parts inventory management: a new hybrid approach

Muniz

Conceição

Rodrigues

et al. 2020

IJLM

View full text Add to dashboard Cite

PurposeThe purpose of this paper is to present a new hybrid approach based on criticality analysis and optimisation to deal with spare parts inventory management in the initial provisioning phase in the mining industry. Spare parts represent a significant part of mining companies' expenditures, so it is important to develop new approaches to reduce the total inventory value of these items.Design/methodology/approachThis hybrid approach combines qualitative and quantitative methods based on VED (vital, essential and desirable) analysis, analytical hierarchical process (AHP), and e-constraint optimisation method to obtain the spare parts to be stocked. The study was applied to a large mining company. The mineral sector was chosen due to the great importance to the emerging Brazilian economy and the lack of researches in this sector. In addition, the spare parts have a relevant weight on the total inventory cost.FindingsPresent a novel approach combining multi-objective optimisation and multi-criteria evaluation approaches to tackle the inventory decision in spare parts management. This work also defines and classifies relevant criteria for spare parts management in the mineral sector validated by specialists. The proposed approach achieves an average increase of 20.2% in the criticality and 16.6% in the number of items to be stocked compared to the historical data of the surveyed company.Research limitations/implicationsThis paper applies the proposed approach to a mining company in Brazil. Future research in other companies or regions should analyse the adequacy of the criticality criteria, hierarchy and weights adopted in this paper.Practical implicationsThe proposed approach is useful for mining industries that deal with a large variety of resource constraints as it helps in formulating appropriate spare part strategies to rationalise financial resources at both tactical and strategic levels.Originality/valueThe paper presents a new hybrid method combining the AHP a multi-criteria decision making (MCDM) approach coupled with e-constraint optimisation to deal with spare parts inventory management allowing for a better spare parts inventory analysis in the initial provisioning phase and providing managers with a systematic tool to analyse the trade-off between spare parts criticality and total inventory value.

show abstract

“…This type of DPUT is often considered as a random variable due to its stochastic nature (Cattani, Jacobs & Schoenfelder, 2011). Intermittent DPUT a common occurrence for service and commercial companies that supply parts to industry sectors such as aerospace (Ayu Nariswari, Bamford & Dehe, 2019), automotive (Zhang & Xiaofeng, 2017), information technology (Antosz & Ratnayake, 2019), and military (Babai, Syntetos & Teunter, 2014). This particular frequency in demand could impact different company strategies (Pavlas et al, 2017;Devika et al, 2016), such as the use of inventory models (Jonkman, Barbosa-Póvoa & Bloemhof, 2019).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Managing slow-moving item: a zero-inflated truncated normal approach for modeling demand

Rojas

Coluccio

Vega-Vargas

et al. 2020

PeerJ Computer Science

View full text Add to dashboard Cite

This paper proposes a slow-moving management method for a system using of intermittent demand per unit time and lead time demand of items in service enterprise inventory models. Our method uses zero-inflated truncated normal statistical distribution, which makes it possible to model intermittent demand per unit time using mixed statistical distribution. We conducted numerical experiments based on an algorithm used to forecast intermittent demand over fixed lead time to show that our proposed distributions improved the performance of the continuous review inventory model with shortages. We evaluated multi-criteria elements (total cost, fill-rate, shortage of quantity per cycle, and the adequacy of the statistical distribution of the lead time demand) for decision analysis using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We confirmed that our method improved the performance of the inventory model in comparison to other commonly used approaches such as simple exponential smoothing and Croston’s method. We found an interesting association between the intermittency of demand per unit of time, the square root of this same parameter and reorder point decisions, that could be explained using classical multiple linear regression model. We confirmed that the parameter of variability of the zero-inflated truncated normal statistical distribution used to model intermittent demand was positively related to the decision of reorder points. Our study examined a decision analysis using illustrative example. Our suggested approach is original, valuable, and, in the case of slow-moving item management for service companies, allows for the verification of decision-making using multiple criteria.

show abstract

Testing an AHP model for aircraft spare parts

Cited by 21 publications

References 69 publications

A hybrid of industrial maintenance decision making grids

A hybrid of industrial maintenance decision making grids

Spare parts inventory management: a new hybrid approach

Managing slow-moving item: a zero-inflated truncated normal approach for modeling demand

Contact Info

Product

Resources

About