Testing an innovative predictive management system for bus fleets: outcomes from the Ravenna case study

Corazza, Maria Vittoria; Magnalardo, Silvia; Musso, Antonio; Petracci, Enrico; Tozzi, Michele; Vasari, Daniela; Verdalle, Emmanuel de

doi:10.1049/iet-its.2017.0207

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…Although the latter was not disseminated, the lesson learnt showed similarities between the PTWs and bus fleets: the need to integrate more models to describe in a more accurate way the emission phenomena, its underestimation, the relevance of maintenance to mitigate it. One more case study in Ravenna (norther Italy), based on preliminary COPERT-based calculations for a large set of pollutants emitted by a restricted fleet of buses under test within the above mentioned EBSF_2 project corroborated such lesson [43].…”

Section: The Adopted Methodologymentioning

confidence: 76%

“…The resulting model, iGREEN, was embedded in a specific software, developed during the EBSF_2 project (a follow-up of the above-mentioned EBSF project), still funded by the European Commission [4]. This software was initially designed to manage predictive maintenance operations at bus garages [43]. The iGREEN new features to embed were thus specifically designed to improve the quality of the maintenance diagnostics, by providing additional predictive information on the emissions.…”

Section: A Methodology To Address the Obsolescence Issuementioning

confidence: 99%

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iGREEN: An Integrated Emission Model for Mixed Bus Fleets

et al. 2021

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The environmental concern has become central for many bus companies, but estimating pollutant emissions can be difficult for many reasons (little knowledge or underestimation of the problem; scarce know-how; reluctance to acknowledge the pollutant potential of bus fleets because either of small size or composed by too many old-generation vehicles). To facilitate this task, an integrated, user-friendly model, iGREEN, is presented. The paper describes the methodology for the development of this tool, which is specifically designed to help transit operators in assessing the pollutants emitted by fleets where the amount of old buses is not negligible. This is not a minor issue, given the large number of obsolete vehicles still circulating and the unsuitability of some models when calculating emissions in case of buses with protracted mileage. Results from two case studies are reported and commented, with the final aim to advance knowledge farther afield. This gives rise to a discussion on the relevance of such environmental concerns also in light of the contemporary pandemic which seem to have generated different priorities in the public transport management.

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Section: The Adopted Methodologymentioning

confidence: 76%

Section: A Methodology To Address the Obsolescence Issuementioning

confidence: 99%

iGREEN: An Integrated Emission Model for Mixed Bus Fleets

et al. 2021

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“…This tendency has necessitated the study of safety stock policies for public transit systems (Sun et al ., 2020). Various approaches have been used in these settings including mathematical programming models for systems in rapid-speed trains (Lin et al ., 2017), double negative binomial approximations (Díaz and Fu, 1997) and monitoring approaches for buses (Corazza et al ., 2018). Long lead times are common in these inventory systems because part demand is typically low volume and specialized (Basten and van Houtum, 2014).…”

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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“…Proper maintenance is an effective solution for reducing device failures and maintaining the normal operation of a system [1]. In the railway transportation, aviation, and electric power industries, preventive maintenance was the most important strategy [2][3][4]. Regarding how to develop a preventive maintenance strategy, a basic approach was proposed in [5].…”

Section: Related Workmentioning

confidence: 99%

A novel refined maintenance strategy for full life cycle of high‐speed automatic train protection system

Kang,

Pang,

Cheng

et al. 2023

IET Intelligent Trans Sys

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Automatic train protection (ATP) system is essential for ensuring the safe operation of high‐speed trains. However, the existing extensive and fixed maintenance mode of the ATP system results in a waste of resources. To achieve a state of operation and maintenance that ensures both protection capability and economic efficiency, a lean method in a dynamic maintenance mode for the full life cycle of the ATP system is proposed. Firstly, reliability tests are carried out based on historical failure data. The parameter values of the possible life distribution are estimated by maximum likelihood method, and the optimal life distribution of different devices is obtained through the Kolmogorov–Smirnov hypothesis test. Secondly, a dynamic failure rate function is introduced to describe the impact of maintenance on device performance. A refined maintenance model is then established within the life cycle, and the dynamically changing preventive maintenance intervals and frequencies are obtained using a genetic algorithm. Finally, to mitigate the impact of the intermittent operation of ATP system on maintenance, the multidimensional relationships among the maintenance strategy, service time and operation mileage are revealed. The effectiveness of the proposed method is verified through an example test on a type of driver machine interface device.

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Testing an innovative predictive management system for bus fleets: outcomes from the Ravenna case study

Cited by 13 publications

References 20 publications

iGREEN: An Integrated Emission Model for Mixed Bus Fleets

iGREEN: An Integrated Emission Model for Mixed Bus Fleets

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

A novel refined maintenance strategy for full life cycle of high‐speed automatic train protection system

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