D 11.1
Ravenna: Demo Description and Implementation Plan
Version 1.0
Date of issue 16/06/2016
Nature of Deliverable External
Dissemination Level Public
Status Final
Issued by Project Director
Guido Di Pasquale, Michele Tozzi, Pluservice UITP
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 636300. Coordinator: UITP – International Association of Public Transport
D309.1 Page 1 of 38 SUMMARY SHEET Programme Horizon 2020 Contract N. 636300 Project Title European Bus Systems for the Future 2 Acronym EBSF_2 Coordinator UITP – International Association of Public Transport Project Director Michele Tozzi, [email protected] Web-site http://ebsf2.eu Starting date 1 May 2015 Number of months 36 months
Deliverable N. 11.1 Deliverable Title Ravenna: Demo description and implementation plan Version 1.0 Date of issue 16th June 2016 Distribution [Internal/External] External Dissemination level Public Abstract The overall objective of the EBSF_2 Ravenna demonstration is the test and implementation of two innovative technological solutions dealing with Intelligent garage and predictive maintenance and IT standard introduction in existing fleets. An accurate maintenance budget plan and predictive maintenance are the basis to increase service reliability. The optimisation of the maintenance scheduling allows the decrease of maintenance costs, breaks, spare parts usage and also the quantity of waste material. Analysis of oil can tell a lot about the health of an engine and residual metals can tell about parts becoming corroded and give a signal that maintenance is necessary before the scheduled one. On the other hand if the result of the oil analysis is good the ordinary maintenance could be postponed with a reduction of maintenance cost. This document describes in detail the objectives of the technological innovations “Predictive maintenance” and “Analysis of the maintenance budget” to be tested within the Ravenna demo, coherently with the Project Validation Objectives as defined in WP2. Moreover it reports on technical specifications, functional and not- functional requirements and planning of the demo activities along the project’s lifetime. Keywords Intelligent Garage, Predictive Maintenance, Budget, Oil Quality Sensor
This report is subject to a disclaimer and copyright. This report has been carried out under a contract awarded by the European Commission, contract number: 636300 No part of this report may be used, reproduced and or/disclosed, in any form or by any means without the prior written permission of UITP and the EBSF_2 consortium. All rights reserved. Persons wishing to use the contents of this study (in whole or in part) for purposes other than their personal use are invited to submit a written request to the following address: UITP International Association of Public Transport Rue Sainte-Marie 6- 1080 Brussels
D309.1 Page 2 of 38 INTERNAL DISTRIBUTION Participant N° Participant organisation name Country 1 Coordinator Union Internationale des Transports Publics - UITP Belgium 2 Régie Autonome des Transports Parisiens - RATP France 3 Iveco France SA - IVECO France 4 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.-FRAUNHOFER Germany 5 Hübner Gummi- und Kunststoff GMBH - HUEBNER Germany 6 DigiMobee SAS - DIGIMOBEE France 7 Centro de Estudios e Investigaciones Técnicas - CEIT Spain 8 Chalmers Tekniska Hoegskola AB - CHALMERS Sweden 9 Compañía del Tranvía de San Sebastián, SA (CTSS) – DBUS Spain 10 IRIZAR S Coop - IRIZAR Spain 11 D’Appolonia S.p.A. - DAPP Italy 12 EvoBus GmbH - EVOBUS Germany 13 Volvo Bus Corporation - VBC Sweden 14 Pluservice srl - PLUSERVICE Italy 15 Universidad Politécnica de Madrid - UPM Spain 16 Actia S.A. - ACTIA France 17 Teknologian Tutkimuskeskus - VTT Finland 18 MEL-SYSTEM Italy 19 Ineo Systrans – INEO France 20 Stuttgarter Strassenbahnen AG - SSB Germany 21 Associazione Trasporti - ASSTRA Italy 22 Pilotfish Networks AB - PILOTFISH Sweden 23 Start Romagna SpA - START ROMAGNA Italy 24 FIT Consulting Srl - FIT Italy 25 Hogia Public Transport Systems AB - HOGIA Sweden 26 Trapeze ITS UK Limited - TRAPEZE Switzerland 27 Digigroup Informatica srl - DIGIGROUP Italy 28 Transports de Barcelona SA - TMB Spain 29 TIS PT, Consultores em Transportes, Inovação e Sistemas, SA - TISPT Portugal 30 Rupprecht Consult - Forschung & Beratung GmbH - RUPPRECHT Germany 31 Keolis SA - KEOLIS France 32 Syndicat Mixte des Transports pourle Rhone et l agglomeration Lyonnaise - SYTRAL France 33 Transport for London – TFL UK 34 Università degli Studi di Roma La Sapienza – UNIROMA1 Italy 35 Verband Deutscher Verkehrsunternehmen - VDV Germany 36 Promotion of Operational Links with Integrated Services, Association Internationale-POLIS Belgium 37 Tekia Consultores Tecnologicos S.L - TEKIA Spain 38 Innovative Informatikanwendungen in Transport-, Verkehrs-und Leitsystemen GmbH-INIT Germany 39 Union des Transports Publics - UTP France 40 Västtrafik AB - VTAB Sweden 41 Commissariat à l’Energie Atomique et aux Energies Alternatives - CEA France 42 Consorcio Regional de Transportes de Madrid - CRTM Spain
D309.1 Page 3 of 38 EXTERNAL DISTRIBUTION Entity Short name Country Contact person European Commission - INEA EC INEA - Mr. Walter Mauritsch
DOCUMENT CHANGE LOG Version Date Main area of changes Organisation Comments 0.1 06/10/2015 First draft. Table of Pluservice Content. Predicitive maintenenace and Budget management 0.2 10/10/2015 Main content and Pluservice Validation objectives 0.3 22/10/2015 Oil quality sensor MEL-System description 0.4 24/10/2015 Implementation plan Pluservice 0.5 26/10/2015 Consolidation and review Pluservice 1.0 01/06/2016 Quality check and final UITP review 1.0 16/06/2016 Final version Pluservice
CONTRIBUTING PARTNERS Company Names Company Info Pluservice Di Pasquale, Petracci ICT solution provider MEL-System Brambilla Oil Quality sensor and filter provider START ROMAGNA Zuccherelli Public Transport Operator UNIROMA1 Corazza, Musso Evaluation
ACRONYMS DoW – Description of Work KPI – Key Performance Indicator TI – Technological Innovation TS – Test scenarios VO – Validation Objective AVM – Automatic Vehicle Monitoring AVL – Automatic Vehicle Localisation TIRav1 – Technological Innovation Ravenna 1 (Predictive maintenance) TIRav2 – Technological Innovation Ravenna 2 (Analysis of maintenance budget) PT – Public Transport LCC – Lyfe Cycle Cost IT – Information Technology ITC – Information and Communication Technology FMS – Fleet Management System CAN – Controller Area Network
D309.1 Page 4 of 38 SW - Software
INDEX 1 Executive Summary...... 6
2 Introduction ...... 7
3 Background and context...... 8 3.1 Geographical and urban context ...... 8 3.2 Service background...... 8
4 Demo objectives...... 13
5 Demo description ...... 16 5.1 Predictive maintenance ...... 16 5.1.1 Architecture...... 18 5.1.2 Oil Quality Sensor...... 21 5.2 Analysis of maintenance budget ...... 23
6 Demo implementation plan ...... 26 6.1 Description ...... 26 6.2 Gantt Chart...... 28 6.3 Demo team...... 29
7 Partner Contribution ...... 31
8 CONCLUSIONS ...... 32
9 ANNEXES ...... 33 9.1 ANNEX 1 – Maintenance Class of the methane fueled bus...... 33 9.2 ANNEX 2 – Maintenance Class of the diesel fueled bus ...... 35 9.3 ANNEX 3 – List of EBSF_2 Validation Objectives...... 36
INDEX OF FIGURES Figure 1 – Ravenna demonstration geographical context ...... 8 Figure 2 – One of the garages operated by START ROMAGNA...... 10 Figure 3 – Examples of the buses operated by START ROMAGNA ...... 10 Figure 4 – Maintenance scheduling...... 11 Figure 5 – Example of a report of the final cost balance-1 ...... 11 Figure 6 – Example of a report of the final cost balance-2 ...... 12 Figure 7 – High level architecture...... 19 Figure 8 – Oil quality sensor and oil flow ...... 21 Figure 9 – Oil quality sensor installed in diesel fuelled Bus...... 21 Figure 10 – Oil quality sensor installed in methane fuelled Bus ...... 22 Figure 11 – Fine oil filtration, Macpherson curve ...... 22 Figure 12 – Overall Gantt chart ...... 28 Figure 13 – Gantt chart, zoom on TIRav1 implementation plan ...... 28 Figure 14 – Gantt chart, zoom on TIRav2 implementation plan ...... 29
INDEX OF TABLES Table 1 – START ROMAGNA’s bus fleet ...... 9 Table 2 – Type of Buses of the fleet ...... 9 Table 3 – Technological Innovation and Validation Objectives ...... 14 Table 3 – Technological Innovation and Validation Objectives (cont.)...... 15 Table 4 – TIRav1 figures...... 17 Table 5 – Architecture components...... 20 Table 6 – TIRav2 figures...... 25 Table 7 – Implementation plan, TIRav1 ...... 27 Table 8 – Implementation plan, TIRav2 ...... 27 Table 9 – Demo team...... 30
D309.1 Page 5 of 38 1 Executive Summary
Deliverable 11.1 provides a general overview of the Ravenna demonstration within the EU co-funded project EBSF_2. The objective of the Italian demonstration in Ravenna is the implementation of two technological solutions dealing with the following EBSF_2 key research areas: Intelligent Garage and Predictive Maintenance and IT Standard Introduction in Existing Fleets. Predictive maintenance allows the decrease of maintenance costs, breaks, spare parts usage and also the quantity of waste material; the service scheduling can be more precise and will need less spare vehicles. Analysis of oil can tell a lot about the health of an engine and residual metals can tell about parts becoming corroded and give a signal that maintenance operations are necessary before the scheduled ones. On the other hand, if the results of the oil analysis are good, the ordinary maintenance could be postponed with a reduction of maintenance cost. Predictive maintenance has to be supported by an accurate maintenance budget in order to increase service reliability. This document describes the technological innovations to be implemented and tested in Ravenna, namely “Predictive maintenance” and “Analysis of the maintenance budget” vis-à- vis the EBSF_2 Validation Objectives as defined together with the project Evaluation Team (task 2.2). The demonstration will be conducted in real operation thanks to the involvement of the public transport operator START ROMAGNA which operates public transport services in the provinces of Ravenna, Forlì-Cesena and Rimini (Italy). This document also reports on the technological solutions’ implementation plan, coherently with the EBSF_2 project master plan, as well as the technical specifications, functional and not-functional requirements of the solutions.
D11.1 Page 6 of 38 2 Introduction
The overall objective of the Italian demonstration in Ravenna is the implementation of innovative solutions under the EBSF_2 Priority Topics: - Intelligent garage and predictive maintenance. - IT standard introduction in existing fleets.
Ravenna demonstration is operated within the area served by the public transport operator START ROMAGNA, which corresponds to the provinces of Ravenna, Forlì, Cesena and Rimini, in the Emilia-Romagna region, Italy. An accurate maintenance budget plan and predictive maintenance are the basis to increase service reliability. The optimisation of the maintenance scheduling allows the decrease of maintenance costs, breaks, spare parts usage and also the quantity of waste material; the service scheduling would be more precise and will need less spare vehicles. Furthermore, like blood analysis can predict malfunctioning of our body, analysis of oil can tell a lot about the health of an engine. Residual metals can tell about parts becoming corroded and give a signal that maintenance is necessary before the scheduled one. On the other hand if the result of the oil analysis is good the ordinary maintenance could be postponed with a reduction of maintenance cost. Romagna demonstration site will implement and validate in real-life operational conditions two Technological Innovations (TI): Predictive maintenance (TIRav1) Analysis of the maintenance budget (TIRav2)
This document describes in detail the objectives of the above mentioned technological innovations, the relation with the Validation Objectives (as defined in task 2.2) and the implementation plan along the project life.
D11.1 Page 7 of 38 3 Background and context
3.1 Geographical and urban context Ravenna demonstration is operated within the area served by the public transport operator START ROMAGNA, which corresponds to the Italian provinces of Ravenna, Forlì, Cesena and Rimini, within the Emilia-Romagna region. Figure 1 shows the geographical context of the demonstration.
Figure 1 – Ravenna demonstration geographical context
The province of Forlì-Cesena has a population of 395,897 as of 2015 over an area of 2,378.4 square kilometres (918.3 sq mi), giving it a population density of 166.46 inhabitants per square kilometre. Forlì has a population of 118,255, and Cesena has a population of 96,885. It contains 30 municipalities. (source: http://www.tuttitalia.it/emilia- romagna/provincia-di-forli-cesena). The province of Ravenna has a population of 391,997 inhabitants as of 2015 over an area of 1,859.44 square kilometres (717.93 sq mi), giving it a population density of 210.81 inhabitants per square kilometre. It contains 18 municipalities. (source: http://www.tuttitalia.it/emilia-romagna/provincia-di-ravenna). The province of Rimini has a population of 335,199 inhabitants as of 2015 over an area of 864.88 square kilometres (333.93 sq mi), giving it a population density of 387.57 inhabitants per square kilometre. The city of Rimini has a population of 147,578 inhabitants. The province borders the independent state of the Republic of San Marino. There are 26 municipalities in the province. (source: http://www.tuttitalia.it/emilia-romagna/provincia-di- rimini).
3.2 Service background START ROMAGNA is the public transport company which have merged three memorable companies in transport management: AVM, ATM and TRAM SERVIZI. In 2012, the public transport operator TPER (Trasporto Passeggeri Emilia Romagna), active in the provinces of Bologna and Ferrara, has become a shareholder of START. START ROMAGNA is the only
D11.1 Page 8 of 38 public transport operator of the Romagna area and its fleet of vehicles is sorted out into the three areas of Forlì-Cesena, Ravenna and Rimini. In particular, START ROMAGNA operates the public transport service on behalf of the following provincial mobility agencies: Mete in the province of Ravenna, ATR in the province of Forlì-Cesena and Agenzia Mobilità in the province of Rimini. Moreover, START ROMAGNA owns a division, called Start Away, devoted to Bus rental for tourism. START ROMAGNA also owns and operates, on a daily basis, two ferries ("Azzurro" and "Balena") which link Marina di Ravenna and Porto Corsini via the Candiano canal. In total it counts 5 depots located in Ravenna, Forlì, Cesena and Rimini, 713 buses used for local public transport, plus school buses and buses for rental. Table 1 and Table 2 show the bus fleet composition by province, their mean age and the type of vehicles owned by START ROMAGNA. Figure 2 and 3 provide a snapshot of the buses and depots operated by START ROMAGNA.
Forlì-Cesena Rimini Ravenna TOTAL
Power Mean age Mean age Mean age Nr. Nr. Nr. Nr. (years) (years) (years)
Petrol 18 9,18 2 10,5 2 12,48 22
Diesel 253 13,91 245 14,51 52 15,36 550
Electric 7 16,2 6 5,37 13
Natural Gas 61 6,34 67 8,04 128
339 253 121 713
Table 1 – START ROMAGNA’s bus fleet
Type Number
EXTRA URBAN 196
AUXILIARY BUS 79
SUB URBAN 150
URBAN 225
FILOBUS 6
SCHOOLBUS 33
RENT BUS 24
Table 2 – Type of Buses of the fleet
D11.1 Page 9 of 38 Figure 2 – One of the garages operated by START ROMAGNA
Figure 3 – Examples of the buses operated by START ROMAGNA
Today START ROMAGNA is able to schedule the fleet’s maintenance, but no predictive maintenance is implemented. The scheduled maintenance relies on“maintenance classes” (maintenance booklets all the vehicle are categorized in) made by a check-list of maintenance operations that the buses has to execute periodically, in terms of time or kilometers. For the sake of clarity, the “maintenance class” of three methane fueled buses and three diesel fueled buses which will be used in the demonstration are reported respectively in ANNEX 1 – Maintenance Class of the methane fueled bus, and ANNEX 2 – Maintenance Class of the diesel fueled bus. Currently, START ROMAGNA schedules the maintenance through the Pluservice software Officina*. The software shows deadlines for maintenance activities of the fleet and schedule them over time through the use of the “Table of Maintenance” (Figure 4), that allows START ROMAGNA to plan in due time the maintenance.
D11.1 Page 10 of 38 Figure 4 – Maintenance scheduling
As for the budget allocated for the maintenance of the vehicle, currently START ROMAGNA calculates it according to actual data of the previous year. Figure 5 and Figure 6 show as an example two of the reports (elaborated via Business Object1) that Pluservice delivered to START ROMAGNA by analyzing the costs sustained for the fleet’s maintenance in 2015.
Figure 5 – Example of a report of the final cost balance-1
1 http://go.sap.com/solution/platform-technology/business-intelligence.html
D11.1 Page 11 of 38 Figure 6 – Example of a report of the final cost balance-2
The need for START ROMAGNA is to have a tool able to calculate the costs and plan the budget for the following year with more accuracy. This should be based on the estimated journeys (kilometers) that START ROMAGNA assigns as a target to the fleet for the following year.
* OFFICINA, powered by Pluservice, is a complete information system for managing the maintenance, information and documentation related to the vehicle fleet. This system is particularly versatile and is a tool for monitoring costs and optimizing maintenance processes. Thanks to this tool, the maintenance can be: Planned/preventive: according to the recorded and estimated distance covered by the vehicles (kilometers/hours of use), according to time deadlines or mixed deadlines (distance plus time). Corrective: by recording in details malfunction warnings originating during the use through interfaces AVL/AVM, mobile devices given to travelling personnel, web interface. Increasing the asset’s value: by carrying out maintenance intervention which can be amortized over time.
D11.1 Page 12 of 38 4 Demo objectives
The Italian demonstration in Ravenna will develop and test in real conditions: oil quality monitoring and extension of oil life with improving of machinery reliability; management of fleet predictive maintenance; maintenance budget plan and optimisation.
The implementation of the above technological developments refer to a set of specific objectives: optimisation of motor oil change in terms of km range; extending the real life of motor oil usage and related consumables; maintenance scheduling (predictive maintenance) for several engine gears, a vehicle out of service time and scheduling of vehicle according to service.
The expected impacts of the implementation planned within the Ravenna demonstration will, thus, be: reduction of maintenance costs; reduction of fleet stop and resulting progress of the PT service; reduction of repair maintenance ; reduction of the number of spare vehicle and LCC; reduction of emission due to an optimised use of lubricant and spare part; increase of retrofitting; implementation of standard interface for IT architecture.
The Technological Innovations (TI) that will be implemented in Ravenna Demo are labeled according to the definition and the coding agreed within the Task 2.2 “Definition of Validation Objectives and Test Scenario”, namely: Predictive maintenance (TIRav1) Analysis of the maintenance budget (TIRav2).
Both TIs are extensively described in in section 5 - Demo description . For each of them a set of Validation Objectives has been identified coherently with the methodology developed by the EBSF_2 Evaluation team in Task 2.2 (ref. ANNEX 3 – List of EBSF_2 Validation Objectives). Error! Reference source not found. presents the Validation Objectives related to the Technological Innovations TIRav1 and TIRav2.
D11.1 Page 13 of 38 Technological Innovation
Predictive maintenance Analysis of the maintenance budget Validation Objective (TIRav1) (TIRav2) (VO)
Main requirements to comply with the VOs
VO3 Reducing the An optimized maintenance of diesel consumption of and methane fueled buses conventional fuels guarantees a reduction in - consumption. VO5 Promoting Buses are retrofitted with the oil retrofitting programs quality sensor. - VO13 Improving Relevant regarding backoffice IT interoperability for architecture. - ground operations VO14 Improving Relevant regarding “Implementation interoperability for IT of on-board architecture” based on IT systems standards and backoffice IT - architecture. VO15 Speeding up data Relevant regarding the algorithm and The management of the maintenance budget management the software for the predictive will be improved with the implementation of maintenance (Officina). It is also algorithms and data management software. relevant for “Implementation of on- board architecture” based on IT standards and backoffice IT architecture. VO17 Minimizing operating The information gathered from the oil The analysis of the budget will allow better and maintenance quality sensor and the CAN Bus, planning of ther expenses and therefore an costs together with the algorithm that will optimization of operating and maintenance be implemented for the predictive costs. maintenance, the associated business intelligence and the correlation of data, are the basis for the minimization of the operating and maintenance costs. VO19 Speeding up Better and optimized management of maintenance the spare parts and bus stops for the operations maintenance allows to speed up the - maintenance operations. VO20 Reducing non The tool will allow to plan with more operational lifetime accuracy the bus stops in the garage - of vehicles for maintenance. VO21 Rationalizing Predictive maintenance provides parking and working information about the components areas at whose malfunction is already in place depots/workshops or will be forthcoming and therefore will allow the technical manager of the company to plan more careful - and targeted maintenance work on the vehicles. This optimizes the use of the parking and working areas reserved for maintenance. Table 3 – Technological Innovation and Validation Objectives
D11.1 Page 14 of 38 Technological Innovation
Predictive maintenance Analysis of the maintenance budget Validation Objective (TIRav1) (TIRav2) (VO)
Main requirements to comply with the VOs
VO22 Reducing noise and Noise and air emissions are linked to air emissions the performance of the predictive - maintenance. VO24 Increasing reliability Primary objective of predictive maintenance is that of increasing the reliability of the vehicle and its components trying to prevent malfunction and broken parts. This - will reduce bus-stops and therefore increase the hours of use of the vehicle. VO28 Increasing economic Predictive maintenance will increase The maintenance budget analysis increases efficiency the economic efficiency because it economic efficiency because it allows to allows to reduce non-operational life schedule maintenance operations in a more time of the vehicle and the related precise and accurate way aiming at savings costs. management costs. VO30 Making the debt Predictive maintenance will increase The maintenance budget analysis increases service coverage the economic efficiency because it economic efficiency because it allows to more affordable allows to reduce non-operational life schedule maintenance operations in a more time of the vehicle and the related precise and accurate way aiming at savings costs. management costs. Table 4 – Technological Innovation and Validation Objectives (cont.)
D11.1 Page 15 of 38 5 Demo description
The Ravenna demonstration Team (Pluservice, MEL-System, START ROMAGNA, UNIROMA1, UITP representing ITXPT) is committed to implement and test 2 technological innovations: TIRav1 - Predictive maintenance A maintenance software to analyse data coming from lubricants’ quality sensors to assess the oil quality and therefore avoid potential breakdowns by replacing spare parts in advance. The analysis will also make possible to understand which substances/problems in general influenced or caused the bad quality of the oil.
TIRav2 - Analysis of the maintenance budget A software to assess costs afforded by public transport management, according to information on the average distance covered by vehicles through an accurate analysis of the cost items.
5.1 Predictive maintenance As described in section 3, in the present scenario a routine programmed maintenance service is performed by the operator START ROMAGNA without analyzing the oil quality and without having the possibility of forecasting imminent breakdowns. The implementation of the Predictive Maintenance TI has the main following objectives: Provide real time information on the quality of the engine oil thanks to an oil quality sensor installed on all the buses involved in the demo. Provide the time trend of the qualitative attributes of the engine oil (conductivity, temperature, amount of water, etc ...) through online reading of the values "Quality Index" assessed by the oil quality sensor. This will allow detecting accurately the oil degradation and predicting the right timing of replacement. At the same time the system will be able to report any unexpected contamination avoiding serious mechanical problems to the vehilces. Elaborate on remaining life of specific engine components thanks to periodic laboratory tests on oil samples to be compared with the values detected by the sensor. Chemical analysis of the oil will be carried out in parallel through the MEL-System’s laboratory and through the independent laboratory OELCHECK based in Brannenburg. Extend the life of the engine oil through the use of a particular filter (mounted on 2 of the 3 diesel vehicles) able to clean up the lubricant from the dross present in it. Allow significant cost savings due to the extension of the lubricant’s lifetime. Allow a significant reduction of CO2 emissions from the vehicles thanks to better performances of the engines.
Starting from the existing software “Officina” by Pluservice, the predictive maintenance management software will have the functionality of forecasting the attitude of vehicles’ components thanks to the analysis of historic data related to motor oil sampling. The maintenance software will be able to analyze the data according to the oil quality and
D11.1 Page 16 of 38 therefore it will be able to predict potential breakdowns and avoid them by replacing spare parts in advance. Moreover it will be able to understand which substances/problems in general influenced or caused the bad quality of the oil. The implementation of the Technological Innovation TIRav1 will be done by equipping six vehicles with an on-board system able to connect to the FMS/CAN BUS and to the oil quality sensor and send the information to an AVM back-office system.Two vehicles (2 diesel fueled) out of six will be equipped also with a purifier in order to test over time the action of the filter itself on the lubricant quality in comparison with the two vehicles without the filter. Since the engine oil may contain zinc, iron and water particles it is necessary to provide the maintenance management software with the functionality of forecasting the behaviour of vehicles’ components, thanks to the analysis of historic data related to motor oil sampling. Additional information on other sensors (for instance, engine temperature, rpm, coolant level, HVAC operation, etc.) will be additionally obtained from the FMS/CANBUS.
As a result, it is expected that on the 2 vehicles equipped with the filter, the frequency of oil changes will be extended, as well as the respective servicing and related operations. This will imply a decrease in stopped vehicles for the programmed maintenance with a subsequent saving on materials and manpower dedicated to such activities. In the predictive maintenance software, the management of oil quality data (deriving from the use of the sensor and the data entry on the analysis of the lubricant samples) will change the approach to the programmed maintenance by START ROMAGNA staff. Taking into account a detailed analysis of data above mentioned, START ROMAGNA has to change the periodicity and frequency of servicing, optimizing the operations according to the vehicle model and the service performed. In order to perform the oil test, also the oil supplier will be involved since it is needed to analyse oil parameters related to previous experiences. The sensors record a specific value and its trend (the derivative) in order to sound the alarm in case of need.
The most suitable vehicles for the test are those with a frequency of changing the motor oil every 20.000 Km for diesel fuelled vehicles and 30.000 Km for methane fuelled vehicles.
As a summary, Table 5 reports the main figures of the Ravenna demonstration for what concerns the Technical Innovation TIRav1-Predictive maintenance.
Lines Staff involved Vehicles involved Area involved
3 natural gas powered buses 13 urban 184 drivers Ravenna Brand: BREDA Flat urban area lines 8 mechanics Model: M 231/GNC4 CU
3 diesel powered buses 14 urban 305 drivers Forlì lines Brand: IRISBUS Flat urban area 12 mechanics Model: 399EL82 (My Way)
Table 5 – TIRav1 figures
D11.1 Page 17 of 38 In order to have a good assessment of results, 12 months are required to perform the tests. In fact, considering the average distances covered by such vehicles, one year is the most suitable period of time to highlight the advantages of using the oil filter. Data collection is realized via the On-Board system: the oil quality sensor is connected to a telematics on-board device that gather data from the sensor, manage the thresholds through an embedded firmware and send data to the AVM back-end system and thus to the predictive maintenance software.
A complementary oil sampling is performed by START ROMAGNA who will send the oil sample to MEL-System. The offline oil analysis is performed by MEL-System supported by the independent laboratory OELCHECK in Brannenburg. MEL-System will send the information to the maintenance software in order to give the possibility of storing the sampling data. The purpose is to accumulate sampling data over time and store into the database statistics that can give hints for the predictive maintenance. This result will be reached also by matching the value of the sensor with the oil analysis. Based on the records of analysis, the algorithm implemented in the predictive maintenance software can detect the evolution status of components, predict a result and give information to START ROMAGNA on the potential failures after that a reference value has exceeded the limit.
The steps to follow to perform an effective data the analysis are: - Have a real time sensor value; - Have a controlled sampling: indication that it is the time for taking the sample; - Oil sampling by the operator; - Oil analysis by MEL reported in a file; - Association of values with the status of the vehicle.
At the moment of sampling, the operator will push a button on the local panel of the oil quality sensor. The event is sent to the on-board computer with the associated kilometres and then sent to the AVM/Maintenance SW. The On-Board computer can gather data from the on-board sensors with a configurable frequency. The right frequency will be tuned during the implementation phase to optimize the process. It is expected a frequency of the order of minutes for what concern the Oil sensor and CAN-Bus values. The oil analysis sample is of the order of months.
5.1.1 Architecture The high level architecture identified to implement the Technological Innovation TIRav1 is shown in Figure 7.
D11.1 Page 18 of 38 Figure 7 – High level architecture
Table 6 describes the components of the architecture and the corresponding providers.
Description Provider
Oil Quality Sensor Sensor for the measurement of the oil quality. MEL-System
Sensor Controller Electronic controller of the sensor. MEL-System
Garage Panel HMI for the manual acquisition of the oil sample. MEL-System
On-board computer able to interface peripheral devices (e.g. oil sensor) and the FMS/CAN. It Telematics device TBD includes GPS/GPRS modules for localisation and communication with the back-office system.
The Fleet Management Systems Interface (FMS) is FMS-Gateway a standard interface to vehicle data of commercial START vehicles (http://www.fms-standard.com/).
Automatic Vehicle Monitoring. This system collects data from the Telematics device and provides AVM Pluservice functionality of fleet monitoring, diagnostic, human interface.
Predictive Maintenance It is the software that elaborates real time and Pluservice
D11.1 Page 19 of 38 historical data collected from the AVM/Telematics device in order to schedule the maintenance in a predictive manner.
Web-based tool for the management of the Operator web interface Pluservice predictive maintenance.
Table 6 – Architecture components
Although the architecture is defined, the best supplier of the telematics device has to be assigned. After an analysis of the market offers, a list of potential supplier has been identified and deeply analysed: ACTIA (http://www.actia.com/) Metatronix/Digigroup (http://www.digigroupinformatica.it) DMD Computers (http://www.dmd.it/) Digitax (http://www.digitax.com/) Teltonika (www.teltonika.it) Connet (http://www.connetweb.com/) Nexcom (http://www.nexcom.com/) Owasys (http://www.owasys.com/)
A set of mandatory requirements for the selection of the telematics unit has been identified: Compliant to IT Standards EN13149 parts 7/8/9 Ability to connect to and manage FMS (Fleet Management System)2 data Ability to connect to and manage the Oil Quality Sensor Ability to send real time data to the AVM system (Automatic Vehicle Monitoring)
The selection process is planned to be completed in M8, according to the implementation plan reported in section 6.
As mentioned, the IT Standards EN13149 parts 7/8/9 will be adopted for the design and the implementation of the IT architecture of the Technological Innovation TIRav1. This will ensure the improvement of interoperability of the involved IT systems both for the on-board architecture and the back-office IT architecture.
2 http://www.fms-standard.com/Bus/index.htm
D11.1 Page 20 of 38 5.1.2 Oil Quality Sensor The Oil quality sensor is a core element for monitoring and extending oil system life. It will be installed both in the diesel fuelled and methane fuelled buses. This device measures the capacity and conductivity of the oil, which once combined can provide the value of the permittivity. Thus it returns a value 60 times more sensitive to the variation of the quality of the oil compared to the dielectrics sensors. Thanks to this sensitivity, the oil quality sensor can therefore detect in advance the deterioration of the oil, allowing a timely planning of any maintenance. Figure 8 shows the interaction of the oil flow with the sensor, the local controller and the external telematics device (FMS and GPRS communication).
Figure 8 – Oil quality sensor and oil flow
Figure 9 and Figure 10 show the oil quality sensor to be installed respectively on diesel and methan fuelled buses. In addition to the oil sensor, the diesel fueled buses will be equipped with an oil filter.
Figure 9 – Oil quality sensor installed in diesel fueled Bus
D11.1 Page 21 of 38 Figure 10 – Oil quality sensor installed in methane fueled Bus
It's very beneficial for the bus engine to remove very small particles from the oil. This conclusion has been made by MacPherson who discovered the importance of small particles. The MacPherson Graph (see Figure 11) is based on accelerated test of 10 roller bearings. The lubrificating oil used was contaminated with dirt form gearbox. The McPherson Graph indicates that the real component life time improvement is achieved when filtering below 10 microns. We can estimate that 90% of all particles in gear oil are smaller that 10 microns i.e., a 10 microns filter will leave 90% of the particles in the oil, only offering a limited filtration. Moreover the dynamic tolerance ion, for example a wind turbine bearing is between 1-5 microns, which indicates that only particles smaller than 5 microns are able to enter and damage the bearings.
Figure 11 – Fine oil filtration, Macpherson curve
D11.1 Page 22 of 38 5.2 Analysis of maintenance budget In the present scenario START ROMAGNA uses historic data to plan the maintenance budget for the following year; no prediction on maintenance costs is performed. On the contrary thanks to the new software application that will be developed within EBFS_2 for the analysis of maintenance budget, a forecast of the distances covered by every vehicle will be available according to the type of services planned for the next year (suspension or creation of new lines) and planning the correct amount of kilometers to respect the budget. According to this, the costs for the planned, repairing, extraordinary and accidents maintenance will be known as well as the comparison of the budget with final data, administrative and operational costs on vehicles (i.e. fuel, lubricants).
The main objectives of this implementation are: Provide a tool to assess accurately the future costs for the management and operation of the fleet. Provide a tool to assess precisely the difference between the projected costs for a given period of time compared to the costs actually incurred in the same period.
Therefore the scope is to implement a software application capable of analyzing the future costs for the management and use of a fleet.In particular the following aspects will be taken into consideration: - Budget for planned maintenance o Calculation of the annual journeys estimated for each vehicle. In the absence of actual information, the distance covered by the vehicle during the previous year will be taken into account. o Maintenances for each vehicle during the period chosen for the budget (number of occurrences, hours of maintenance estimated for the work, necessary materials associated with each scheduled maintenance activity) will be calculated according to the frequency of each scheduled maintenance. o The system will be able to estimate the kilometers and the date for each task and then we will be able to project the occurrences of the scheduled maintenance for each vehicle for the period covered by the budget analysis.
- Budget for repairing maintenance: o A historical period will be considered to calculate the occurrence of faults on each vehicle. The period will be configurable (3 years, 4 years, 5 years and so on). o In this period the occurrences of each repairing maintenance for each vehicle will be taken into account. For each occurrence, life-km of the vehicle and the date of the repair execution will be recorded. These data will be averaged according to the model of the vehicle: in this way, for each model of vehicle and for each repairing activity an average periodicity of execution (km and days) will be derived. In parallel with the calculation of the repairing activities, all the materials used for not programmed working will be also taken into consideration. o In this way the repairing maintenance of each vehicle will be linked to the budget analysis in the considered period.
D11.1 Page 23 of 38 - Budget for extraordinary maintenance o "Extraordinary maintenance" means the set of activities that does not necessarily have been included in the maintenance plan of the vehicle. o The program will allow, for each vehicle included in the budget analysis, the manual entry of extraordinary activities, indicating the required working hours and the cost and type of execution (internal, external).
- Budget for maintenance resulted from accidents o The system calculates, for the year preceding the reference year of the budget, the costs for activities relating to accidents (manpower and materials). o The system calculates, for each month of the year preceding the budget reference, the cost for the activities relating to accidents by obtaining the cost per kilometer per month according to the distance covered by the fleet. o The monthly cost for the activities relating to accidents will be linked to the period of the budget according to established journeys.
- Budget for the use of fuels and lubricants o Based on the current consumption of the vehicle, the quantity of fuel the vehicle will consume is calculated in the period of the budget analysis, on the basis of estimated Km.
- Budget for administrative deadlines/contracts o Project administrative deadlines and contracts to the analysis of the budget for the selected period.
- Comparability of the budget with the actual figures o The application will include the visual comparison of planned budget figures with actual figures for the same period in order to allow the PT Operator (START) to make corrections on cost management.
The Analysis of the maintenance budget (TIRav2) will involve the whole START’s fleet. Table 7 reports the figures in terms of lines, staff and vehicles involved in the demonstration. The goal is to have a clear picture of all costs afforded by the management board of a public transport operator and have information on the average distance covered by vehicles through an accurate analysis of the cost items. It is necessary to understand also where managers should act in order to reduce negative features while b keeping unvaried the service, highlighting how much has been saved over time by the optimization of resources involved in the vehicle maintenance department (human resources, external suppliers, etc.). The goal is reached when START ROMAGNA will be able to provide the same service to passengers but with less expenses. Cost savings concerning the maintenance are estimated to be about 15%.
D11.1 Page 24 of 38 TIRav2 Lines involved Staff involved Vehicles involved
Ravenna 13 Urban lines 723 vehicles in total, of which: Forlì 14 Urban lines 194 Interurban 8 test plates 82 auxiliaries Cesena 17 Urban lines 150 Suburban 4 units (managing the 222 Urban whole fleet) 6 trolleybus Cesenatico 3 Urban lines 3 trailers 33 school buses Rimini 62 urban lines 24 for rental
Suburban: 6 Extra-urban Extraurban and consortium: 61
Table 7 – TIRav2 figures
Currently in START ROMAGNA, the maintenance budget for the following year is decided according to the final data at the end of the previous year (retrieved from the Officina software) by increasing or decreasing them in proportion with the expected Km in comparison with those travelled the previous year. The technical department reports the budget for maintenances. Once the implementation of TIRav2 will be completed, the forecasts of expenses will be calculated in a much more detailed way because the system will indicate the precise activities to perform with respective amounts and number of required hours, the list of spare parts to use, potential “extraordinary” maintenance operations that the company may perform, etc. To be able to perform as much precise calculations as possible, Start Romagna will have to indicate the expected travelling distances for every vehicle according to the service performed and the total budget per Km agreed with the Regional Public Administration. Estimated data will be compared with the final ones concerning the same period.
D11.1 Page 25 of 38 6 Demo implementation plan
6.1 Description Ravenna Demo implementation plan follows the general scheduling and milestones of the project: M6 – Description of the demo and implementation plan delivered (D11.1). M18 – Preparation and execution of the demo – INTERMEDIATE RELEASE delivered (D11.2) M24 – Demonstration Started and Deliverable “Preparation and execution of the demo – FINAL RELEASE” delivered (D11.2) M30 – Completion of data collection and analysis of data. Deliverable “Demonstration results” delivered (D11.3)
In order to have a good assessment of results in the Technological Innovation dealing with Predictive maintenance, 8 months are required to perform the tests and collect data. For this reason, the plan is to complete the development and the integration in site of the IT architecture at M16 (August 2016), in order to start the operation phase and collection of data at M17 (September 2016) for 8 months. Data with NO-EBSF_2 situation and EBSF_2 situation will be collected in parallel. The implementation of the predictive maintenance software will be performed in two phases: the first one by M12 is to allow the import of data gathered for the oil sensor and for the storage of the results coming from the laboratory analysis of the sampled oil.
Table 8 reports the implementation plan of the Predictive maintenance Technological Innovation.
Activities Start End
TIRav1-Predictive maintenance M1 M24
Analysis of the predictive maintenance scenario and functionality. M4 M5
Design of the predictive maintenance functionality in the sw Officina by M6 M10 Pluservice Development and verification of the predicitive maintenance software-phase M10 M14 1 (visualisation of oil real time data and samples) Development and verification of the predicitive maintenance software-phase M11 M15 2 (predictive maintenance functionality).
IT standard EN13149 part 7/8/9 M1 M13
Design of the IT architecture M1 M6
D11.1 Page 26 of 38 Selection of the On-Board computer M4 M8
Development of the IT standard specifications (On-Board and Back-Office) M4 M13
Development of the IT standard interface between AVM back-office and M4 M13 Pluservice Officina. Procurement and installation of OnBoard devices in one Bus (Computer, M11 M13 Sensor&Filter)
Installation of the OnBoard devices (Computers, Sensors&Filters) M14 M15
On field verification (OnBoard and Back Office)-Implementation&Integration M15 M16 test, phase 1 On field verification (OnBoard and Back Office)-Implementation&Integration M15 M17 test, phase 2
Go Live (Start of the Operation period) M17
Operational period and data collection M17 M24
Table 8 – Implementation plan, TIRav1
The Technological Innovation Analysis of the maintenance budget will not affect the implementation of TIRav1 and thus it can be implemented in parallel. Table 9 reports the implementation plan of the analysis of the maintenance budget Technological Innovation.
Activities Start End
TIRav2-Analysis of the maintenance budget M1 M24
Analysis of the maintenance budget scenario and functionality. M1 M5
Design of maintenance budget software M5 M9
Development of maintenance budget software M10 M14
On field verification-Implementation&Integration test M15 M17
Go Live (Start of the Operation period) M18 M18
Operational period and data collection M18 M24
Table 9 – Implementation plan, TIRav2
D11.1 Page 27 of 38 6.2 Gantt Chart
The following figures show the Gantt chart representing the implementation plan of the Ravenna demo. Figure 12 is the overall Gantt, Figure 13 and Figure 14 focus respectively on the activities related to the TIRav1 and the TIRav2.
Figure 12 – Overall Gantt chart
Figure 13 – Gantt chart, zoom on TIRav1 implementation plan
D11.1 Page 28 of 38 Figure 14 – Gantt chart, zoom on TIRav2 implementation plan
6.3 Demo team The organizations and the responsible persons in charge of the different activities in the Ravenna demo site are shown in Table 10.
Demo Partner Role Contact person
Coordinator and leader of the EBSF_2 Ravenna demo. Provider and developer of the Predictive maintenance management software (TIRav1). Provider and developer of the Guido Di Pasquale Analysis of the budget [email protected] maintenance software Pluservice (TIRav2). Contribution to the design of Enrico Petracci the IT architecture. [email protected] Contribution to the development of the IT system. Importing and storing data on analysis inside the Maintenance SW. Data collection and support to the evaluation.
Public Transport Operator, provider of the Bus fleet Oil Sampling Claudio Zuccherelli, START ROMAGNA User of the predictive maintenance software [email protected] User of the analysis of the maintenance budget Support to the integration and
D11.1 Page 29 of 38 the implementation of the Technological Innovation on the Buses. Support to collection of data and evaluation.
Provider of the Oil Quality Sensor Provider of the Oil filter Laboratory analysis of the Oil Contribution to the design of Luigi Brambilla, MEL-System the IT architecture. l.brambilla @mel-systems.it Contribution to the development of the IT system. Data collection and support to the evaluation.
Antonio Musso [email protected] Local evaluator Uniroma1 Link to WP2 Maria Vittoria Corazza [email protected]
Support to the implementation of the priority topic : IT Michele Tozzi UITP standard introduction in [email protected] existing fleets
Support to the implementation Emmanuel de Verdalle of the priority topic : IT Digimobee standard introduction in emmanuel.de- existing fleets [email protected]
Table 10 – Demo team
D11.1 Page 30 of 38 7 Partner Contribution
Company Sections Description of the partner contribution Pluservice 1; 2; 4; 5; 6; Editor of the whole document. 8; 9 Definition of the demo objectives, description of the Technological Innovations, IT architecture and Gantt. START 3; 5.1; 5.2; 6 Context and background. Support to the definition of the demo objectives and planning. MEL-Systems 4; 5.1.1; Description of the Oil sensor and filter, interaction with the ITarchitecture and Gantt. 5.1.2; 0 Support to the definition of the demo objectives. UNIROMA1 1 to 6 General revision to check consistency with Ravenna Demo description in Del. 2,2 UITP Whole Document quality check document
D11.1 Page 31 of 38 8 CONCLUSIONS
Ravenna test site will demonstrate the potential of the EBSF_2 research priority topics “Intelligent garage and predictive maintenance” together with “IT standards introduction in existing fleets” in improving the efficiency of bus fleets. The demonstration will be conducted in real-life operational conditions in collaboration with the public transport operator START ROMAGNA which serves the inhabitants of the provinces of Ravenna, Forlì-Cesena and Rimini. The Technological Innovations to be implemented, namely “Predictive Maintenance” and “Analysis of the maintenance budget”, implies the development of the following solutions or tools:
IT interfaces for real time oil monitoring and data acquisition through vehicle FMS, development of communication protocol with the AVMs and between AVMs and the existing software for management of fleet maintenance according to EN13149 parts 7/8/9 standard. Predictive maintenance software that will be based on historic data, real time data collected via the AVMs. Maintenance budget plan software that will include planned maintenance cost, repair maintenance cost, predictive maintenance data, etc.
The above developments are related to a set of specific objectives: optimising the motor oil change in terms of km range, extending the real life of motor oil usage and related consumables, maintenance scheduling (predictive maintenance) for several engine gears, a vehicle out of service time and scheduling of vehicle according to service.
The analysis of the user (PT operator) needs has been conducted in the first six month of the project life, resulting in a set of requirements for the two Technological Innovations, as reported in this deliverable. The Ravenna demo site partners have also defined a detailed implementation plan reported in section 6. When the demonstration will be running, performance data to evaluate the degree of achievement of the results such as quality of the communication between the on-board oil sensors devices and AVMs, or information related to maintenance cost etc. will be collected for a minimum period of 8 months, in order to have a reasonable period of time to have significant measures. Data will ‘feed’ a set of Key Performance Indicators (KPIs) which will be used to achieve a ‘before/during’ comparison, run by Sapienza University of Rome, as local evaluator, coherently with the methodology developed by the project Evaluation Team. KPIs assessment will allow the evaluation of the technological innovations both at local and cross- site level. KPIs belong to the selected priority topics and categories in the maintenance field (costs, operational performance, etc.), according to the method and directions provided by the Global Evaluation WP. The local evaluator together with the demo team will ensure suitability of the testing process, consistency of data collected and relevance of results.
D11.1 Page 32 of 38 9 ANNEXES
9.1 ANNEX 1 – Maintenance Class of the methane fueled bus The maintenance class specifications of the 3 methane vehicles selected for the project are detailed in the following: Type (K=km; Working Frequency D=Days) Methane engine revision 1000000 K Automatic gear ZF revision 900000 K
Elipress - Integrity Control / Diagnosis / Tests 55000 K Elipress - Replacing front elipress 180000 K Elipress - Replacing rear elipress 60000 K Lower arms - replacement heads and bearings 380000 K Shock absorbers - Replacing rear shocks 550000 K Help - Steering oil change and filter 240000 K Help - Steering Replacing pipes high-pressure pump 700000 K Intake ducts - Cleaning the air filter 10000 K Intake ducts - Air filter replacement 70000 K Transmission shaft - Replacement 800000 K Cooling - Dry cooler with a pressure washer 365 D Cooling - Liquid Density Control 365 D
Cooling - Replacing hoses wheel 630000 K Feeding methane - Loading valve 1095 D Methane power - Replace the proportional valve / Stepper Motor / DEFCO 120000 K
Preheater - Replacing pressure regulator 2920 D Preheater - Replace water pump 300000 K Axle - Revision independent suspension 310000 K
Bridge - Oil change 120000 K Stabilizer - Replacing rear bush 500000 K Automatic Transmission - Change oil and filter 120000 K Automatic Transmission - Registration / replacement micro intervention Slow load and accelerator 600000 K Engine - diagnostics tester / Control / Checks 60000 K Engine - Replacement filter vent Bloow By 280000 K Engine - Free / Sensor Throttle body 50000 K Engine - Replacement bushings 700000 K Engine - Registration Punterie 140000 K
Turbocharger - Turbocharger Replacement 550000 K Engine - Replacement Coils 220000 K
D11.1 Page 33 of 38 Engine - Replacement cable / connection candles 90000 K Engine - Change spark 30000 K Engine - Replacing injectors METHANE 190000 K Engine - Replacing oil filters 30000 K Engine - Oil change 60000 K Engine - Replacing Water Pump Engine 400000 K Engine - Replacing water pipe air compressor and CNG reducers 240000 K Engine - Replacing Thermostat Engine 400000 K Engine - Change engine oil and filter plant idroventola 240000 K Climate - Changing belt A / C 80000 K Climate - Changing bearings and shock cords A / C 130000 K Engine - Changing belt alternator 80000 K Engine - Replacing the bearings and alternator belt tensioner 130000 K Disable rump - Greasing 50000 K Air conditioning - Replacing evaporator blowers 4200 D Alternator - Alternator Replacement 1 260000 K Alternator - Alternator Repair 1 140000 K
Alternator - Alternator Replacing 2 260000 K Alternator - Alternator Repair 2 140000 K Starter Motor - Replacement 515000 K
Validation - Stimer noun VPE 365 D Air Compressor - Air Compressor Replacement 500000 K Air Compressor - Replacement flexible compressor 250000 K
Pneumatic components - Replacement Repair Pulls, valves, graders and height. 650000 K Pneumatic components - Replacement / Cleaning the air filter suspension 200000 K Pneumatic components - Cleaning / Sostiutzione Water Separator 120000 K
Components Tyres - Check water separator 40000 K Pneumatic components - Replacement dryer 240000 K Pneumatic components - Replacement filter dryer and verify proper operation dryer 120000 K
Pneumatic components - Replacing brake hoses post 460000 K Pneumatic components - Replacement pipes front brakes and suspension 460000 K Pneumatic components - Replacement lessibile charging circuit wheel 660000 K
Scheduled maintenance AP01 - MECHANICAL 10000 K Scheduled maintenance AP01 - ELECTRICIANS 10000 K Scheduled maintenance AP02 - MECHANICAL 20000 K
Scheduled maintenance AP02 - ELECTRICIANS 20000 K Scheduled maintenance AP03 - MECHANICAL 40000 K Scheduled maintenance AP03 - ELECTRICIANS 40000 K
Scheduled maintenance AP04 - MECHANICAL 80000 K Scheduled maintenance AP04 - ELECTRICIANS 80000 K Scheduled maintenance AP05 - MECHANICAL 120000 K
D11.1 Page 34 of 38 Scheduled maintenance AP05 - ELECTRICIANS 120000 K Scheduled maintenance AP06 - MECHANICAL 160000 K Scheduled maintenance AP06 - ELECTRICIANS 160000 K Scheduled maintenance AP07 - MECHANICAL 200000 K Scheduled maintenance AP07 - ELECTRICIANS 200000 K Scheduled maintenance AP08 - MECHANICAL 240000 K Scheduled maintenance AP08 - ELECTRICIANS 240000 K Heating control preseason 730 D Control preseason Air 730 D Check preseason Heating 365 D Check preseason Air 365 D cleaning Statements 10000 K cleaning Fund 20000 K Control of the parking area 5000 K Wash the roof with a sponge and cloth 365 D
9.2 ANNEX 2 – Maintenance Class of the diesel fueled bus The maintenance class specifications of the 3 diesel fueled vehicles selected for the project are detailed in the following: Type (K=km; Working Frequency D=Days) COUPON 20,000 KM - POG R19 20000 K COUPON 40,000 KM - POG R19 40000 K COUPON 80.000 KM - POGR19 80000 K
COUPON 160,000 KM - POGR19 160000 K COUPON 320,000 KM - POGR19 320000 K COUPON 640,000 KM - POGR19 640000 K Check preseason Heating 365 D Shock absorbers - Replacing front shocks 320000 K Shock absorbers - Replacing rear shocks 320000 K
Help - Steering oil change and filter 320000 K Intake ducts - Air filter replacement 40000 K Bridge - Oil change 160000 K
Automatic Transmission - Change oil and filter 40000 K Engine - Replacement filter vent Bloow By 40000 K Engine - Replacement bushings 320000 K
Engine - Registration tappet 160000 K Turbocharger - Turbocharger Replacement 320000 K Turbocharger - Replacement air filter turbocharger 80000 K Engine - Oil change 40000 K
D11.1 Page 35 of 38 Cooling / Heating - sanitized clean or replace filters recirculated air 90 D Alternator - Alternator Replacement 1 160000 K Alternator - Alternator Replacing 2 160000 K Starter Motor - Replacement 160000 K njection - Revision / Replacing injectors DIESEL 320000 K Injection - Injection Cleaning 80000 K Air Compressor - Air Compressor Replacement 320000 K Pneumatic components - Replacement dryer 160000 K Pneumatic components - Replacement filter dryer and verify proper operation dryer 80000 K Control preseason Air 730 D Check preseason Air 365 D
9.3 ANNEX 3 – List of EBSF_2 Validation Objectives As defined in Task 2.2, Validation Objectives (VOs) in EBSF_2 are meant to establish by objective evidence whether the TI implementation process and the TI itself met the expectations which led to include it in EBSF_2 project as a demonstrators. Such VOs pertain to different areas of assessment (from operations, to economy, safety, energy, environment and perception), all consistent with the mandate to assess the possibility to “increase attractiveness and improve the image of bus systems within a context of efficiency and sustainability concerns”.
The list of EBSF_2 VOs (38), which gave rise to the selection for Ravenna (see Table 3), is reported as follows: VO1 Improving the overall energy efficiency of fleets VO2 Improving the overall energy efficiency of specific components (HVAC) VO3 Reducing the consumption of conventional fuels or electric energy VO4 Increasing the uptake of fully electric and hybrid options VO5 Promoting retrofitting programs VO6 Making driving safer VO7 Making driving practice more environmentally conscious VO8 Increasing capacity VO9 Speeding up boarding/alighting operations VO10 Increasing accessibility for all VO11 Speeding up coupling/decoupling operations VO12 Reducing travel time VO13 Improving interoperability for ground operations VO14 Improving interoperability for IT systems VO15 Speeding up data management VO16 Reducing staff workload VO17 Minimizing operating and maintenance costs VO18 Improving on board travel comfort
D11.1 Page 36 of 38 VO19 Speeding up maintenance operations VO20 Reducing non-operational lifetime of vehicles VO21 Rationalizing parking and working areas at depots/workshops VO22 Reducing noise and air emissions VO23 Increasing attractiveness of the service VO24 Increasing reliability VO25 Increasing passengers’ perceived quality of service VO26 Increasing perceived importance of technology among the passengers VO27 Increasing passengers’ safety VO28 Increasing economic efficiency VO29 Increasing demand VO30 Making the debt service coverage more affordable VO31 Improving passengers’ satisfaction VO32 Improving modularity VO33 Improving urban interface with the bus VO34 Improving staff qualification VO35 Improvement of auxiliaries management VO36 Making the motion of the bus autonomous VO37 Getting the local authorities positively involved in bus terminals VO38 Improving the bus terminals management process
D11.1 Page 37 of 38 End of the Document
D11.1 Page 38 of 38