This page has only limited features, please log in for full access.
J. Torres Farinha works at the Polytechnic Institute of Coimbra, and does research at the CEMMPRE, University of Coimbra, Portugal.
Knowledge-based approaches are useful alternatives to predict the Failure Probability (FP) coping with the insufficient data, process integrity, and complexity issue in manufacturing systems. This study proposes a Fault Tree Analysis (FTA) approach as proactive knowledge-based technique to estimate the FP based maintenance planning with subjective information from domain experts. However, the classical-FTA still suffers from uncertainty and static structure limitations which poses a substantial dilemma in predicting FP. To deal with the uncertainty issues, a Fuzzy-FTA (FFTA) model was developed by statistical analysing the effective attributes such as experts' trait impacts, scales variation and, assorted membership and defuzzification functions. Besides, a Bayesian Network (BN) theory was conducted to overcome the static limitation of classical-FTA. The results of FFTA model revealed that the changes in decision attributes were not statistically significant on FP variation while BN model considering conditional rules to reflect the dynamic relationship between events had more impact on predicting FP. After all, the integrated FFTA-BN model was used in the optimization model to find the optimal maintenance intervals according to estimated FP and the total expected cost. As a practical example, the proposed model was implemented in a semi-automatic filling system in an automotive production line. The outcomes could be useful for upgrading the availability and safety of complex equipment in manufacturing systems.
Hamzeh Soltanali; Mehdi Khojastehpour; José Torres Farinha. An Integrated Fuzzy Fault Tree Model With Bayesian Network-based Maintenance Optimization of Complex Equipment in Automotive Manufacturing. 2021, 1 .
AMA StyleHamzeh Soltanali, Mehdi Khojastehpour, José Torres Farinha. An Integrated Fuzzy Fault Tree Model With Bayesian Network-based Maintenance Optimization of Complex Equipment in Automotive Manufacturing. . 2021; ():1.
Chicago/Turabian StyleHamzeh Soltanali; Mehdi Khojastehpour; José Torres Farinha. 2021. "An Integrated Fuzzy Fault Tree Model With Bayesian Network-based Maintenance Optimization of Complex Equipment in Automotive Manufacturing." , no. : 1.
The availability maximization is a goal for any organization because the equipment downtime implies high non-production costs and, additionally, the abnormal stopping and restarting usually imply loss of product’s quality. In this way, a method for predicting the equipment’s health state is vital to maintain the production flow as well as to plan maintenance intervention strategies. This paper presents a maintenance prediction approach based on sensing data managed by Hidden Markov Models (HMM). To do so, a diagnosis of drying presses in a pulp industry is used as case study, which is done based on data collected every minute for three years and ten months. This paper presents an approach to manage a multivariate analysis, in this case merging the values of sensors, and optimizing the observable states to insert into a HMM model, which permits to identify three hidden states that characterize the equipment’s health state: “Proper Function”, “Alert state”, and “Equipment Failure”. The research described in this paper demonstrates how an equipment health diagnosis can be made using the HMM, through the collection of observations from various sensors, without information of machine failures occurrences. The approach developed demonstrated to be robust, even the complexity of the system, having the potential to be generalized to any other type of equipment.
Alexandre Martins; Inácio Fonseca; José Torres Farinha; João Reis; António J. Marques Cardoso. Maintenance Prediction through Sensing Using Hidden Markov Models—A Case Study. Applied Sciences 2021, 11, 7685 .
AMA StyleAlexandre Martins, Inácio Fonseca, José Torres Farinha, João Reis, António J. Marques Cardoso. Maintenance Prediction through Sensing Using Hidden Markov Models—A Case Study. Applied Sciences. 2021; 11 (16):7685.
Chicago/Turabian StyleAlexandre Martins; Inácio Fonseca; José Torres Farinha; João Reis; António J. Marques Cardoso. 2021. "Maintenance Prediction through Sensing Using Hidden Markov Models—A Case Study." Applied Sciences 11, no. 16: 7685.
Predictive maintenance is very important in industrial plants to support decisions aiming to maximize maintenance investments and equipment’s availability. This paper presents predictive models based on long short-term memory neural networks, applied to a dataset of sensor readings. The aim is to forecast future equipment statuses based on data from an industrial paper press. The datasets contain data from a three-year period. Data are pre-processed and the neural networks are optimized to minimize prediction errors. The results show that it is possible to predict future behavior up to one month in advance with reasonable confidence. Based on these results, it is possible to anticipate and optimize maintenance decisions, as well as continue research to improve the reliability of the model.
Balduíno Mateus; Mateus Mendes; José Farinha; António Cardoso. Anticipating Future Behavior of an Industrial Press Using LSTM Networks. Applied Sciences 2021, 11, 6101 .
AMA StyleBalduíno Mateus, Mateus Mendes, José Farinha, António Cardoso. Anticipating Future Behavior of an Industrial Press Using LSTM Networks. Applied Sciences. 2021; 11 (13):6101.
Chicago/Turabian StyleBalduíno Mateus; Mateus Mendes; José Farinha; António Cardoso. 2021. "Anticipating Future Behavior of an Industrial Press Using LSTM Networks." Applied Sciences 11, no. 13: 6101.
Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.
Ana Malta; Mateus Mendes; Torres Farinha. Augmented Reality Maintenance Assistant Using YOLOv5. Applied Sciences 2021, 11, 4758 .
AMA StyleAna Malta, Mateus Mendes, Torres Farinha. Augmented Reality Maintenance Assistant Using YOLOv5. Applied Sciences. 2021; 11 (11):4758.
Chicago/Turabian StyleAna Malta; Mateus Mendes; Torres Farinha. 2021. "Augmented Reality Maintenance Assistant Using YOLOv5." Applied Sciences 11, no. 11: 4758.
The big hospitals’ electricity supply system’s reliability is discussed in this article through Petri nets and Fuzzy Inference System (FIS). To simulate and analyse an electric power system, the FIS Mamdani in MATLAB is implemented. The advantage of FIS is that it uses human experience to provide a faster solution than conventional techniques. The elements involved are the Main Electrical Power, the Generator sets, the Automatic Transfer Switches (ATS), and the Uninterrupted Power Supply (UPS), which are analysed to characterize the system behaviour. To evaluate the system and identified the lower reliability modules being proposed, a new reliable design model through the Petri Nets and Fuzzy Inference System approach. The resulting approach contributes to increasing the reliability of complex electrical systems, aiming to reduce their faults and increase their availability.
Constâncio Pinto; José Farinha; Sarbjeet Singh; Hugo Raposo. Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling. Applied Sciences 2021, 11, 2604 .
AMA StyleConstâncio Pinto, José Farinha, Sarbjeet Singh, Hugo Raposo. Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling. Applied Sciences. 2021; 11 (6):2604.
Chicago/Turabian StyleConstâncio Pinto; José Farinha; Sarbjeet Singh; Hugo Raposo. 2021. "Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling." Applied Sciences 11, no. 6: 2604.
Reliability and safety analyses are the most important activities for reducing risk of failure events and upgrading availability of manufacturing industries. The traditional statistical models have been currently used; however, the complexity growth and diversity of systems as well as uncertainty of their functions result in extreme difficulties in analyzing the reliability by such models. To overcome such drawbacks, the soft computing techniques are useful alternative for modeling of complex systems and prediction applications. Hence, this paper provides a comparative structure for predicting the operational reliability in automotive manufacturing industry, using soft computing + statistical techniques. The results of comparative structure revealed that the soft computing techniques can estimate the reliability function with the lowest error in all cases. Based on the performance criteria, it was observed that among the soft computing techniques, the Adaptive Neuro-Fuzzy Inference System (ANFIS) model yields better results in most cases and thus can be used for predicting operational reliability, since it predicts the reliability more accurately and precisely than the statistical models. Ultimately, the maintenance intervals based on the ANFIS model are proposed to upgrade the reliability and safety of automotive manufacturing process.
Hamzeh Soltanali; Abbas Rohani; Mohammad Hossein Abbaspour-Fard; José Torres Farinha. A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing. Applied Soft Computing 2020, 98, 106738 .
AMA StyleHamzeh Soltanali, Abbas Rohani, Mohammad Hossein Abbaspour-Fard, José Torres Farinha. A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing. Applied Soft Computing. 2020; 98 ():106738.
Chicago/Turabian StyleHamzeh Soltanali; Abbas Rohani; Mohammad Hossein Abbaspour-Fard; José Torres Farinha. 2020. "A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing." Applied Soft Computing 98, no. : 106738.
Production performance measurement is the most important activity to achieve the higher productivity in food industries. The Overall Equipment Effectiveness (OEE) is a standard for measuring production productivity. However, the uncertainty of OEE components could mask the true production performance estimation in food processing lines. In this study, the production speed and stoppage duration measurements as major uncertainties to estimate the OEE and its components were investigated. In order to handle the uncertainties, two methods based on fuzzy arithmetic and interval arithmetic were conducted to supplement the classical-OEE. To survey the classical-OEE, the operational data field of edible oil purification process over a period of two years were examined. The comparison results of filed data revealed that the new OEE index has been increased around 4% by maintenance improvements. In such index, the total availability, performance efficiency and quality rate were improved by 3%, 2% and 5%, respectively. The research results showed that the spread values of Fuzzy-OEE are more explicit to show the worst and best values, while the interval arithmetic of OEE reflects the results by tighter limits. The proposed methods are more convenient to quantify uncertainty with limits to understand the OEE variations helping to make better decisions on uncertainties in food production lines.
Hamzeh Soltanali; Mehdi Khojastehpour; José Torres Farinha. Measuring the production performance indicators for food processing industry. Measurement 2020, 173, 108394 .
AMA StyleHamzeh Soltanali, Mehdi Khojastehpour, José Torres Farinha. Measuring the production performance indicators for food processing industry. Measurement. 2020; 173 ():108394.
Chicago/Turabian StyleHamzeh Soltanali; Mehdi Khojastehpour; José Torres Farinha. 2020. "Measuring the production performance indicators for food processing industry." Measurement 173, no. : 108394.
The use of clean and renewable energy sources is increasingly important, for economic and environmental reasons. Wind plays a key role among renewable energy sources. Hence, the location, monitoring and maintenance of wind turbines are areas that have received more and more attention in recent years. The paper presents a survey of datasets of wind resources, wind farm installed capacity and wind farm operation, which contain generous amounts of data. Those datasets are important tools, freely available for analysis of wind resources and study of the performance of wind turbines. A short analysis of one of the datasets is also presented, identifying different operational regions, and the ones more likely to aggregate failures. Principal Component Analysis (PCA) is used to study wind turbines’ behavior.
Diogo Menezes; Mateus Mendes; Jorge Alexandre Almeida; Torres Farinha. Wind Farm and Resource Datasets: A Comprehensive Survey and Overview. Energies 2020, 13, 4702 .
AMA StyleDiogo Menezes, Mateus Mendes, Jorge Alexandre Almeida, Torres Farinha. Wind Farm and Resource Datasets: A Comprehensive Survey and Overview. Energies. 2020; 13 (18):4702.
Chicago/Turabian StyleDiogo Menezes; Mateus Mendes; Jorge Alexandre Almeida; Torres Farinha. 2020. "Wind Farm and Resource Datasets: A Comprehensive Survey and Overview." Energies 13, no. 18: 4702.
Hugo David Nogueira Raposo; José Torres Farinha; Inácio Fonseca; Diego Galar. Predicting condition based on oil analysis – A case study. Tribology International 2019, 135, 65 -74.
AMA StyleHugo David Nogueira Raposo, José Torres Farinha, Inácio Fonseca, Diego Galar. Predicting condition based on oil analysis – A case study. Tribology International. 2019; 135 ():65-74.
Chicago/Turabian StyleHugo David Nogueira Raposo; José Torres Farinha; Inácio Fonseca; Diego Galar. 2019. "Predicting condition based on oil analysis – A case study." Tribology International 135, no. : 65-74.
This paper presents a case study and a model to predict maintenance interventions based on condition monitoring of diesel engine oil in urban buses by accompanying the evolution of its degradation. Many times, under normal functioning conditions, the properties of the lubricants, based on the intervals that manufacturers recommend for its change, are within normal and safety conditions. Then, if the lubricants’ oil condition is adequately accompanied, until reaching the degradation limits, the intervals of oil replacement can be enlarged, meaning that the buses’ availability increases, as well as their corresponding production time. Based on this assumption, a mathematical model to follow and to manage the oil condition is presented, in order to predict the next intervention with the maximum time between them, which means the maximum availability.
Hugo Raposo; José Torres Farinha; Inácio Fonseca; L. Andrade Ferreira. Condition Monitoring with Prediction Based on Diesel Engine Oil Analysis: A Case Study for Urban Buses. Actuators 2019, 8, 14 .
AMA StyleHugo Raposo, José Torres Farinha, Inácio Fonseca, L. Andrade Ferreira. Condition Monitoring with Prediction Based on Diesel Engine Oil Analysis: A Case Study for Urban Buses. Actuators. 2019; 8 (1):14.
Chicago/Turabian StyleHugo Raposo; José Torres Farinha; Inácio Fonseca; L. Andrade Ferreira. 2019. "Condition Monitoring with Prediction Based on Diesel Engine Oil Analysis: A Case Study for Urban Buses." Actuators 8, no. 1: 14.
The electromedicine and biomedical engineering are two fields where the hospital maintenance is of extreme importance; for this reason, many companies are aware and focused on the implementation of a high quality service, namely in the electromedicine maintenance equipment. This paper describes some relevant aspects about the maintenance interventions based on an outsourcing contract by the company "Assistência Total em Manutenção (ATM), S.A.", concerning electromedicine equipment in hospital environment in diverse hospitals and clinics located in the north of Portugal. In the ambit of the referred contract, the paper focus on the Vital Signs Monitors and the defibrillators. It also refers the audit methodology used on operating theatres and recovery rooms, as well as the work developed about a maintenance management platform through the software Microsoft Access program. Throughout the paper some equipment is referred, including test equipment, target of the maintenance interventions and to the audit safety process.
Nelson Mendes; Fernanda Coutinho; José Torres Farinha. Maintenance of Electromedicine Equipment: A Case Study Based on Outsourcing. 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) 2019, 1 -4.
AMA StyleNelson Mendes, Fernanda Coutinho, José Torres Farinha. Maintenance of Electromedicine Equipment: A Case Study Based on Outsourcing. 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG). 2019; ():1-4.
Chicago/Turabian StyleNelson Mendes; Fernanda Coutinho; José Torres Farinha. 2019. "Maintenance of Electromedicine Equipment: A Case Study Based on Outsourcing." 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) , no. : 1-4.
International publishers of academic, scientific and professional journals since 1979.
Filipe Didelet; Luís Ferreira; Hugo Raposo; José Torres Farinha. Economic life cycle of the bus fleet: a case study. International Journal of Heavy Vehicle Systems 2019, 26, 31 .
AMA StyleFilipe Didelet, Luís Ferreira, Hugo Raposo, José Torres Farinha. Economic life cycle of the bus fleet: a case study. International Journal of Heavy Vehicle Systems. 2019; 26 (1):31.
Chicago/Turabian StyleFilipe Didelet; Luís Ferreira; Hugo Raposo; José Torres Farinha. 2019. "Economic life cycle of the bus fleet: a case study." International Journal of Heavy Vehicle Systems 26, no. 1: 31.
The purpose of the paper is to discuss the application of econometric models to life-cycle cost (LCC) of an urban bus fleet with an emphasis on the maintenance costs. The practical results are compared with theoretical ones, which represent a good maintenance and functioning management. The influence of inflation ratio, as well as the price of fuel in the withdrawal time are evaluated. The paper analyses if there is a variation at the time of the vehicle replacement, obtained from several econometric methods namely the annual uniform income and minimisation of the average total cost with reduction to the present value. It also emphasises an eventual relation between the maintenance policy and the reserve fleet, and the relation between maintenance performance and time replacement of bus fleet. Finally, the paper analyses differences between replacement simulations from theoretical econometric models and the same ones applied to real data.
Hugo Raposo; José Torres Farinha; Luis Ferreira; Filipe Didelet. Economic life cycle of the bus fleet: a case study. International Journal of Heavy Vehicle Systems 2019, 26, 31 .
AMA StyleHugo Raposo, José Torres Farinha, Luis Ferreira, Filipe Didelet. Economic life cycle of the bus fleet: a case study. International Journal of Heavy Vehicle Systems. 2019; 26 (1):31.
Chicago/Turabian StyleHugo Raposo; José Torres Farinha; Luis Ferreira; Filipe Didelet. 2019. "Economic life cycle of the bus fleet: a case study." International Journal of Heavy Vehicle Systems 26, no. 1: 31.
ISO 55001 – A Strategic Tool for the Circular Economy – Diagnosis of the Organization’s State
Jose Pais; Hugo David Nogueira Raposo; A. Meireles; J. T. Farinha; Portugal And Coimbra Isec. ISO 55001 – A Strategic Toolfor the Circular Economy – Diagnosisof the Organization’s State. Journal of Industrial Engineering and Management Science 2019, 2018, 89 -108.
AMA StyleJose Pais, Hugo David Nogueira Raposo, A. Meireles, J. T. Farinha, Portugal And Coimbra Isec. ISO 55001 – A Strategic Toolfor the Circular Economy – Diagnosisof the Organization’s State. Journal of Industrial Engineering and Management Science. 2019; 2018 (1):89-108.
Chicago/Turabian StyleJose Pais; Hugo David Nogueira Raposo; A. Meireles; J. T. Farinha; Portugal And Coimbra Isec. 2019. "ISO 55001 – A Strategic Toolfor the Circular Economy – Diagnosisof the Organization’s State." Journal of Industrial Engineering and Management Science 2018, no. 1: 89-108.
The paper presents a case study and a model for condition monitoring of Diesel engines’ oil of urban buses, through the accompaniment of the evolution of its degradation, with the objective to implement a predictive maintenance policy. Along time, because the usage, there is some decay in the lubricant properties. However, in normal functioning conditions, the lubricants properties, at the time the manufacturers recommend its changing, regardless of they are within the safety limits. Then, based on the accompaniment of the lubricants’ oil condition, the intervals of oil replacement can be enlarged what implies the availability increasing and the corresponding production increasing of the equipment. The model presented in this paper shows its potential to be spread to other types of equipment and organisations that want can implement similar maintenance policies, to achieve the best availability based on the real equipment health conditioning conditions
Hugo Raposo; José Torres Farinha; Inácio Fonseca; Luis Ferreira. Condition Monitoring with Prediction Based on Oil Engines of Urban Buses – A Case Study. 2018, 1 .
AMA StyleHugo Raposo, José Torres Farinha, Inácio Fonseca, Luis Ferreira. Condition Monitoring with Prediction Based on Oil Engines of Urban Buses – A Case Study. . 2018; ():1.
Chicago/Turabian StyleHugo Raposo; José Torres Farinha; Inácio Fonseca; Luis Ferreira. 2018. "Condition Monitoring with Prediction Based on Oil Engines of Urban Buses – A Case Study." , no. : 1.
José Torres Farinha. Terology beyond Tomorrow. Asset Maintenance Engineering Methodologies 2018, 301 -301.
AMA StyleJosé Torres Farinha. Terology beyond Tomorrow. Asset Maintenance Engineering Methodologies. 2018; ():301-301.
Chicago/Turabian StyleJosé Torres Farinha. 2018. "Terology beyond Tomorrow." Asset Maintenance Engineering Methodologies , no. : 301-301.
The paper demonstrates the dependence of a fleet reserve of buses on the maintenance policy of the whole fleet, in particular, condition-based maintenance using a motor oil degradation analysis. The paper discusses an approach to evaluate the oil degradation and the prediction of the next value for one relevant oil variable. The methodology to evaluate the reserve fleet is based on bus availability, estimated through the mean time between failures and the mean time to repair ratios. Through the use of econometric models, it is possible to determine the most rational size of the reserve fleet.
Hugo Raposo; José Torres Farinha; Luis Ferreira; Diego Galar. Dimensioning reserve bus fleet using life cycle cost models and condition based/predictive maintenance: a case study. Public Transport 2017, 10, 169 -190.
AMA StyleHugo Raposo, José Torres Farinha, Luis Ferreira, Diego Galar. Dimensioning reserve bus fleet using life cycle cost models and condition based/predictive maintenance: a case study. Public Transport. 2017; 10 (1):169-190.
Chicago/Turabian StyleHugo Raposo; José Torres Farinha; Luis Ferreira; Diego Galar. 2017. "Dimensioning reserve bus fleet using life cycle cost models and condition based/predictive maintenance: a case study." Public Transport 10, no. 1: 169-190.
The maintenance planning corresponds to an approach that seeks to maximize the availability of equipment and, consequently, increase the levels of competitiveness of companies by increasing production times. This paper presents a maintenance planning based on operating variables (number of hours worked, duty cycles, number of revolutions) to maximizing the availability of operation of electrical motors. The reading of the operating variables and its sampling is done based on predetermined sampling cycles and subsequently is made the data analysis through time series algorithms aiming to launch work orders before reaching the variables limit values. This approach is supported by tools and technologies such as logical applications that enable a graphical user interface for access to relevant information about their Physical Asset HMI (Human Machine Interface), including the control and supervision by acquisition through SCADA (Supervisory Control And data acquisition) data, also including the communication protocols among different logical applications.
Francisco Rodrigues; Inácio Fonseca; José Torres Farinha; Luís Ferreira; Diego Galar. Electric Motors Maintenance Planning From Its Operating Variables. Management Systems in Production Engineering 2017, 25, 205 -216.
AMA StyleFrancisco Rodrigues, Inácio Fonseca, José Torres Farinha, Luís Ferreira, Diego Galar. Electric Motors Maintenance Planning From Its Operating Variables. Management Systems in Production Engineering. 2017; 25 (3):205-216.
Chicago/Turabian StyleFrancisco Rodrigues; Inácio Fonseca; José Torres Farinha; Luís Ferreira; Diego Galar. 2017. "Electric Motors Maintenance Planning From Its Operating Variables." Management Systems in Production Engineering 25, no. 3: 205-216.
Hugo Raposo; José Torres Farinha; Luis Ferreira; Diego Galar. An integrated econometric model for bus replacement and determination of reserve fleet size based on predictive maintenance. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017, 19, 358 -368.
AMA StyleHugo Raposo, José Torres Farinha, Luis Ferreira, Diego Galar. An integrated econometric model for bus replacement and determination of reserve fleet size based on predictive maintenance. Eksploatacja i Niezawodnosc - Maintenance and Reliability. 2017; 19 (3):358-368.
Chicago/Turabian StyleHugo Raposo; José Torres Farinha; Luis Ferreira; Diego Galar. 2017. "An integrated econometric model for bus replacement and determination of reserve fleet size based on predictive maintenance." Eksploatacja i Niezawodnosc - Maintenance and Reliability 19, no. 3: 358-368.
The maintenance of diesel Engines is usually scheduled according to the maintenance procedures defined by manufacturers. However, the state of the art shows that the condition monitoring maintenance associated with adequate prediction algorithms allows performance improvement both by increasing the intervals between interventions and by helping to maintain reliability levels. There are many types of variables that can be used to measure equipment condition, as is the case of several types of pollutant emissions such as NOx, CO2, HC, PM, and NOISE, among others. This is a typical problem that can be solved through a hidden Markov model, taking into account the specificity of this type of equipment. The paper describes two algorithms that can help to increase the quality of assessment of engine states and the efficiency of maintenance planning. Those are the Viterbi and Baum–Welch algorithms. The importance of how to calculate the performance index of the model by the use of the perplexity algorithm is also emphasized. In this paper, a new paradigm is proposed, designated as ecological predictive maintenance. Copyright © 2017 John Wiley & Sons, Ltd.
António Simões; José Manuel Viegas; José Torres Farinha; Inácio Fonseca. The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines. Quality and Reliability Engineering International 2017, 33, 2765 -2779.
AMA StyleAntónio Simões, José Manuel Viegas, José Torres Farinha, Inácio Fonseca. The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines. Quality and Reliability Engineering International. 2017; 33 (8):2765-2779.
Chicago/Turabian StyleAntónio Simões; José Manuel Viegas; José Torres Farinha; Inácio Fonseca. 2017. "The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines." Quality and Reliability Engineering International 33, no. 8: 2765-2779.