Search results for: maintenance strategy selection

Authors: K.-H. Yang

Abstract:

In the past, there was a lot of excellent research studies conducted on topics related to supplier selection. Because the considered factors of supplier selection are complicated and difficult to be quantified, most researchers deal supplier selection issues by qualitative approaches. Compared to qualitative approaches, quantitative approaches are less applicable in the real world. This study tried to apply the quantitative approach to study a supplier selection problem with considering operation cost and delivery reliability. By those factors, this study applies Normalized Normal Constraint Method to solve the dual objectives mixed integer program of the supplier selection problem.

Keywords: bi-objectives MIP, normalized normal constraint method, supplier selection, quantitative approach

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Santos Cabrera, Halbert Yesid, Moncada Nino, Alvaro Fernando, Rincon Cuta, Yeisson Alexis

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The present work evaluates the feasibility of implementing a health and use monitoring system (HUMS), based on vibration analysis as a condition-based maintenance program for the UH60L 'Blackhawk' helicopters. The mixed approach used consists of contributions from national and international experts, the analysis of data extracted from the software (Meridium), the correlation of variables derived from the diagnosis of availability, the development, and application of the HUMS system, the evaluation of the latter through of the use of instruments designed for the collection of information using the DELPHI method and data capture with the device installed in the helicopter studied. The results obtained in the investigation reflect the context of maintenance in aerial operations, a reduction of operation and maintenance costs of over 2%, better use of human resources, improvement in availability (5%), and fulfillment of the aircraft’s security standards, enabling the implementation of the monitoring system (HUMS) in the condition-based maintenance program. New elements are added to the study of maintenance based on condition -specifically, in the determination of viability based on qualitative and quantitative data according to the methodology. The use of condition-based maintenance will allow organizations to adjust and reconfigure their strategic, logistical, and maintenance capabilities, aligning them with their strategic objectives of responding quickly and adequately to changes in the environment and operational requirements.

Keywords: air transportation sustainability, HUMS, maintenance based condition, maintenance blackhawk capability

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Authors: Maximilian Winkens, Peter Nyhuis

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Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

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Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros

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This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.

Keywords: asset management, PV module, optimization, maintenance

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Authors: Muhammad Azhar, Arshad Hussain

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Vehicular emissions have increased in recent years due to rapid growth in world traffic resulting in an increase in associated problems such as air pollution and climate change, therefore it’s necessary to control vehicle emissions. This study looks at the effect of road maintenance on vehicle emissions. The Highway Development and Management Tool (HDM-4) was used to find the effect of road maintenance on vehicle emissions. Key data collected were traffic volume and composition, vehicle characteristics, pavement characteristics and climate data of the study area. Two options were analysed using the HDM-4 software; the base case or do nothing while the second is overlay maintenance. The study also showed a strong correlation between average roughness and yearly emission levels in both the alternatives. Finally, the study showed that proper maintenance reduces the roughness and emissions.

Keywords: vehicle emissions, road roughness, IRI, maintenance, HDM-4, CO2

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Farzad Pargar

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We introduce the preventive maintenance and renewal scheduling problem for a multi-unit system over a finite and discretized time horizon. Given the latest possible time for carrying out the next maintenance and renewal projects after the previous ones and considering several common set-up costs, the introduced scheduling model tries to minimize the cost of projects by grouping them and simultaneously finding the optimal balance between doing maintenance and renewal. We present a 0-1 pure integer linear programming that determines which projects should be performed together on which location and in which period (e.g., week or month). We consider railway track as a case for our study and test the performance of the proposed model on a set of test problems. The experimental results show that the proposed approach performs well.

Keywords: maintenance, renewal, scheduling, mathematical programming model

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Authors: Aisha Iddrisu, Ferruh Uztuğ

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This study is a quantitative content analysis of advertising message strategies used in Ghana’s TV commercials (2020-2021) using the modified strategy of Wang and Praet (2016) with the objective of exploring the various advertising message strategies used in Ghana’s TV advertisement, its variation according to product category including the most widely used message strategy. The findings indicate that, out of the 220 commercials used in the study, the Affective message strategy (n=122, 55%) was the dominant message strategy used in Ghana’s TV commercials. The most advertised product category in Ghana’s TV commercials (2020-2021) was the food category, and a significant relationship was observed between message strategy and product category as well as message strategy and brand type.

Keywords: advertising, message strategy, Ghana, television

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Authors: John Q. Todd

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Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

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Authors: Naoko Kanazawa, Tran Thi Bich Nguyet, Yoshiyuki Higuchi, Hideki Hamada

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Construction machines’ condition is maintained with the regularly inspections, preventive maintenance and repairs by skillful and qualified engineers. If an accident occurs, there will be enormous influence such as human injuries, delays in the term of construction. In this paper, we revealed the characteristics such as inspection, maintenance and repair works for construction machines, and we also clarified the trends of employment injuries based on actual data by simple and cross tabulation methods, and investigated the relation with their works, injured body parts and accident types.

Keywords: construction machines, employment injuries, maintenance and repair, safety and health

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Osama Sassi, Manal Eltorki, Iftikhar Ahmad

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Poor integrity is one of the major causes of leaks and accidents in gas transmission pipelines. To ensure safe operation, it is must to have efficient and effective pipeline integrity management (PIM) system. The corrosion management is one of the important aspects of successful pipeline integrity management program together design, material selection, operations, risk evaluation and communication aspects to maintain pipelines in a fit-for-service condition. The objective of a corrosion management plan is to design corrosion mitigation, monitoring, and inspection strategy, and for maintenance in a timely manner. This paper presents the experience of corrosion management of a gas transmission pipeline from Wafa field to Mellitah gas plant in Libya. The pipeline is 525.5 km long and having 32 inches diameter. It is a buried pipeline. External corrosion on pipeline is controlled with a combination of coatings and cathodic protection while internal corrosion is controlled with a combination of chemical inhibitors, periodic cleaning and process control. The monitoring and inspection techniques provide a way to measure the effectiveness of corrosion control systems and provide an early warning when changing conditions may be causing a corrosion problem. This paper describes corrosion management system used in Mellitah Oil & Gas BV for its gas transmission pipeline based on standard practices of corrosion mitigation and inspection.

Keywords: corrosion mitigation on gas transmission pipelines, pipeline integrity management, corrosion management of gas pipelines, prevention and inspection of corrosion

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Authors: Farzaneh Sarbandi Farahani

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Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

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Authors: H. V. Smit, V. H. J. de Wet

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South African municipalities are dealing with aging and dilapidated infrastructure while faced with challenges in the form of expanding informal settlements, vandalism, theft, and a lack of maintenance which place even more pressure on existing infrastructure. The existing infrastructure was never designed to cater to these challenges, and this becomes evident when evaluating the current state of many municipal sewer pump stations. A need has thus arisen to develop a sewer pump station design concept that will address these challenges and allow for a long-term sustainable solution. This article deals with the design concepts which have been developed for sewer pump stations for an effective reduction in maintenance, improved grit handling, improvement to the operation and maintenance working conditions, and the adoption of high-security design philosophy.

Keywords: high security, low maintenance, municipal application, sewer pump station

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Authors: H. Cha, J. Kim, D. Kim, J. Shin, K. Lee

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Since 1980's, the rapid economic growth resulted in so many aged apartment buildings in South Korea. Nevertheless, there is insufficient maintenance practice of buildings. In this study, to facilitate the building maintenance the authors classified the building defects into three levels according to their level of performance and developed a mobile application tool based on each level's appropriate feedback. The feedback structure consisted of 'Maintenance manual phase', 'Online feedback phase', 'Repair work phase of the specialty contractors'. In order to implement each phase the authors devised the necessary database for each phase and created a prototype system that can develop on its own. The authors expect that the building users can easily maintain their buildings by using this application.

Keywords: building defect, maintenance practice, mobile application, system algorithm

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Authors: Muzamil Mahmood, Afshan Naseem, Muhammad Zeeshan Mirza, Yasir Ahmad, Masood Raza

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The purpose of this research is to analyze how aviation maintenance workers’ characteristics and work demand affect their development of work-related musculoskeletal disorders (WMSDs). Guided by literature on task characteristics, work demand, and WMSDs, data is collected from 128 aviation maintenance workers of private and public airlines. Data is then analyzed through descriptive and inferential statistics. It is found that task characteristics have a significant positive effect on WMSDs and an increase in tasks performed by aviation maintenance workers leads to increase in WMSDs. Work demand did not have a significant effect on WMSDs. The task characteristics of aviation maintenance workers moderates the relationship between their work demand and WMSDs. This reveals that task characteristics of aviation maintenance workers enhance the effect of work demand on WMSDs. The task characteristics of aviation maintenance workers are challenging and unpredictable. Subsequently, WMSDs are prevalent among aviation maintenance workers. The work demand of aviation maintenance workers does not influence their development of WMSDs. Pakistan Civil Aviation Authority should minimize the intensity of tasks assigned to aviation maintenance workers by introducing work dynamisms such as task sharing, job rotation, and probably teleworking to enhance flexibility. Human Resource and Recruitment Department need to consider the ability and fitness levels of potential aviation maintenance workers during recruitment. In addition, regular physical activities and ergonomic policies should be put in place by the management of the Pakistan Civil Aviation Authority to reduce the incidences of WMSDs.

Keywords: work related musculoskeletal disorders, ergonomics, occupational health and safety, human factors

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Authors: Aminu Mubarak Sadis

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This study appraised the maintenance management practice in Federal University Dutse and Jigawa State Polytechnic Dutse, in Nigeria. The Physical Planning, Works and Maintenance Departments of the two Higher Institutions (Federal University Dutse and Jigawa State Polytechnic) are responsible for production and maintenance management of their physical assets. Over–enrollment problem has been a common feature in the higher institutions in Nigeria, Data were collected by the administered questionnaires and subsequent oral interview to authenticate the completed questionnaires. Random sampling techniques was used in selecting 150 respondents across the various institutions (Federal University Dutse and Jigawa State Polytechnic Dutse). Data collected was analyzed using Statistical Package for Social Science (SPSS) and t-test statistical techniques The conclusion was that maintenance management activities are yet to be given their appropriate attention on functions of the university and polytechnic which are crucial to improving teaching, learning and research. The unit responsible for maintenance and managing facilities should focus on their stated functions and effect changes were possible.

Keywords: appraisal, maintenance management, university, Polytechnic, practices

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

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Authors: Chiranjit Das, Sanjay Jharkharia

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This study is focused on transport mode selection under lead time variability and emissions constraint. In order to reduce the carbon emissions generation due to transportation, organization has often faced a dilemmatic choice of transport mode selection since logistic cost and emissions reduction are complementary with each other. Another important aspect of transportation decision is lead-time variability which is least considered in transport mode selection problem. Thus, in this study, we provide a comprehensive mathematical based analytical model to decide transport mode selection under emissions constraint. We also extend our work through analysing the effect of lead time variability in the transport mode selection by a sensitivity analysis. In order to account lead time variability into the model, two identically normally distributed random variables are incorporated in this study including unit lead time variability and lead time demand variability. Therefore, in this study, we are addressing following questions: How the decisions of transport mode selection will be affected by lead time variability? How lead time variability will impact on total supply chain cost under carbon emissions? To accomplish these objectives, a total transportation cost function is developed including unit purchasing cost, unit transportation cost, emissions cost, holding cost during lead time, and penalty cost for stock out due to lead time variability. A set of modes is available to transport each node, in this paper, we consider only four transport modes such as air, road, rail, and water. Transportation cost, distance, emissions level for each transport mode is considered as deterministic and static in this paper. Each mode is having different emissions level depending on the distance and product characteristics. Emissions cost is indirectly affected by the lead time variability if there is any switching of transport mode from lower emissions prone transport mode to higher emissions prone transport mode in order to reduce penalty cost. We provide a numerical analysis in order to study the effectiveness of the mathematical model. We found that chances of stock out during lead time will be higher due to the higher variability of lead time and lad time demand. Numerical results show that penalty cost of air transport mode is negative that means chances of stock out zero, but, having higher holding and emissions cost. Therefore, air transport mode is only selected when there is any emergency order to reduce penalty cost, otherwise, rail and road transport is the most preferred mode of transportation. Thus, this paper is contributing to the literature by a novel approach to decide transport mode under emissions cost and lead time variability. This model can be extended by studying the effect of lead time variability under some other strategic transportation issues such as modal split option, full truck load strategy, and demand consolidation strategy etc.

Keywords: carbon emissions, inventory theoretic model, lead time variability, transport mode selection

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Authors: Nipun Agarwal, David Paul, Fareed Un Din

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Every organization develops a strategy that needs to be implemented and is undertaken through project delivery. In essence, project requirements should exactly replicate an organization’s strategy. In reality this does not happen, and behavioral factors deviate the project delivery from the strategic objectives. This occurs as project stakeholders can have competing objectives. Resultantly, requirements that are implemented through projects are less aligned to the strategy. This paper develops a game theoretic model to simulate why such deviations occur. That explains the difference between strategy development and implementation.

Keywords: strategy, simulation, project management, game theory

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Authors: Sung-Bok Choi, Hyun-Jun Shin, Hyoung-Kyu Song

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This paper proposes a single relay selection scheme in cooperative communication. Decode and forward scheme is considered when a source node wants to cooperate with a single relay for data transmission. To use the proposed single relay selection scheme, the source node make a little different pattern signal which is not complex pattern and broadcasts it. The proposed scheme does not require the channel state information between the source node and candidates of the relay during the relay selection. Therefore, it is able to be used in many fields.

Keywords: relay selection, cooperative communication, df, channel codes

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Authors: Zeynep Sener, Mehtap Dursun

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Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision methodology.

Keywords: fuzzy decision making, fuzzy multiple objective programming, medical supply chain, supplier selection

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Authors: Jung-In Baik, Seung-Jun Yu, Young-Min Ko, Hyoung-Kyu Song

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This paper proposes an efficient relaying algorithm to obtain diversity for improving the reliability of a signal. The algorithm achieves time or space diversity gain by multiple versions of the same signal through two routes. Relays are separated between a source and destination. The routes between the source and destination are set adaptive in order to deal with different channels and noises. The routes consist of one or more relays and the source transmits its signal to the destination through the routes. The signals from the relays are combined and detected at the destination. The proposed algorithm provides a better performance than the conventional algorithms in bit error rate (BER).

Keywords: multi-hop, OFDM, relay, relaying selection

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

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Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

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