Relevant bibliographies by topics / Production engineering maintenance

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Production engineering maintenance'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Production engineering maintenance"

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Wöstmann, R., P. Strauss, and J. Prof Deuse. "Predictive Maintenance in der Produktion*/Predictive Maintenance in production." wt Werkstattstechnik online 107, no. 07-08 (2017): 524–29. http://dx.doi.org/10.37544/1436-4980-2017-07-08-48.

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Über neue Möglichkeiten der Vernetzung und Datenverarbeitung von Anlagen und -komponenten gewinnt die prädiktive Instandhaltung stetig an Bedeutung. Während sie insbesondere in der Luftfahrt sowie bei der Versorgungs- und Energietechnik schon seit Jahren zum Einsatz kommt, sind innerhalb der Produktion derzeit noch wenige Anwendungsfälle zu finden. Der Beitrag stellt die bisher ungenutzten Potentiale dar, indem branchenübergreifende Anwendungsfälle sowie deren Übertragbarkeit auf die Produktion und Voraussetzungen für eine erfolgreiche Einführung vorgestellt werden.   Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applications and their transferability to production as well as prerequisites for a successful implementation.
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Tapiero, Charles S. "Continuous quality production and machine maintenance." Naval Research Logistics Quarterly 33, no. 3 (August 1986): 489–99. http://dx.doi.org/10.1002/nav.3800330313.

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Ahmad, Rosmaini, and Shahrul Kamaruddin. "Structured maintenance engineering policy development based on a production machine process perspective." Journal of Quality in Maintenance Engineering 23, no. 2 (May 8, 2017): 180–94. http://dx.doi.org/10.1108/jqme-03-2016-0009.

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Purpose The purpose of this paper is to present the development of a maintenance engineering policy in the context of a decision support model based on a production machine process perspective. Design/methodology/approach The structure of the policy is called the maintenance decision support (MDS) model, which consists of three steps: initial setup, deterioration monitoring, and decision making. A detailed presentation of each step of the proposed model together with a real case example from the pulp manufacturing industry proves the applicability of the model. Findings Validation of the proposed MDS model is as follows. In Task 1 of Step 1, the cutting, sealing, and perforating line processes are classified as critical machining processes. The analysis of Task 2 of Step 1 found that cutting knife, bearing, and motor are classified as the components that most possibly contribute to the cutting appearance quality. In Task 3 of Step 1, it was found that the cutting knife is classified as a maintenance-significant component with non-repairable and single-component type characteristics. The result of Step 2 suggested that at the 29th hour of operating time, the decision of do-something was suggested. In the following step (Step 3), for the case of the cutting knife, which has been classified as a non-repairable type component, the decision to perform preventive replacement of cutting knife is recommended to be carried out at the 29th hour of operating time. Research limitations/implications The uniqueness of this model is that it systematically considers different machinery component(s) characteristics, including single- and multiple-component cases, repairable and non-repairable types, and functional or/and physical failure types, to make maintenance decisions. Practical implications The proposed MDS model provides a systematic guideline for identifying, evaluating, and monitoring, which makes maintenance-related decisions. Three significant maintenance decisions can be determined based on the proposed MDS model, which includes an appropriate time-to-perform maintenance, correct maintenance actions to be performed, and the right component required for maintenance (for multi-component cases). Originality/value One of the vital elements in considering the production machine process perspective toward the development of the MDS model is the need to use product output/quality characteristics for machine deterioration-monitoring and decision-making processes.
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Zhang, Jun, Zhao Hong Yan, and Zhang Jian Qiang. "IETM Technology is the Development Direction of Engineering Machinery Maintenance." Advanced Materials Research 823 (October 2013): 572–76. http://dx.doi.org/10.4028/www.scientific.net/amr.823.572.

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Based on the interactive electronic technical manual (IETM) characteristics of the analysis, combined with the current situation of China's engineering machinery repair, comparative analysis of technical advantages of using IETM technology in engineering machinery repair in data acquisition technology, from the speed, fault isolation efficiency and personnel's work efficiency and other aspects, discusses the necessity of its application; combined with IETM production standards, from the main creative part of IETM, such as information generation, information management, production of interactive interface, several aspects of publishing, explains IETM make the development process and the main production platform. By using the structure block diagram, showing the method of information production and information management mode, and the main modules in the block diagram and function are described; and discusses future development proposals.
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Wang, Chih-Hsiung. "Optimal production and maintenance policy for imperfect production systems." Naval Research Logistics 53, no. 2 (March 2006): 151–56. http://dx.doi.org/10.1002/nav.20124.

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IRAVANI, SEYED M. R., and IZAK DUENYAS. "Integrated maintenance and production control of a deteriorating production system." IIE Transactions 34, no. 5 (May 2002): 423–35. http://dx.doi.org/10.1080/07408170208928880.

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Zarrin, Mansour, and Ali Azadeh. "Simulation optimization of lean production strategy by considering resilience engineering in a production system with maintenance policies." SIMULATION 93, no. 1 (September 29, 2016): 49–68. http://dx.doi.org/10.1177/0037549716666682.

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Lean production aims are to reduce work-in-process and maintain close to zero inventories and resilience is about reacting quickly to disruptions impacting manufacturing systems. In this study, a manufacturing organization with maintenance strategy is simulated to evaluate the impacts of resilience engineering (RE) principles on lean practices. The process of simulation is conducted for different scenarios. Each scenario includes a set of resilience principles. Using computer simulation, many outputs are calculated namely, utility and availability of machines and maintenance operators, time in system, total cost, and number of failures. The optimal values of scenarios’ efficiencies are achieved using data envelopment analysis (DEA) model, which is a mathematical programming approach. The results of the DEA are validated by using principal component analysis. In addition, an analysis is performed to determine which factor of RE has the maximum effect on the system’s performance. The results show that the redundancy among the RE principles, has the maximum impact on the system’s performance. To the best of my knowledge, this is the first study that evaluates the performance of lean production considering RE in a production line with maintenance policies.
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Chang, Qing, Jun Ni, Pulak Bandyopadhyay, Stephan Biller, and Guoxian Xiao. "Maintenance Opportunity Planning System." Journal of Manufacturing Science and Engineering 129, no. 3 (February 7, 2007): 661–68. http://dx.doi.org/10.1115/1.2716713.

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Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. Since the majority of PM tasks requires that equipment be stopped, these tasks can generally only be performed during nonproduction shifts, breaks, or other scheduled downtime. Thus, there is a trade-off between time dedicated to production and time available for preventive maintenance. One approach to mitigate this trade-off is to perform maintenance during scheduled production time by strategically shutting down equipment for short time periods. This research developed a systematic method on when to shut down equipment to do maintenance in an automotive assembly environment. It is called maintenance opportunity. The method incorporated real-time information about production and machine failure conditions. A simulation-based algorithm is developed by utilizing the buffer contents as well as machine starvation and congestion to obtain maintenance opportunities during production time.
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Macchi, Marco, Adolfo Crespo Márquez, Maria Holgado, Luca Fumagalli, and Luis Barberá Martínez. "Value-driven engineering of E-maintenance platforms." Journal of Manufacturing Technology Management 25, no. 4 (April 29, 2014): 568–98. http://dx.doi.org/10.1108/jmtm-04-2013-0039.

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Purpose – The purpose of this paper is to propose a methodology for the engineering of E-maintenance platforms that is based on a value-driven approach. Design/methodology/approach – The methodology assumes that a value-driven engineering approach would help foster technological innovation for maintenance management. Indeed, value-driven engineering could be easily adopted at the business level, with subsequent positive effects on the industrial applications of new information and communication technologies solutions. Findings – The methodology combines a value-driven approach with the engineering in the maintenance scope. The methodology is tested in a manufacturing case to prove its potential to support the engineering of E-maintenance solutions. In particular, the case study concerns the investment in E-maintenance solutions developed in the framework of a Supervisory Control and Data Acquisition system originally implemented for production purposes. Originality/value – Based on literature research, the paper presents a methodology that is implemented considering three different approaches (business theories, value-driven engineering and maintenance management). The combination of these approaches is novel and overcomes the traditional view of maintenance as an issue evaluated from a cost-benefit perspective.
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Nentwich, Corbinian, Maximilian Benker, Johannes Ellinger, Simon Zhai, Robin Kleinwort, Gunther Reinhart, and F. Michael Zäh. "Predictive Maintenance in der Produktion/Predictive Maintenance within the industrial value chain." wt Werkstattstechnik online 110, no. 03 (2020): 98–102. http://dx.doi.org/10.37544/1436-4980-2020-03-14.

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Ungeplante Maschinenausfälle führen zu Stillständen in der Produktion, die große Auswirkungen auf die Wertschöpfungskette eines Unternehmens haben. Der Einsatz von Predictive Maintenance (PdM) entlang dieser Kette erhöht die Maschinenverfügbarkeit und sichert einen reibungslosen Produktionsablauf. Im Rahmen verschiedener Forschungsprojekte am iwb werden Anwendungsfälle für PdM in der Fertigung, der Montage und der Produktionssteuerung betrachtet. Dieser Beitrag beleuchtet individuelle Herausforderungen, Lösungsansätze und Grenzen von PdM im produktionstechnischen Umfeld.   Unplanned machine downtimes can have a big impact on the value chain of a company. Predictive Maintenance (PdM) shows the potential to increase machine availability and secures smooth production processes. Different research projects at iwb examine applications of PdM within manufacturing and assembly, as well as the integration of such approaches in production planning. This article highlights individual challenges, solutions and limits of PdM within production.
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Dissertations / Theses on the topic "Production engineering maintenance"

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Coetzee, Jasper Lodewikus. "An Optimised instrument for designing a maintenance plan - A sequel to reliability centred maintenance." Thesis, University of Pretoria, 2002. http://hdl.handle.net/2263/30007.

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Reliability Centred Maintenance (RCM) started a new chapter in the history of preventive maintenance strategy setting. It was now possible to develop a scientifically based, highly successful maintenance program for complex systems. It developed as a result of the reliability problems and cost of maintenance of aircraft during the late 50’s and early 60’s. The result was a methodology called MSG-1, followed by the improved MSG-2. When MSG-2 was used contractually for the United States Department of Defence, it led to the present definition of RCM. In academic circles there developed a growing dissatisfaction with the technique [Pintelon et al (1999], of which part stems from watering down its scientific basis to make RCM more marketable [Moubray (2000)], while at least part is based on perceived inherent scientific weaknesses in the methodology itself. This thesis, in setting out to solve these limitations, makes several important contributions to the RCM methodology. The first of these is a method of concentrating the RCM analysis effort on the most important failure modes encountered by the organisation. Secondly, it introduces a Quality Improvement task in the RCM task selection tree, based on a limitation identified by Harris (1985). The third contribution is the addition of a formal task packaging methodology, following Gits (1984). The thesisalso combines the use of RCM for the most important failure modes with conventional maintenance tasks for the remaining failure modes, to form a total methodology for the typical industrial concern. It furthermore introduces the application of sound management principles in the implementation of RCM and lastly, blends concepts from different RCM authors, together with the innovations listed above, into one logical whole. In summary, the proposed revised methodology can play a very important part to achieve the goal of World Class manufacturing standards, including ensuring that the organisation’s maintenance effort is as proactive as possible. D13/4/90
Thesis (PhD (Industrial Engineering))--University of Pretoria, 2002.
Industrial and Systems Engineering
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Enofe, Obamwonyi Martyn, and Gregory Aimienrovbiye. "Maintenance impact on Production Profitability - A Case Study." Thesis, Linnéuniversitetet, Institutionen för teknik, TEK, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-6633.

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Maintenance has had a tremendous impact on company’s proficiency to optimize its production system in order to meet its long term objectives. Generally, a production system in which maintenance is not given attention may easily lead to the system producing defective product as a result of machine defect. The purpose of this thesis is to utilized tools and methods to analyze the impact of maintenance implementation in a production system. The analytical Hierarchy process was utilized to filter the defining factors and sub-factors considered to be related to the life length and performance of production equipment in the research which was carried out at SCA Packaging Sweden AB. Various cost associated with these factors were analyzed using the cost breakdown structure, an element of life cycle cost analysis. Finally, economic evaluation of the filtered factors was performed to show the benefits associated with implementing maintenance. The result shows that while investment on maintenance implementation might be a cost at the earlier stage of implementation because it is hard to measure and follow up its impact on company’s business. Nevertheless, its role in improving company productivity profitability is indispensable. Thus, maintenance is a profit centre rather than a cost centre.
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Riccetti, Sauro. "Design of equipment safety & reliability for an aseptic liquid food packaging line through maintenance engineering." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/5301.

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The organisation of maintenance, in the Aseptic Liquid Food (ALF) industry, represents an important management task that enables a company to pursue higher manufacturing effectiveness and improved market share. This research is concerned with the process to design and implement maintenance tasks. These two complementary processes (design and implementation) have been thought and designed to answer the particular needs of food industry regarding product safety and equipment reliability. Numerous maintenance engineering researchers have focused on maintenance engineering and reliability techniques highlighting the contribution of maintenance in achieving world class manufacturing and competitive advantage. Their outcome emphasizes that maintenance is not a “necessary evil” because of costs associated, but it can be considered an “investment” that produces an added value which generates a real company profit. The existing maintenance engineering techniques pursue equipment reliability at minimum cost; but in food industry, food safety represents the most critical issue to address and solve. The research methodology chosen is based on case studies coming from ALF industries. These show that low maintenance effectiveness could have dramatic effects on final consumers and on the company’s image and underline the need of a maintenance design and implementation process that takes into consideration all critical factors relevant to liquid food industry. The analysis of measurable indicators available, represents a tool necessary to show the status of critical performance indicators and reveals the urgency of a research necessary to address and solve the maintenance problems in food industry. The literature review underlines the increasing regulations in place in food industry and that no literature is available to define a maintenance design and implementation process for ALF and in general for food industry. The literature review enabled also the gap existing between theory and real maintenance status, in the ALF, to be identified and the aim of the research was to explore this gap. The analysis of case studies and Key Performance Indicators (KPI’s) available highlights the problem and the literature review provides the knowledge necessary to identify the process to design and implement maintenance procedures for ALF industry. The research findings provide a useful guide to identify the process to design maintenance tasks able to put under control food safety and equipment reliability issues. Company’s restraining forces and cultural inertia, that work against new maintenance procedures, have been analysed and a maintenance implementation process have been designed to avoid losing the benefits produced by the design phase. The analysis of condition monitoring systems shows devices and techniques useful to improve product safety, equipment reliability, and then maintenance effectiveness. This research aimed to fill the gap in the existing literature showing the solution to manage both food safety and production effectiveness issues in food industry. It identifies a maintenance design process able to capture all conceivable critical factors in food industry and to provide the solution to design reliable task lists. Furthermore, the maintenance implementation process shows the way to maximize the maintenance design outcome through the empowerment of equipment operators and close cooperation with maintenance and quality specialists. The new maintenance design and implementation process represents the answer to the research problem and a reliable solution that allows the food industry to improve food safety and production effectiveness.
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MOAYED, FARMAN AMIN. "EVALUATION AND ANALYSIS OF THE MAINTENANCE FUNCTION IN LEAN PRODUCTION v.s. MASS PRODUCTION." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1037653472.

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Edakara, Sibson Dalgo. "A novel methodology to investigate the performance of production line systems using an integrated product service system approach." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/a-novel-methodology-to-investigate-the-performance-of-production-line-systems-using-an-integrated-product-service-system-approach(9d2163cc-511c-4801-bc9c-18f2f7b5b6a2).html.

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Production Line Systems (PLS) are ubiquitous in today’s manufacturing industry. The need for enhanced efficiencies and higher throughput in such systems has increased their complexity and size that has made performance analysis challenging for practitioners. This thesis introduces a novel approach based on Product Service System (PSS) design and analysis which simplifies Production Line System study and identifies opportunities for performance improvement that can be quantified based on the hardware and maintenance system performance. The approach involves modelling and simulation techniques based on reliability engineering principles and systems thinking. In order to apply the principles of PSS approach to PLS, it is essential to draw a comparison between PLS and PSS, so as to take account of the differences while applying the new approach; a literature review has been carried out on PSS Design and Analysis, that identified the state of the art modelling and simulation techniques in PSS. Additionally, a separate literature review on maintenance system and production line was carried out. This enabled the PSS methodology to be applied to PLS by incorporating the differences. A systems thinking approach has been employed to create the static simulation model of the integrated production line system by means of schematic representations. Key improvement areas, identified from the static simulation model have been modelled dynamically to incorporate the stochastic behaviour of the system. All the dynamic models are developed using a Discrete Event Simulation platform. These models were supported by Monte Carlo Simulation, queuing principles, probabilistical and statistical methods pertinent to reliability engineering. The novel integrated simulation model consists of a production line model and a maintenance system model. The production line model simulates two types of failures in addition to the outages in the system: breakdowns and short stops. The maintenance system model simulates the maintenance actions in the production line by considering the resources availability, repair time, and resources travelling time amongst others. In addition, the maintenance model is capable of optimizing the preventive maintenance interval for maintainable failures for cost, availability and criticality while taking into account the maintenance effectiveness value from the failure data. The simulation model is validated using an industrial case study which consists of a large production line for beer. Sensitivity studies on the simulation model enabled the case study company to focus on strategies for throughput improvement by improving the reliability and maintainability, optimal resources allocation and maintenance interval optimization in targeted areas in the large and complex system. The model developed is generic and can easily be applied to analyse other industrial production line systems. It can also be used as a design tool for new production lines.
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Feliciano, David Michael. "Exploring barriers, enablers,jJustification and planning methods for total productive maintenance implementation in automated production of commercial airplanes." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98998.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M., Massachusetts Institute of Technology, Engineering Systems Division, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 87-90).
The 737 program is currently producing 42 airplanes per month and will increase that production rate to 47 per month by 2017 and 52 per month in 2018 [1] [2]. In order to help meet these rates Boeing plans to increase the amount of automation in the shop that produces front and rear spars for all 737 variants. To mitigate risks associated with increased automation, the automation design team would like to implement an approach to equipment maintenance and operation known as Total Productive Maintenance (TPM). However the justification for TPM was not clear and an implementation strategy did not exist. The focus of this thesis therefore, is to clarify the justification for TPM, understand how TPM could impact the production system, identify the barriers and enablers of TPM implementation at Boeing, and present a TPM implementation plan that will be appropriate and effective for the particular context in which it will be executed. An analysis of current maintenance data and practices, case studies within the current factory, and a qualitative analysis of the future production system suggest that TPM could provide many quantitative and qualitative benefits and that the new production system is a good candidate for TPM. Results from a discrete event model show that TPM poses minimal risk of disrupting the future production system. Results of an employee survey show that the most important factors to successful TPM implementation are related to planning and building support prior to implementation. These findings influenced the design of the TPM implementation plan presented in this thesis, which focuses initially on building support, planning, and training. As the airline industry adopts automated equipment in response to increased competition, TPM may become an important strategy for staying competitive. The multi-pronged analyses demonstrated in this thesis for justifying TPM, the survey method used to understand the company-specific barriers and enablers of TPM, and the method of designing a customized TPM implementation plan based on the insights from these analyses can serve as a general model for implementing TPM within Boeing and within the broader airline industry.
by David Michael Feliciano.
M.B.A.
S.M.
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Kaabi-Harrath, Jihène. "Contribution à l'ordonnancement des activités de maintenance dans les systèmes de production." Phd thesis, Université de Franche-Comté, 2004. http://tel.archives-ouvertes.fr/tel-00259516.

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Le contexte de notre travail s'intéresse à l'ordonnancement des activités de maintenance dans les systèmes de production. L'objectif de la thèse concerne l'élaboration de méthodes de résolution minimisant un critère regroupant les deux aspects production et maintenance. Les règles de priorité ainsi que les algorithmes génétiques ayant fait leur preuve dans le domaine seront à la base de notre étude. Etude faite tout d'abord sur un problème à une machine puis étendue au cas du Flow Shop. Notre contribution comporte tois volets. Le premier volet prend appui sur les solutions générées à l'aide d'une règle de dominance reliant les tâches de production et les tâches de maintenance. Le deuxième volet propose un algorithme par séparation et évaluation permettant de générer des ordonnancements de permutation du problème conjoint de la production et de la maintenance au sein du FLow Shop à deux machines. Le troisième volet étend l'étude au cas du Flow Shop à plusieurs machines. Nous proposons dans ce cas un algorithme génétique avec un codage approprié. Cet algorithme a l'avantage de balayer tout l'espace de recherche et par conséquent de générer des ordonnancements de très bonne qualité. Nous optons pour la maintenance préventive systématique pour l'appliquer dans notre étude. L'une des difficultés majeures de ce type de maintenance est le choix des périodes d'interventions optimales. Nous proposons dans ce cadre une méthode de choix de périodes systématiques.
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Benbouzid, Sitayeb Fatima. "Contribution à l'étude de la performance et de la robustesse des ordonnancements conjoints Production/Maintenance - Cas du Flowshop." Phd thesis, Université de Franche-Comté, 2005. http://tel.archives-ouvertes.fr/tel-00257906.

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La maintenance et la production sont deux fonctions qui agissent sur les mêmes ressources. Cependant l'ordonnancement de leurs activités respectives est indépendant, et ne tient pas compte de cette contrainte. Les ressources (machines) sont toujours considérées comme disponibles à tout moment ou éventuellement durant certaines fenêtres de temps. Dès lors la planification de la maintenance n'est jamais prioritaire sur la production, pour effectuer des interventions préventives. Les travaux de cette thèse proposent quelques éléments de réponse au problème de la planification commune et intégrée des tâches de maintenance et de production, avec comme objectif le respect des contraintes intrinsèques au problème. L'objectif de notre travail est double. D'une part démontrer la nécessité de développer des heuristiques d'ordonnancement conjoint production/maintenance pour atteindre l'objectif d'optimisation de la sûreté de fonctionnement du système de production. Dans ce contexte nous avons proposé l'adaptation d'un certains nombre d'heuristiques des approches constructive, itérative et évolutive pour le cas de l'ordonnancement conjoint production/maintenance dans un atelier de type flowshop de permutation. D'autre part, nous avons étudié la contribution de la maintenance à la robustesse de ces ordonnancements conjoints. Le modèle proposé a pour objectif d'inscrire la génération d'ordonnancements conjoints comme une démarche proactive, et de démontrer que l'intégration de la maintenance lors de la génération des ordonnancements de production est à mettre au profit de la robustesse de ces derniers.
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Thomas, Edouard. "Contribution à la prise de décision dynamique en maintenance prévisionnelle par formalisation d'un principe d'opportunité." Phd thesis, Université Henri Poincaré - Nancy I, 2009. http://tel.archives-ouvertes.fr/tel-00420000.

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Les besoins essentiels de produire " plus ", " mieux " et " moins cher " s'inscrivent aujourd'hui dans une crise financière qui conduit les entreprises industrielles à faire face à des enjeux économiques liés aux impératifs de gains de productivité, mais aussi à des enjeux sociaux liés aux impératifs de sécurité des hommes et des matériels, aux exigences de protection de l'environnement et de réduction des nuisances. Ces enjeux se déclinent au niveau des équipements par le concept de maintien en condition opérationnelle (MCO). La maintenance en est l'élément principal, et l'un des principaux leviers d'action sur la performance globale des systèmes de production lorsqu'elle est couplée à un processus de pronostic. On parle alors de stratégies de maintenance prévisionnelles.
Ces nouvelles formes de maintenance posent de nombreux défis scientifiques et industriels, dont certains sont étudiés dans les présents travaux : Quel est le " meilleur " instant pour réaliser une intervention de maintenance préventive donnée ? Comment regrouper deux actions de maintenance préventive ? Qu'est-ce qu'une opportunité pour la maintenance ?
Les réponses à ces questions mobilisent des outils mathématiques variés, allant de l'algorithme de Bruss en analyse stochastique aux relations d'équivalence en algèbre.
Enfin, une application industrielle sur la plateforme TELMA est présentée.
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Hassan, Muhammad. "Production 4.0 of Ring Mill 4 Ovako AB." Thesis, Högskolan i Gävle, Elektronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-33405.

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Cyber-Physical System (CPS) or Digital-Twin approach are becoming popular in industry 4.0 revolution. CPS not only allow to view the online status of equipment, but also allow to predict the health of tool. Based on the real time sensor data, it aims to detect anomalies in the industrial operation and prefigure future failure, which lead it towards smart maintenance. CPS can contribute to sustainable environment as well as sustainable production, due to its real-time analysis on production. In this thesis, we analyzed the behavior of a tool of Ringvalsverk 4, at Ovako with its twin model (known as Digital-Twin) over a series of data. Initially, the data contained unwanted signals which is then cleaned in the data processing phase, and only before production signal is used to identify the tool’s model. Matlab’s system identification toolbox is used for identifying the system model, the identified model is also validated and analyzed in term of stability, which is then used in CPS. The Digital-Twin model is then used and its output being analyzed together with tool’s output to detect when its start deviate from normal behavior.
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Books on the topic "Production engineering maintenance"

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Burduk, Anna, Edward Chlebus, Tomasz Nowakowski, and Agnieszka Tubis, eds. Intelligent Systems in Production Engineering and Maintenance. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-97490-3.

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Burduk, Anna, and Dariusz Mazurkiewicz, eds. Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-64465-3.

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Rahim, M. A. Integrated Models in Production Planning, Inventory, Quality, and Maintenance. Boston, MA: Springer US, 2001.

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Shahidehpour, M. Maintenance scheduling in restructured power systems. Norwell, MA: Kluwer Academic Publishers, 2000.

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Canadian, Institute of Mining and Metallurgy Maintenance/Engineering Plant Engineering and Maintenance Conference (5th 1986 Bathurst N. B. ). Fifth CIM Maintenance/Engineering Plant Engineering and Maintenance Conference: Maintenance, the key to production and profit : Bathurst, New Brunswick, June 15-18, 1986. Montreal, Quebec: Canadian Institute of Mining and Metallurgy, 1986.

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Doucet, Ronald. Vocabulaire relatif aux nouvelles pratiques de maintenance industrielle. [Québec]: Gouvernement du Québec, Ministère de l'industrie, du commerce et de la technologie, Direction des communications, 1991.

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Smith, Ricky. Rules of thumb for maintenance and reliability engineers. Burlington, MA: Elsevier/Butterworth-Heinemann, 2007.

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Software engineering: The production of quality software. New York: Macmillan, 1987.

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Software engineering: The production of quality software. 2nd ed. New York: Macmillan Pub. Co., 1991.

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Maintenance minimization for competitive advantage: A life-cycle approach for product manufacturers and end users. Yverdon, Switzerland: Gordon and Breach Science Publishers, 1994.

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Book chapters on the topic "Production engineering maintenance"

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Dietrich, Franz, Sebastian Thiede, and Günther Seliger. "Maintenance." In CIRP Encyclopedia of Production Engineering, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-35950-7_12-3.

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Seliger, Günther. "Maintenance." In CIRP Encyclopedia of Production Engineering, 818–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-20617-7_12.

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Dietrich, Franz, Sebastian Thiede, and Günther Seliger. "Maintenance." In CIRP Encyclopedia of Production Engineering, 1120–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-53120-4_12.

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Rødseth, Harald, Per Schjølberg, Markus Wabner, and Uwe Frieß. "Predictive Maintenance for Synchronizing Maintenance Planning with Production." In Lecture Notes in Electrical Engineering, 439–46. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5768-7_47.

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Bokrantz, Jon, and Anders Skoogh. "Perspectives on the Future of Maintenance Engineering Education." In Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 209–16. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85914-5_22.

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Zimroz, Radoslaw, Monika Hardygóra, and Ryszard Blazej. "Maintenance of Belt Conveyor Systems in Poland – An Overview." In Lecture Notes in Production Engineering, 21–30. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12301-1_3.

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Roy, Rajkumar, John Ahmet Erkoyuncu, and Andy Shaw. "The Future of Maintenance for Industrial Product-Service Systems." In Lecture Notes in Production Engineering, 1–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30820-8_1.

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Fuchs, J., H. Herrmann, S. J. Oks, M. Sjarov, and J. Franke. "Increasing Efficiency in Maintenance Processes Through Modular Service Bundles." In Lecture Notes in Production Engineering, 439–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62138-7_44.

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Brockhaus, B., F. Hoffmann, J. Metternich, and M. Weigold. "Predictive Maintenance for Flexible Protective Covers in Machine Tools." In Lecture Notes in Production Engineering, 177–85. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78424-9_20.

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Zimroz, Radoslaw, Paweł K. Stefaniak, Walter Bartelmus, and Monika Hardygóra. "Novel Techniques of Diagnostic Data Processing for Belt Conveyor Maintenance." In Lecture Notes in Production Engineering, 31–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12301-1_4.

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Conference papers on the topic "Production engineering maintenance"

1

Almuhtady, Ahmad, Seungchul Lee, and Jun Ni. "Joint Maintenance and Production Planning by Maintenance-Optimal Swapping." In ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/msec2013-1076.

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Degradation is an inevitable course of any manufacturing tool, machine or system. The degradation of the health state of manufacturing tools results in some sort of an ineludible maintenance action which could be both costly and occurring during critical production time. In many manufacturing systems, a fleet of identical machines are assigned different tasks (or products) towards satisfying production requirements. We re-introduce the maintenance-optimal resource allocation planning scheme [1] (presented in MSEC2012) and focus on the solution of the generated mathematical model. The planning scheme, denoted as Degradation Based Optimal Swapping (DBOS), incorporates the optimal implementation of swapping scheduled tasks (or products) and allocating maintenance actions throughout a finite time horizon. The objective is to minimize projected maintenance costs and/or utilize the manufacturing productivity towards prescribed logistics and/or production goals. A DBOS-specific branch-and-bound-based optimization algorithm is developed to address the complexity in the generated model. Numerical results will demonstrate the effectiveness of the algorithm in comparison to standard optimization algorithms. DBOS planning scheme coupled with the proposed algorithm succeeds in establishing substantial savings in the simulated case studies which amount up to 70% of the estimated maintenance costs in comparison to the scenario where fixed scheduling is applied.
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Schutz, J. "Joint optimization of production-maintenance plans based on optimal production rates." In 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2014. http://dx.doi.org/10.1109/ieem.2014.7058775.

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Ko, Chien-Ho, and Jiun-De Kuo. "Enhancing Building Maintenance Using RFID Technology." In International Conference on Engineering, Project, and Production Management. Association of Engineering, Project, and Production Management, 2010. http://dx.doi.org/10.32738/ceppm.201010.0006.

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Liao, Wenzhu, Xiufang Zhang, and Min Jiang. "An optimization model integrated production scheduling and preventive maintenance for group production." In 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2016. http://dx.doi.org/10.1109/ieem.2016.7798015.

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Liao, Wen-Zhu, Min Jiang, and Xiu-Fang Zhang. "Group production scheduling model with due window and maintenance." In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2017. http://dx.doi.org/10.1109/ieem.2017.8289959.

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Akbar, Sajjad. "Industrial Maintenance Strategies." In 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/icone14-89148.

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Industrial plants have become more complex due to technological advancement. This has made the task of maintenance more difficult. The maintenance costs in terms of resources and downtime loss are so high that maintenance function has become a critical factor in a plant’s profitability. Industry should devote as much forethought to the management of maintenance function as to production. Maintenance has grown from an art to a precise, technical engineering science. Planning, organizing scheduling and control of maintenance using modern techniques pays dividends in the form of reduced costs and increased reliability. The magnitude and the dimension of maintenance have multiplied due to development in the engineering technologies. Production cost and capacities are directly affected by the breakdown time. Total operating cost including the maintenance cost plays an important role in replacement dimension. The integrated system approach would bring forth the desired results of high maintenance standards. The standards once achieved and sustained, would add to the reliability of the plan and relieve heavy stresses and strains on the engineering logistic support.
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Zou, Jing, Qing Chang, Yong Lei, Guoxian Xiao, and Jorge Arinez. "Stochastic Maintenance Opportunity Windows for Serial Production Line." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9307.

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Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. The current PM at most manufacturing plants is to conduct maintenance tasks during non-production shifts, breaks, or other scheduled downtime. This practice may introduce unnecessary extra labor and overhead costs. Therefore, there is need to look for hidden maintenance opportunities to perform PM tasks during normal production time without impacting throughput. Additional benefit of the hidden opportunity window is that it can be translated to hidden energy saving opportunity during which machines can be strategically shut down or turned to energy saving mode while PM can be performed. Since production schedules are always made beforehand, the development of opportunity window and the downtime schedule need future prediction about the production system. In this paper, a stochastic model of the downtime opportunity on serial production systems is developed. Based on the stochastic model, revised opportunity window and recovery time is defined, which can help on production control on deciding when and where to insert the downtime events and the duration of the downtime events for the incoming process.
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Kumar, Sandeep, and Bhupesh Kumar Lad. "Effect of maintenance resource constraints on flow-shop environment in a joint production and maintenance context." In 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2016. http://dx.doi.org/10.1109/ieem.2016.7797954.

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Lin Ma, Yong Sun, and Joseph Mathew. "Effects of Preventive Maintenance on the reliability of production lines." In 2007 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, 2007. http://dx.doi.org/10.1109/ieem.2007.4419266.

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Wang, Lin, and Zhiqiang Lu. "A predictive production planning with condition-based maintenance in a deteriorating production system." In 2016 International Conference on Robotics and Automation Engineering (ICRAE). IEEE, 2016. http://dx.doi.org/10.1109/icrae.2016.7738784.

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