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  • 1.
    Algabroun, Hatem
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Dynamic sampling rate algorithm (DSRA) implemented in self-adaptive software architecture: a way to reduce the energy consumption of wireless sensors through event-based sampling2019In: Microsystem Technologies: Micro- and Nanosystems Information Storage and Processing Systems, ISSN 0946-7076, E-ISSN 1432-1858Article in journal (Refereed)
    Abstract [en]

    With the recent digitalization trends in the industry, wireless sensors are, in particular, gaining a growing interest. This is due to the possibility of being installed in inaccessible locations for wired sensors. Although great success has already been achieved in this area, energy limitation remains a major obstacle for further advances. As such, it is important to optimize the sampling with a sufficient rate to catch important information without excessive energy consumption, and one way to achieve sufficient sampling is using adaptive sampling for sensors. As software plays an important role in the techniques of adaptive sampling, a reference framework for software architecture is important in order to facilitate their design, modeling, and implementation. This study proposes a software architecture, named Rainbow, as the reference architecture, also, it develops an algorithm for adaptive sampling. The algorithm was implemented in the Rainbow architecture and tested using two datasets; the results show the proper operation of the architecture as well as the algorithm. In conclusion, the Rainbow software architecture has the potential to be used as a framework for adaptive sampling algorithms, and the developed algorithm allows adaptive sampling based on the changes in the signal.

  • 2.
    Algabroun, Hatem
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    On the development of a maintenance approach for factory of the future implementing Industry 4.02017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The objective of this thesis is to develop a maintenance approach that fulfills the requirements of Industry 4.0. It explores the role and importance of maintenance activities in today’s industry. Then, it develops the features and tasks required to be performed by maintenance to fulfill the demands of Industry 4.0. Finally, it develops a reference model to be used in designing maintenance system for Industry 4.0. To perform these studies, real data were collected and applied as well as a typical scenario was implemented.

    The results achieved in the papers of this thesis are 1) a mathematical representation and application of a model that identifies, analyses and prioritizes economic weakness in working areas related to production, 2) a model that analyses, identifies and prioritizes failures that impact the competitive advantages and profitability of companies, 3) characterization of a suitable maintenance technique for Industry 4.0 and 4) a reference model i.e. a framework, that could be utilized to develop a maintenance approach for Industry 4.0.

    The conclusion of this thesis confirms that maintenance has a significant impact on companies’ competitive advantages, other working areas and profitability. To achieve a suitable maintenance technique for Industry 4.0, this technique must be able to monitor, diagnose, prognosis, schedule, assist in execution and present the relevant information. In order to perform these tasks several features must be acquired, the most important features are to be: digitized, automated, intelligent, able to communicate with other systems for data gathering and monitoring, openness, detect deviation in the condition at an early stage, cost- effective, flexible for adding new CM techniques, provide accurate decisions and scalable. The developed framework could be used as a base to design a maintenance system for Industry 4.0. This study contributes to our understanding of the maintenance importance in today’s industry and how to develop a maintenance approach for Industry 4.0.

  • 3.
    Algabroun, Hatem
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Al-Najjar, Basim
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Ingwald, Anders
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering. Linnaeus University, Faculty of Technology, Department of Physics and Electrical Engineering.
    Assessment of the impact of maintenance integration within a plant using MFD: A case study2019In: Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies: Proceedings of the 12th World Congress on Engineering Asset Management and the 13th International Conference on Vibration Engineering and Technology of Machinery / [ed] Joseph MathewC.W. LimLin MaDon SandsMichael E. CholettePietro Borghesani, Springer, 2019, p. 61-71Conference paper (Refereed)
    Abstract [en]

    In the recent decades the recognition of maintenance as an effective part of the company competitiveness has grown. In order to enhance maintenance performance and its positive impact, integration with the rest of the plant activities should be planned and performed. In this study, Maintenance Function Deployment model was applied on a real data of a case company. The model was used to analyse the company’s production with respect to the business and economic variables. This was done first through finding loss causes of the strategic goals of the case company, then breaking down these causes and their costs into their root causes. Based on economic estimations, the results show that the major root causes behind losses are insufficient training of personnel and lack of maintenance integration. It is concluded that properly considering the integration of maintenance within the company’s activities, reduces loss and improves the company’s performance. Also, that applying MFD eases the identification of the root-causes behind losses as well as quantifying and prioritizing the economic losses. © Springer Nature Switzerland AG 2019.

  • 4.
    Algabroun, Hatem
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Iftikhar, Muhammad Usman
    Al-Najjar, Basim
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Weyns, Danny
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Maintenance 4.0 Framework using Self: Adaptive Software Architecture2018In: Journal of Maintenance Engineering, Vol. 2, p. 280-293Article in journal (Refereed)
    Abstract [en]

    With the recent advances of manufacturing technologies, referred to as Industry 4.0, maintenance approaches have to be developed to fulfill the new de-mands. The technological complexity associated to Industry 4.0 makes designing maintenance solutions particularly challenging. This paper proposes a novel maintenance framework leveraging principles from self-adaptation and software architecture. The framework was tested in an operational scenario where a bearing condition in an electrical motor needs to be managed, the results showed a proper operation. As a conclusion, the proposed framework could be used to develop maintenance systems for Industry 4.0.

  • 5.
    Algabroun, Hatem
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Iftikhar, Muhammad Usman
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Al-Najjar, Basim
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Weyns, Danny
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Catholic University of Leuven, Belgium.
    Maintenance 4.0 Framework Using Self-Adaptive Software Architecture2017In: Proceedings of 2nd International Conference on Maintenance Engineering, IncoME-II 2017.The University of Manchester, UK, The University of Manchester, UK , 2017, , p. 299-309Conference paper (Refereed)
    Abstract [en]

    With the recent advances of manufacturing technologies, referred to as Industry 4.0, maintenance approaches have to be developed to fulfill the new de-mands. The technological complexity associated to Industry 4.0 makes designing maintenance solutions particularly challenging. This paper proposes a novel maintenance framework leveraging principles from self-adaptation and software architecture. The framework was tested in an operational scenario where a bearing condition in an electrical motor needs to be managed, the results showed a proper operation. As a conclusion, the proposed framework could be used to develop maintenance systems for Industry 4.0.

  • 6.
    Al-Najjar, Basim
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Algabroun, Hatem
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    A Model for Increasing Effectiveness and Profitability of Maintenance Performance: A Case Study2018In: Engineering Asset Management 2016: Proceedings of the 11th World Congress on Engineering Asset Management, Springer, 2018, p. 1-12Conference paper (Refereed)
    Abstract [en]

    In today’s market, companies strive to achieve the competitive advantages. Failing in achieving these goals could threaten the companies’ existence. Failures in the operative level impact negatively on achieving these goals. In order to record these failures for better actions planning, special systems are often used for counting the number of failures, registering the duration of machines downtime and uptime for assessing the total downtime and classifying problems/failures in categories that are decided in advance. These categories can be Electrical, Electronic, Hydraulic, Mechanical, Pneumatics, Human error, and Miscellaneous. In this study, we develop a model to break down the contents of a company/machine failure databases, prioritize failures, assess economic losses due to failure impact on the competitive advantages and suggest a method of how maintenance actions should be rank-ordered cost-effectively. The model is tested using real data. The major results showed that losses aremainly due to two categories i.e. “Bad quality“ and “Less profit margin”, where failures of “Gear”, “Bearing” and “Raw materials quality” cause most of the losses. It is concluded that this model enables the user to quickly identify and prioritize maintenance and improvement efforts cost-effectively.

  • 7.
    Al-Najjar, Basim
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Algabroun, Hatem
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Jonsson, Mikael
    E-maintenance Sweden AB, Sweden.
    Maintenance 4.0 to fulfil the demands of Industry 4.0 and Factory of the Future2018In: International Journal of Engineering Research and Applications, ISSN 2248-9622, E-ISSN 2248-9622, Vol. 8, no 11, p. 20-31Article in journal (Refereed)
    Abstract [en]

    In today's high market competition, industries attempt adapt new technologies retain their market share. With technology advancement in factories, maintenance methods are developed to suit the new manufacturers. demands. Now, with the Industry 4.0, new maintenance techniques have to be developed to fulfill the new demands which we refer to as Maintenance 4.0. Each currently used maintenance technique has its own advantages and disadvantages. Until now it is unclear if these techniques are suitable for Industry 4.0. This study shows how to identify the maintenance technique that is the most suitable to be further developed for Industry 4.0. In this paper, the tasks and features of Maintenance 4.0 are identified, and the suitability of the most popular maintenance techniques is examined with respect to Industry 4.0 demands. This is done by using Multiple Attribute Decision Making combined with the Simple Additive Weight. The results show that Total Quality Maintenance(TQMain) and then Condition Based Maintenance(CBM) are the highest ranked among the examined maintenance techniques, and therefore it is concluded that these maintenance techniques could be used as a based to develop Maintenance 4.0.

  • 8.
    Al-Najjar, Basim
    et al.
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Algabroun, Hatem
    Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.
    Jonsson, Mikael
    E-maintenance Sweden AB, Sweden.
    Smart maintenance model using cyber physical system2018In: Paper presented at the International Conference on "Role of Industrial Engineering in Industry 4.0 Paradigm" (ICIEIND), Bhubaneswar, India, September 27-30, 2018, 2018, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Modern manufacturing are exposed to rapid and dynamic changes in operating conditions, market demands, national and international competition. Therefore, new generations and concepts of maintenance techniques are necessary to overcome the deficiencies  in the current techniques. The purpose of this paper is to propse a maintenance model that is automatic, digitzalised and intelligent using Cyber Physical System (CPS-Maint). In this paper, we presented comparable maintenance approaches and described their shortages. Thereafter, we developed a new maintenance model. Then, A simulation using LabVIEW is conducted  to examin the model and its behavior. The results showed that the required tasks are performed with no conflict among its components. The major result is the development of CPS-Maint and the major conclusion is applying CPS-Maint fulfills industry needs. This paper provides a framework that could help developers and researchers in desining and developing an automatic and smart maintenance system.

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