Fuzzy FMEA model: a case study to identify rejection and losses in fibre industry

The growing competition between fibre producing industry and the standards to which, it requires high quality standards. ABC company’s procurement department data shows N of number of defects in cellulose pulp sheet uncurl every month. Cellulose sheet is an important raw material in the fibre (Staple) producing industry. Quality tools such as Failure Mode and Effects Analysis (FMEA) applied to admeasure the risk of potential miscarriages. This study aims to determine the most dominant activity as the cause of rejection and losses of cellulose sheets and evince improvements that can be made by using the fuzzy FMEA model. Data collection techniques in the study are using the method of observations, interviews as well as assessment of experts to identity it. This study is based on the four criterion which dominates the defect of cellulose pulp sheet vis. Processing activities, acceptance, examination and delivery. Solicitation for overcoming these problems is presented

A spectrum deconvolution method based on grey relational analysis

The extensive usage of X ray spectroscopies in studying complex material systems is not only intended to reveal underlying mechanisms that govern physical phenomena, but also used in applied studies focused on an insight driven performance improvement of a wide range of devices. However, the traditional analysis methods for X ray spectroscopic data are rather time consuming and sensitive to errors in data pre processing e.g., normalization or background subtraction . In this study, a method based on grey relational analysis, a multi variable statistical method, is proposed to analyze and extract information from X ray spectroscopic data. As a showcase, the valence bands of microcrystalline silicon suboxides probed by hard X ray photoelectron spectroscopy HAXPES were investigated. The results obtained by the proposed method agree well with conventionally derived composition information e.g., curve fit of Si 2p core level of the silicon suboxides . Furthermore, the uncertainty of chemical compositions derived by the proposed method is smaller than that of traditional analysis methods e.g., the least square fit , when artificial linear functions are introduced to simulate the errors in data pre processing. This suggests that the proposed method is capable of providing more reliable and accurate results, especially for data containing significant noise contributions or that is subject to inconsistent data pre processing. Since the proposed method is less experience driven and error prone, it offers a novel approach for automate data analysis, which is of great interest for various applications, such as studying combinatorial material librarie

A Method for Identifying the Key Performance Shaping Factors to Prevent Human Errors during Oil Tanker Offloading Work

Acknowledgments: The authors would like to appreciate the experts and the engineers working in the Beihai Oil Terminal for their constructive supports during the development of this work. The authors would also like to thank the editors and the anonymous reviewers for their valuable comments.Peer reviewedPublisher PD

An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Purpose The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry. Design/methodology/approach To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers. Findings To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust. Research limitations/implications The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry. Originality/value This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications

Influencia de la metodología FMEA en la disponibilidad operativa de grúas telescópicas modelo R9130-2 de la Empresa Cosmos S.A

La presente investigación tuvo como objetivo general determinar la influencia de la metodología FMEA en la disponibilidad de grúas telescópicas modelo RT 9130-2 de la empresa Cosmos S.A. Para ello, empleó una metodología de enfoque cuantitativo, de nivel explicativo, de corte longitudinal, de diseño experimental. La población y muestra estuvieron conformadas por 4 grúas telescópicas RT 9130-2 durante un periodo de 12 meses en el año 2019. La técnica de recolección de datos fue la observación directa. Los resultados evidenciaron que el comportamiento de la disponibilidad operativa de grúas telescópicas modelo RT 9130-2 del periodo histórico del 2019, previo a la implementación de cambios fue deficiente, en tanto que en promedio solo alcanzaba una disponibilidad del 87.5%, ello se basa en gran presencia de fallas, lo cual reduce el tiempo medio entre fallas a 34.10 horas e incrementó el tiempo medio para las reparaciones a 4.85 horas. Finalmente, se concluye que gracias a la influencia de la metodología FMEA se incrementó la disponibilidad de grúas telescópicas modelo RT 9130-2 de la empresa Cosmos S.A, en tanto que se pasa de un valor de disponibilidad de 87.5% en promedio pre-test a 96.7% en promedio post-test; de igual forma, se observaron cambios favorables en el tiempo medio entre fallas (de 34.10 a 102.91 horas) y el tiempo medio para reparaciones (4.85 a 2.75 horas) en promedio de ambos escenarios.The current research had as a general objective to determine the influence of the FMEA methodology on the availability of telescopic cranes model R 9130-2 of the company Cosmos S.A. To do this, he used a methodology of quantitative approach, explanatory level, longitudinal cut, experimental design. The population and sample consisted of 4 RT 9130-2 telescopic cranes during a 12-month period in 2019. The data collection technique was direct observation. The results showed that the behavior of the operational availability of telescopic cranes model RT 9130-2 in the historical period of 2019, prior to the implementation of changes, was deficient, while on average it only reached an availability of 87.5%, this is based on great presence of failures, which reduces the mean time between failures to 34.10 hours and increased the mean time for repairs to 4.85 hours. Finally, it is concluded that the FMEA methodology increased the availability of telescopic cranes model RT 9130-2 of the company Cosmos SA, while going from an availability value of 87.5% in pre-test average to 96.7% in post-test average. test; Similarly, favorable changes were observed in the mean time between failures (from 34.10 to 102.91 hours) and the mean time to repairs (4.85 to 2.75 hours) on average for both scenarios

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

Advances in Fluid Power Systems

The main purpose of this Special Issue of “Advances in Fluid Power Systems” was to present new scientific work in the field of fluid power systems for hydraulic and pneumatic control of machines and devices used in various industries. Advances in fluid power systems are leading to the creation of new smart devices that can replace tried-and-true solutions from the past. The development work of authors from various research centres has been published. This Special Issue focuses on recent advances and smart solutions for fluid power systems in a wide range of topics, including: • Fluid power for IoT and Industry 4.0: smart fluid power technology, wireless 5G connectivity in fluid power, smart components, and sensors.• Fluid power in the renewable energy sector: hydraulic drivetrains for wind power and for wave and marine current power, and hydraulic systems for solar power. • Hybrid fluid power: hybrid transmissions, energy recovery and accumulation, and energy efficiency of hybrid drives.• Industrial and mobile fluid power: industrial fluid power solutions, mobile fluid power solutions, eand nergy efficiency solutions for fluid power systems.• Environmental aspects of fluid power: hydraulic water control technology, noise and vibration of fluid power components, safety, reliability, fault analysis, and diagnosis of fluid power systems.• Fluid power and mechatronic systems: servo-drive control systems, fluid power drives in manipulators and robots, and fluid power in autonomous solutions

ADVANCED RISK MANAGEMENT OF AN ARCTIC MARINE SEISMIC SURVEY OPERATION

This research is motivated by the lack of a robust risk management framework addressing the high risks in Arctic Marine Seismic Survey Operations (AMSSO), and the lack of transparent decision-making in Arctic shipping risk management globally. The literature review carried out herein reveals that the AMSSO and Arctic navigation involve significant risks caused by human elements and the unique features of this region. These known risk factors combine to constitute a ship-ice collision risk. This last represents the goal of the research investigation. With the complexity of the AMSSO system, three technical chapters are proposed to analyse and reduce the risks in the AMSSO. The first technical chapter deals with local risk analysis of the system. Herein, a Fuzzy Rule-based methodology is developed employing the probability distribution assessment in the form of belief degrees with Bayesian Network (BN) and Failure Mode and Effect Analysis (FMEA) for estimating the risk parameters of each hazard event using a computer-aided analysis. A case study of the application of the proposed risk model – Fuzzy Rule-based Bayesian Network (FRBN) –, in the Greenland, Iceland and Norwegian Seas (GNIS) AMSSO is carried out to identify the most critical hazard event in the prospect oil field. The second technical chapter deals with the global safety performance of the Ship-Ice Collision model dovetailing the Evidential Reasoning (ER) technique and Analytic Hierarchy Process (AHP) with the FRBN. A trial application of the global safety performance of the Ship-Ice Collision case in a prospect oil field is carried out to determine the safety level of AMSSO, measured against a developed benchmark risk. The outcome of the investigation reveals the Risk Influence Factor (RIF) of each hazard event in AMSSO. Since the risk level is far above the tolerable region of the developed benchmark risk, several Risk Control Options (RCOs) are investigated in the last technical chapter to reduce and control the critical risks. This technical chapter finalises the risk management framework developed in this research. In a trial application of reducing a critical risk in AMSSO, AHP-TOPSIS is utilised to find a balance between cost and benefit in selecting the most appropriate RCO at the heart of several RCOs and their associated criteria. The novelty of this research lies in the fact that it tackles the major concerns in risk analysis (concerns such as dynamic event risk analysis, hazard data uncertainties, and hazard event dependencies) of a complex system. More also, it adopts a hybrid methodology that offers a non-monotonic utility output to select the most appropriate RCO amongst several RCOs and conflicting criteria, to reduce the critical risks in AMSSO, in an economically viable strategy