Minimize Production Loss in Device Testing via Condition-Based Equipment Maintenance

Jin, Tongdan; Mechehoul, Mahmoud

doi:10.1109/tase.2010.2046164

Cited by 22 publications

(4 citation statements)

References 23 publications

(28 reference statements)

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“…[19] goes a step forward, presenting a general architecture for enabling industrial telemaintenance comprising both supervision and remote maintenance of distributed equipment, applied to the notable use case of a large subway environment. Finally, [20] presents a more general-purpose condition-based maintenance solution applied to Automatic Test Equipment (ATE) to minimize the device testing cost. While it presents a solution that can be applied by interacting with devices providing self-diagnostic tests, its adoption seems to be limited to a testing environment, thus not designed for and validate in a distributed worldwide use case.…”

Section: Related Workmentioning

confidence: 99%

Smart Appliances and RAMI 4.0: Management and Servitization of Ice Cream Machines

Corradi

Giannelli

Lazzarini³

et al. 2019

IEEE Trans. Ind. Inf.

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1 -The widespread adoption of Information and Communication Technologies (ICT) is profoundly changing manufacturing. Several Internet-of-Things (IoT) and Industry 4.0 solutions deployed in production environments have pushed for standardization efforts, most notably Reference Architecture Model Industrie 4.0 (RAMI 4.0), typically focusing on smart factory environments. However, ICT evolution is also enabling novel smart appliance scenarios, where relatively cheap machines, connected and integrated, are deployed outside the typical industrial environment with a wide range of stakeholders involved. The paper reports about a real-world use case composed of more than 12000 ice cream machines connected worldwide and shows how, anticipating the state-of-the-art, the underlying design of the ICT platform presents many interesting similarities with RAMI 4.0. The integration of appliances in a smart value chain enables to develop novel services for different stakeholders, ranging from ice cream manufacturer and maintenance technicians to ice cream shop owners and final consumers. The important synergies with RAMI 4.0 and the extensive onthe-field validation make the proposed solution a compelling reference application, from which to draw useful and generally applicable guidelines for the development of future Industry 4.0 smart appliance platforms.

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Section: Related Workmentioning

confidence: 99%

Smart Appliances and RAMI 4.0: Management and Servitization of Ice Cream Machines

Corradi

Giannelli

Lazzarini³

et al. 2019

IEEE Trans. Ind. Inf.

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“…Therefore, degradation data-based reliability estimation has become a feasible and low-cost alternative used for estimating system reliability [1], [2]. Reliability estimation ultimately serves maintenance scheduling [3], [4]. Based on reliability estimation by degradation modeling, preventive maintenance work orders need to be timely triggered to minimize unscheduled downtime.…”

Section: Introductionmentioning

confidence: 99%

A Generalized Result for Degradation Model-Based Reliability Estimation

Zhou

2014

IEEE Trans. Automat. Sci. Eng.

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“…Even in the limited works modeling the degradation process with time‐varying mean and variance (e.g. ), the fluctuation of the degradation is not used as a performance variable to define the failure. Thus, how to estimate RUL for systems with time‐varying mean and variance is still not well solved.…”

Section: Introductionmentioning

confidence: 99%

Remaining Useful Life Estimation for Systems with Time‐varying Mean and Variance of Degradation Processes

Zhang

et al. 2014

Quality & Reliability Eng

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This paper focuses on the problem of how to estimate remaining useful life (RUL) for a class of systems with high fluctuating dagradation caused by time‐varying mean and variance. In engineering practice, the fluctuation of the degradation data can reflect the system stability, and hence it can serve as an additional indicator for the system's health state in addition to the degradation observations. To estimate the RUL for this class of systems, three issues should be considered jointly: (i) how to model the degradation data with high fluctuation, (ii) how to define an indicator denoting the fluctuation's level, and (iii) how to combine the degradation path and the fluctuation for the RUL estimating task. In responses to the above issues, this paper characterizes the degree of the fluctuation by the standard deviation of the stochastic degradation process and defines the standard deviation as an additional performance variable. Moreover, a stochastic degradation model is proposed to reflect the high fluctuating degradation data, in which the standard deviation is time dependent. To obtain the marginal distribution of the RUL derived by the standard deviation, the failure threshold of the standard deviation is given according to its influence on the degradation process. Another marginal distribution derived by the degradation data is also obtained by the time distribution of the degradation process crossing the degradation threshold. Then, through deriving the correlation between the two marginal distributions based on the probability theory, the joint distribution of the RUL is obtained. Finally, a practical case study for gyro is conducted. The results demonstrate the feasibility and applicability of the proposed model. Copyright © 2014 John Wiley & Sons, Ltd.

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Minimize Production Loss in Device Testing via Condition-Based Equipment Maintenance

Cited by 22 publications

References 23 publications

Smart Appliances and RAMI 4.0: Management and Servitization of Ice Cream Machines

Smart Appliances and RAMI 4.0: Management and Servitization of Ice Cream Machines

A Generalized Result for Degradation Model-Based Reliability Estimation

Remaining Useful Life Estimation for Systems with Time‐varying Mean and Variance of Degradation Processes

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