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Related Concept Videos

Insulation Coordination01:23

Insulation Coordination

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Insulation coordination is the process of matching electric equipment's insulation strength with protective device characteristics to protect the equipment against expected overvoltages. This selection is based on engineering judgment and cost. Equipment can generally withstand short-duration high transient overvoltages, but repeated tests with identical waveforms can yield inconsistent results. As a result, standard impulse voltage waveforms are used for testing, defined by specific times...
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Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
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An Integrated Risk-Informed Multicriteria Approach for Determining Optimal Inspection Periods for Protective Sensors.

Ricardo J G Mateus1, Rui Assis1, Pedro Carmona Marques1

  • 1RCM2+ Research Centre for Asset Management and Systems Engineering, Lusófona University, Campo Grande, 376, 1749-024 Lisboa, Portugal.

Sensors (Basel, Switzerland)
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Summary

This study introduces a new method for optimizing protective sensor inspection intervals, balancing costs and equipment availability. The optimal period found was 90 hours, improving upon traditional methods.

Keywords:
inspection periodmaintenancemulticriteriaoptimization-simulationprobability managementrisksensors

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Area of Science:

  • Industrial Engineering
  • Operations Research
  • Reliability Engineering

Background:

  • Equipment failure causes significant industrial disruption, with unplanned downtime costing up to 11% of manufacturing revenue.
  • Proactive maintenance, including protective sensors, is crucial, but sensors themselves can fail hiddenly, necessitating inspections.
  • Existing inspection strategies often lack economic considerations and uncertainty analysis.

Purpose of the Study:

  • To develop an integrated, multi-methodological approach for determining optimal inspection periods for protective sensors subject to hidden failures.
  • To evaluate inspection periods based on risk-informed overall values, considering multiple Key Performance Indicators (KPIs).
  • To select the optimal inspection period by accounting for uncertainties and organizational preferences.

Main Methods:

  • Combined discrete event simulation, Monte Carlo simulation, optimization, risk analysis, and multicriteria decision analysis.
  • Developed a novel approach to evaluate inspection periods using risk-informed values and multiple conflicting KPIs.
  • Implemented a decision support system in Microsoft Excel based on probability management principles.

Main Results:

  • Identified an optimal inspection period of 90 hours for protective sensors, a compromise between maintenance costs and equipment availability.
  • This contrasts with a 120-hour interval derived from cost minimization alone, demonstrating the value of integrated decision-making.
  • Sensitivity analysis confirmed the solution's robustness, with validity across a wide range of organizational weightings for equipment availability (35%-82%).

Conclusions:

  • The proposed integrated approach provides quantitatively superior maintenance cost and availability outcomes compared to empirical standards.
  • Integrating organizational preferences into the decision process is vital for selecting truly optimal inspection intervals.
  • The developed decision support system offers an open, transparent, and auditable tool for practical application in industrial settings.