scholarly journals Condition Based Maintenance Optimization of an Aircraft Assembly Process Considering Multiple Objectives

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
J. Li ◽  
T. Sreenuch ◽  
A. Tsourdos
Keyword(s):  
Production Rate ◽  
Scatter Search ◽  
Condition Based Maintenance ◽  
Design Solution ◽  
Maintenance Cost ◽  
Assembly Process ◽  
Commercial Aircraft ◽  
Final Assembly ◽  
Trade Offs ◽  
Complex Process

The Commercial Aircraft Cooperation of China (COMAC) ARJ21 fuselage’s final assembly process is used as a case study. The focus of this paper is on the condition based maintenance regime for the (semi-) automatic assembly machines and how they impact the throughput of the fuselage assembly process. The fuselage assembly process is modeled and analyzed by using agent based simulation in this paper. The agent approach allows complex process interactions of assembly, equipment, and maintenance to be captured and empirically studied. In this paper, the built network is modeled as the sequence of activities in each stage, which are parameterized by activity lead time and equipment used. A scatter search is used to find multiobjective optimal solutions for the CBM regime, where the maintenance related cost and production rate are the optimization objectives. In this paper, in order to ease computation intensity caused by running multiple simulations during the optimization and to simplify a multiobjective formulation, multiple Min-Max weightings are used to trace Pareto front. The empirical analysis reviews the trade-offs between the production rate and maintenance cost and how sensitive the design solution is to the uncertainties.

Optimizing the Cost and Reliability of Shared Anchors in an Array of Floating Offshore Wind Turbines

2021 ◽  
Author(s):  
Michael Devin ◽  
Bryony DuPont ◽  
Spencer Hallowell ◽  
Sanjay Arwade
Keyword(s):  
Optimization Algorithm ◽  
System Reliability ◽  
Failure Modes ◽  
The United States ◽  
Offshore Wind ◽  
Bayesian Optimization ◽  
Maintenance Cost ◽  
Offshore Wind Turbine ◽  
Trade Offs ◽  
Floating Offshore Wind Turbines

Abstract Commercial floating offshore wind projects are expected to emerge in the United States by the end of this decade. Currently, however, high costs for the technology limit its commercial viability, and a lack of data regarding system reliability heightens project risk. This work presents an optimization algorithm to examine the trade-offs between cost and reliability for a floating offshore wind array that uses shared anchoring. Combining a multivariable genetic algorithm with elements of Bayesian optimization, the optimization algorithm selectively increases anchor strengths to minimize the added costs of failure for a large floating wind farm in the Gulf of Maine under survival load conditions. The algorithm uses an evaluation function that computes the probability of mooring system failure, then calculates the expected maintenance costs of a failure via a Monte Carlo method. A cost sensitivity analysis is also performed to compare results for a range of maintenance cost profiles. The results indicate that virtually all of the farm's anchors are strengthened in the minimum cost solution. Anchor strength is in- creased between 5-35% depending on farm location, with anchor strength nearest the export cable being increased the most. The optimal solutions maintain a failure probability of 1.25%, demonstrating the trade-off point between cost and reliability. System reliability was found to be particularly sensitive to changes in turbine costs and downtime, suggest- ing further research into floating offshore wind turbine failure modes in extreme loading conditions could be particularly impactful in reducing project uncertainty.

Technical and Engineering Decisions That Drive Choices for Predictive Analytics of Plant Data

2011 ◽  
Author(s):  
William Nieman
Keyword(s):  
Real Time ◽  
Predictive Analytics ◽  
Current Data ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Real Time Systems ◽  
Efficient Technology ◽  
Time Model ◽  
Trade Offs ◽  
Time Systems

Power generation has the goal of maximizing power output while minimizing operations and maintenance cost. The challenge for plant manager is to move closer to reliability limits while being confident the risks of any decision are understood. To attain their goals and meet this challenge they are coming to realize that they must have frequent, accurate assessment of equipment operating conditions, and a path to continued innovation-. At a typical plant, making this assessment involves the collection and effective analysis of reams of complex, interrelated production system data, including demand requirements, load, ambient temperature, as well as the dependent equipment data. Wind turbine health and performance data is available from periodic and real-time systems. To obtain the timeliest understanding of equipment health for all the key resources in a large plant or fleet, engineers increasingly turn to real-time, model-based solutions. Real-time systems are capable of creating actionable intelligence from large amounts and diverse sources of current data. They can automatically detect problems and provide the basis for diagnosis and prioritization effectively for many problems, and they can make periodic inspection methods much more efficient. Technology exists to facilitate prediction of when assets will fail, allowing engineers to target maintenance costs more effectively. But, it is critical to select the best predictive analytics for your plant. How do you make that choice correctly? Real-time condition monitoring and analysis tools need to be matched to engineering process capability. Tools are employed at the plant in lean, hectic environments; others are deployed from central monitoring centers charged with concentrating scarce resources to efficiently support plants. Applications must be flexible and simple to implement and use. Choices made in selection of new tools can be very important to future success of plant operations. So, these choices require solid understanding of the problems to be solved and the advantages and trade-offs of potential solutions. This choice of the best Predictive Analytic solution will be discussed in terms of key technology elements and key engineering elements.

Optimization of the installation sequence for the temporary fasteners in the aircraft industry

2021 ◽  
pp. 1-25
Author(s):  
Tatiana Pogarskaia ◽  
Sergey Lupuleac ◽  
Julia Shinder ◽  
Philipp Westphal
Keyword(s):  
Combinatorial Problem ◽  
Hole Drilling ◽  
Assembly Process ◽  
Process Verification ◽  
Final Assembly ◽  
Uncertain Input ◽  
Uncertain Input Data ◽  
Aircraft Production

Abstract Riveting and bolting are common assembly methods in aircraft production. The fasteners are installed immediately after hole drilling and fix the relative tangential displacements of the parts, that took place. A proper fastener sequence installation is very important because a wrong one can lead to a “bubble-effect”, when gap between parts after fastening becomes larger in some areas rather than being reduced. This circumstance affects the quality of the final assembly. For that reason, the efficient methods for determination of fastening sequence taking into account the specifics of the assembly process are needed. The problem is complicated by several aspects. First of all, it is a combinatorial problem with uncertain input data. Secondly, the assembly quality evaluation demands the time-consuming computations of the stress-strain state of the fastened parts caused by sequential installation of fasteners. Most commonly used strategies (heuristic methods, approximation algorithms) require a large number of computational iterations what dramatically complicates the problem. The paper presents the efficient methods of fastener sequence optimization based on greedy strategy and the specifics of the assembly process. Verification of the results by comparison to commonly used installation strategies shows its quality excellence.

2309 Human Error and Production Rate Correlation in Assembly Process of Electronics Goods

2014 ◽  
Vol 2014.24 (0) ◽  
pp. _2309-1_-_2309-6_
Author(s):  
Adi SAPTARI ◽  
Jia Xin LEAU ◽  
Poh Kiat NG ◽  
Effendi MOHAMAD
Keyword(s):  
Production Rate ◽  
Human Error ◽  
Assembly Process ◽  
Rate Correlation

CBM Integrated Maintenance Scheduler

2008 ◽  
Author(s):  
Simon Jessop ◽  
Scott Valentine ◽  
Michael Roemer
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Open Systems ◽  
Software Tool ◽  
Condition Based Maintenance ◽  
Maintenance Cost ◽  
Future Health ◽  
Support Tool ◽  
System Readiness ◽  
The Right

Condition Based Maintenance (CBM) is a key technology enabling facility maintenance cost reduction. The CBM approach to maintenance replaces rigid time-based maintenance schedules with the “right maintenance at the right time” identified by real-time equipment health monitoring. This approach creates a new requirement for determining the best time to schedule newly identified critical maintenance actions in light of the real world constraints of available labor and resources. One of the major challenges encountered when attempting to optimize a maintenance schedule is related to the resolution of the many and often complex interdependencies or constraints present throughout the maintenance process. This paper presents a CBM decision support software tool that leverages real-time current and future health condition information to optimize maintenance resources, tasking, and planning in order to maximize the system readiness. Over the past year Impact Technologies, under contract by NAVSEA, has been developing technologies that will provide the necessary decision support tools to address this dynamic maintenance environment. The software scheduling tool utilizes an Open Systems Architecture for Condition-Based Maintenance (OSA-CBM) architecture to facilitate implementation into new or legacy systems. The tool employs a generic maintenance model that accounts for equipment reliability attributes, maintenance task material and labor requirements, system dependencies, and subsystems relationships. The focus of the development has been on Naval Ship maintenance, but the model inputs can be adapted to a variety of applications including power generators, aircraft, ships, and production facilities. The core of the decision support tool is a multi-sweep optimization algorithm that is tuned to the maintenance scheduling problem. The algorithm has been designed to achieve the best computational speed. Benefits and risks of maintenance decisions have been quantified in risk, which can be defined in terms of readiness or financial. The probability and consequence of each system failure are considered in light of the complex system interdependencies, such as dependant and redundant systems, to achieve the best overall system readiness. Novel post-processing steps identify the active solution constraints further enhancing the user’s ability to understand the issues that affect system availability.

scholarly journals Science should not be left behind during the design of a marine protected area: meeting conservation priorities while integrating stakeholder interests

FACETS ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 472-492 ◽  
Author(s):  
Manuel Muntoni ◽  
Rodolphe Devillers ◽  
Mariano Koen-Alonso
Keyword(s):  
Marine Protected Areas ◽  
Planning Process ◽  
Marine Protected Area ◽  
Extractive Industries ◽  
Conservation Priorities ◽  
Conservation Priority ◽  
Left Behind ◽  
Stakeholder Interests ◽  
Trade Offs ◽  
Complex Process

Marine protected areas (MPAs) design is a complex process that typically involves diverse stakeholders, requiring compromise between diverging priorities. Such compromises, when not carefully understood, can threaten the ecological effectiveness of MPAs. Using the example of the Canadian Laurentian Channel MPA, we studied a planning process from initial scientific advice to the final MPA. We analysed the impacts of successive boundary modifications to the draft MPA, often made to accommodate extractive industries, on the protection of seven species initially identified as potential conservation priorities. We also quantified the potential economic impacts of changes in boundary modifications on the fisheries industry. Results show that reducing the proposed MPA size by 33.4% helped reduce the potential economic impact on the fishing industry by 65.5%, but it resulted in up to 43% decrease in protection of species of conservation priority. Changes in MPA boundary delineation during the design were not subjected to formal scientific reviews, raising questions on the potential effectiveness of this MPA. Better integration of science in MPA design is required to help assess the impacts that trade-offs made during stakeholder consultations can have on the MPA ecological effectiveness.

A Fixture Failure Control Chart for Variation Caused by Assembly Fixtures

2012 ◽  
Author(s):  
Kristina Wärmefjord ◽  
Johan S. Carlson
Keyword(s):  
Fault Diagnosis ◽  
Case Studies ◽  
Control Chart ◽  
Assembly Process ◽  
Final Assembly ◽  
Sources Of Variation ◽  
Auto Body ◽  
Different Sources

In the auto body assembly process, fixtures are used to position parts during assembly and inspection. If there is variation in the positioning process, this will propagate to the final assembly. There are also other sources of variation in the final assembly, such as variation in parts due to previous manufacturing steps. To facilitate the separation of the different sources of variation, and thereby also improve fault diagnosis, a fixture failure subspace control chart is proposed. This control chart is based on a multivariate T2-chart, but only variations in the fixture failure subspace are considered. The method is applied to two industrial case studies with satisfying results.

scholarly journals Optimal Design of a Residential Photovoltaic Renewable System in South Korea

2019 ◽  
Vol 9 (6) ◽  
pp. 1138 ◽  
Author(s):  
Hyunkyung Shin ◽  
Zong Geem
Keyword(s):  
Optimal Design ◽  
South Korea ◽  
Piecewise Linear ◽  
Design Model ◽  
Design Solution ◽  
Maintenance Cost ◽  
Pv System ◽  
Local Optima ◽  
Pv Systems ◽  
Electricity Bill

An optimal design model for residential photovoltaic (PV) systems in South Korea was proposed. In the optimization formulation, the objective function is composed of three costs, including the monthly electricity bill, the PV system construction cost (including the government’s subsidy), and the PV system maintenance cost. Here, because the monthly electricity bill is not differentiable (it is a stepped piecewise linear function), it cannot be solved by using traditional gradient-based approaches. For details considering the residential electric consumption in a typical Korean household, consumption was broken down into four types (year-round electric appliances, seasonal electric appliances, lighting appliances, and stand-by power). For details considering the degree of PV generation, a monthly generation dataset with different PV tilt angles was analyzed. The optimal design model was able to obtain a global design solution (PV tilt angle and PV size) without being trapped in local optima. We hope that this kind of practical approach will be more frequently applied to real-world designs in residential PV systems in South Korea and other countries.

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