Dynamic lifecycle cost modeling for adaptable design optimization of additively remanufactured aeroengine components

Additive manufacturing (AM) is being used increasingly for repair and remanufacturing of aeroengine components. This enables the consideration of a design margin approach to satisfy changing requirements, in which component lifespan can be optimized for different lifecycle scenarios. This paradigm requires lifecycle cost (LCC) modeling; however, the LCC models available in the literature consider mostly the manufacturing of a component, not its repair or remanufacturing. There is thus a need for an LCC model that can consider AM for repair/remanufacturing to quantify corresponding costs and benefits. This paper presents a dynamic LCC model that estimates cumulative costs over the in-service phase and a nested design optimization problem formulation that determines the optimal component lifespan range to minimize overall cost while maximizing performance. The developed methodology is demonstrated by means of an aeroengine turbine rear structure

A lifecycle cost-driven system dynamics approach for considering additive re-manufacturing or repair in aero-engine component design

Aero-engine component design decisions should consider re-manufacturing and/or repair strategies and their impact on lifecycle cost. Existing design approaches do not account for alternative production technologies such as the use of additive manufacturing in life extension processes. This paper presents a modeling and optimization methodology for examining the impact of design decisions in the early development stage on component lifecycle cost during the in-service phase while considering the potential use of additive manufacturing in life extension strategies. Specifically, a system dynamics model is developed to assess different end-of-life scenarios. Finally, an optimization problem is formulated and solved to minimize lifecycle cost with respect to design variables related to remanufacturing

Industrialization of Additive Manufacturing: Assessing the Impact of Excess Margins on Manufacturing Costs

The rapid industrialization of additive manufacturing (AM) has revealed significant challenges in terms of its position in the value chain. Since the technology has attained reasonable maturity, companies are now focusing on its economic viability to identify areas where AM can justifiably replace conventional manufacturing. Such decision supports can be provided by quantitative cost models which can highlight potential cost savings and increase in manufacturability. Most existing cost models do not consider the possible design advantage of AM, which may help companies save costs. One way is to systematically identify excess margins and quantify them in terms of their cost and manufacturability impact. In this paper, we use the concept of margins and their undesirable effect on performance as a proxy for quantifying the cost of overdesign. This can be used to justify the choice of the manufacturing method in a commercial setting. A simplified industrial example of an aeroengine component is used to demonstrate the approach. The example compares the impact of margins on manufacturability when using additive manufacturing as opposed to a conventional manufacturing (CM) methods such as casting

Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers

Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber’s modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature

Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer

External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design

Integrating additive manufacturing and repair strategies of aeroengine components in the computational multidisciplinary engineering design process

This paper presents a methodology for integrating failure and lifecycle analysis related to additive manufacturing in a computational multidisciplinary engineering design framework. The specific goal of this framework is to quantify the impact of component design decisions on system-level performance in order to assess alternative manufacturing, re-manufacturing and repair strategies from both technical and business perspectives. The ultimate objective of this research is to enable such considerations in the early product design phases, where sufficient degree of freedom exists to identify component design solutions that can facilitate and accommodate different manufacturing and repair techniques that impact the entire lifecycle. The developed methodology is demonstrated by means of a jet engine component where repair strategies are included as variables in the computational design process. Numerical results confirm that these strategies can be used to trade among design attributes such as lifecycle cost, weight, and performance

Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers

Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber’s modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature