A Design Framework for Bi-Level Estimation of Machining Energy for Parts and Assemblies

2009 ◽  
Author(s):  
Gaurav Ameta ◽  
Mahesh Mani ◽  
He Huang
Keyword(s):  
Energy Range ◽  
Asset Management ◽  
Design Stage ◽  
Design Strategies ◽  
Energy Estimation ◽  
Planning And Scheduling ◽  
Early Design ◽  
Early Design Stage ◽  
Negative Impacts ◽  
Manufacturing Stage

This paper presents a framework and approach for the computation of machining energy for parts and assemblies, at two levels — early design stage and manufacturing stage. Energy estimation at an early design stage can be useful for redesign strategies and improving manufacturing efficiency. At the manufacturing stage, energy estimations allow for asset management based on energy efficient process planning and scheduling, thereby reducing the negative impacts of the product to the environment. To facilitate the computation of the machining energy, at an early design stage, we first automate the process of identifying the material removal volume for machining operations for a given part. We subsequently use the identified removal volume together with the material specific data to compute an energy range for manufacturing the part. For an assembly, the above computations for individual parts are aggregated to arrive at the final energy range. The proposed method allows the identification of energy intensive parts/features based on the percent contribution, thereby assisting re-design strategies. We additionally explore the application of statistical analysis and allocation principles to identify priority re-design parts. In this paper, we limit our product re-design discussions based on form (geometry and shape) and material. Future extensions will potentially also include manufacturing process optimization. Although the framework presented in this paper is currently applied only to milled parts and assemblies, it can also be extended to other machining methods.

Towards a Design Framework for Bi-Level Estimation of Turning Energy for Parts and Assemblies

2009 ◽  
Author(s):  
He Huang ◽  
Gaurav Ameta
Keyword(s):  
Design Stage ◽  
Computational Framework ◽  
Energy Estimation ◽  
Planning And Scheduling ◽  
Early Design ◽  
Early Design Stage ◽  
Machined Parts ◽  
Percent Contribution ◽  
Turned Parts ◽  
Manufacturing Stage

This paper presents a computational framework for calculating turning energy for parts and assemblies, at two levels — early design stage and manufacturing stage. At the early design stage such energy estimation can be used to redesign the part and assemblies for manufacturing energy efficiency. At the manufacturing stage, allocation of resources based on energy efficient process planning and scheduling aids in reducing the carbon emissions of the product due to manufacturing energy production. For computing the turning energy, at the early design stage, first removal volume for turning operations for a part is identified. Then, material data and the removal volume are used to calculate a range of turning energy for manufacturing the part. If dealing with an assembly, then the above computations are applied to each individual parts and total turning energy is computed for the assembly. Energy hogging parts/features are identified based on percent contribution, which is then used to suggest parts for re-design. Application of statistical analysis and allocation of turning energy for identifying re-design parts is also explored. Re-design at the early design stage is performed at two levels — form (geometry and shape) and material. At the manufacturing stage, turning energy calculations can be utilized for optimizing the process plans. Although the framework presented in this paper is applied only to turned parts and assemblies, it can also be applied to machined parts and assemblies.

Towards a Computational Framework for Energy Estimation: Needs, Requirements, and Its Generic Shell

2010 ◽  
Author(s):  
He Huang ◽  
Gaurav Ameta
Keyword(s):  
Energy Consumption ◽  
Asset Management ◽  
Product Life Cycle ◽  
Manufacturing Industry ◽  
Raw Materials ◽  
Computational Framework ◽  
Energy Estimation ◽  
Planning And Scheduling ◽  
Cad Cam ◽  
Negative Impacts

Excessive energy consumption has become a worldwide issue in today’s design and manufacturing industry. A framework for estimating energy consumption that could later be used to integrate with CAD/CAM systems is in demand. This paper initially presents needs and requirements for a computational framework to estimate energy consumption during a product life-cycle, i.e., from extraction of raw materials to recycling or disposal. Energy estimations allow for asset management, thereby reducing the negative impacts of the product to the environment. At the manufacturing stage, asset management can be based on energy efficient process planning and scheduling. As a first step, the research presented in this paper proposes a framework that represents a generic shell for computing energy.

A Dynamic Analysis Of The Impact Of Air Pollution On The daylight Availability In An Open-plan Office In London

2021 ◽  
pp. 94-103
Author(s):  
Jiangtao Du ◽  
Steve Sharples
Keyword(s):  
Air Pollution ◽  
Urban Areas ◽  
Simulation Analysis ◽  
Design Stage ◽  
Design Strategies ◽  
Early Design Stage ◽  
Pollutant Deposition ◽  
Open Plan ◽  
Building Project ◽  
The Impact

The deposition of air pollutants on glazing can significantly affect the daylight transmittance of building fenestration systems in urban areas. This study presents a simulation analysis of the impact of air pollution and glazing visual transmittance on indoor daylight availability in an open-plan office in London. First, the direct links between glazing visual transmittance and daylighting conditions were developed and assessed. Second, several simple algorithms were established to estimate the loss of daylight availability due to the pollutant deposition at the external surface of vertical glazing. Finally, some conclusions and design strategies to support facade planning at the early design stage of an urban building project were developed.

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

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