Sustainable Manufacturing Analysis Using Activity Based Costing in SysML

2011 ◽  
Author(s):  
Yuriy Romaniw ◽  
Bert Bras ◽  
Tina Guldberg
Keyword(s):  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Functional Model ◽  
Object Oriented ◽  
Analysis Tool ◽  
Activity Based Costing ◽  
Multiple Perspectives ◽  
Multi Scale ◽  
Scale Modeling ◽  
Validation Experiment

This paper outlines an approach for dynamic, multi-scale modeling of manufacturing systems using an Activity Based Cost structure. The purpose of these models is to assess the sustainability of the manufacturing system and aid as a quick, first principle analysis tool for comparing alternatives. The models are constructed using a computer-aided version of the object oriented modeling language SysML. The model, known as the Activity Based Object Oriented Manufacturing Model (or ABOOM Model), is capable of decomposing a system from multiple perspectives, using the same library of activities reducing redundancy and complexity while increasing modularity. The model is built in MagicDraw SysML, using ParaMagic and Mathematica to parse and simulate the model and return numerical results. This paper builds on a project previously presented in its infancy at IDETC/CIE 2009. This paper presents a functional model structure now that the project has matured and nears the next phase of implementation. Executable hypothetical case study instance structures are presented as well as results from a validation experiment performed since the project was first presented. This paper summarizes the results from the case studies as well as the conclusions from the validation experiment.

Multi-Scale Modeling of Cementitious Materials (Briefing Chart)

2014 ◽  
Author(s):  
M. M. Shahzamanian ◽  
T. Tadepalli ◽  
A. M. Rajendran ◽  
W. D. Hodo ◽  
R. Mohan ◽  
...  
Keyword(s):  
Cementitious Materials ◽  
Multi Scale ◽  
Scale Modeling ◽  
Multi Scale Modeling

scholarly journals A mathematical model for designing a reliable cellular hybrid manufacturing-remanufacturing system considering alternative and contingency process routings

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Amirreza Hooshyar Telegraphi ◽  
Akif Asil Bulgak
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Manufacturing Systems ◽  
Closed Loop ◽  
Sustainable Manufacturing ◽  
Critical Issue ◽  
Economic Benefits ◽  
Mixed Integer ◽  
Hybrid Manufacturing ◽  
Closed Loop Supply Chain

AbstractDue to the stringent awareness toward the preservation and resuscitation of natural resources and the potential economic benefits, designing sustainable manufacturing enterprises has become a critical issue in recent years. This presents different challenges in coordinating the activities inside the manufacturing systems with the entire closed-loop supply chain. In this paper, a mixed-integer mathematical model for designing a hybrid-manufacturing-remanufacturing system in a closed-loop supply chain is presented. Noteworthy, the operational planning of a cellular hybrid manufacturing-remanufacturing system is coordinated with the tactical planning of a closed-loop supply chain. To improve the flexibility and reliability in the cellular hybrid manufacturing-remanufacturing system, alternative process routings and contingency process routings are considered. The mathematical model in this paper, to the best of our knowledge, is the first integrated model in the design of hybrid cellular manufacturing systems which considers main and contingency process routings as well as reliability of the manufacturing system.

scholarly journals Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Weixin Xu ◽  
Huihui Miao ◽  
Zhibin Zhao ◽  
Jinxin Liu ◽  
Chuang Sun ◽  
...  
Keyword(s):  
Tool Wear ◽  
Information Technologies ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Wear Prediction ◽  
Multi Scale ◽  
Tool Wear Prediction ◽  
Machine Health Monitoring ◽  
Gated Recurrent Unit ◽  
Unit Network

AbstractAs an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry. In this paper, a multi-scale Convolutional Gated Recurrent Unit network (MCGRU) is proposed to address raw sensory data for tool wear prediction. At the bottom of MCGRU, six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network, which augments the adaptability to features of different time scales. These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations. At the top of the MCGRU, a fully connected layer and a regression layer are built for cutting tool wear prediction. Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.

Multi-Scale Modeling of Neural Structure in X-Ray Imagery

2021 ◽  
Author(s):  
Aishwarya Balwani ◽  
Joseph Miano ◽  
Ran Liu ◽  
Lindsey Kitchell ◽  
Judy A. Prasad ◽  
...  
Keyword(s):  
Neural Structure ◽  
X Ray ◽  
Multi Scale ◽  
Scale Modeling ◽  
Multi Scale Modeling
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