Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

Manufacturing Process Related Abstracts

4 A Comparison of Neural Network and DOE-Regression Analysis for Predicting Resource Consumption of Manufacturing Processes

Authors: Frank Kuebler, Rolf Steinhilper

Abstract:

Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: design of experiments, Manufacturing Process, Regression analysis, Resource Efficiency, Artificial Neural Network

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3 Input-Output Analysis in Laptop Computer Manufacturing

Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

Abstract:

The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: Manufacturing Process, input-output analysis, monetary input-output model, laptop computer

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2 Texture Identification Using Vision System: A Method to Predict Functionality of a Component

Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

Abstract:

Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: Manufacturing Process, vision system, diamond stylus, texture identification

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1 Energy-Led Sustainability Assessment Approach for Energy-Efficient Manufacturing

Authors: Aldona Kluczek

Abstract:

In recent years, manufacturing processes have interacted with sustainability issues realized in the cost-effective ways that minimalize energy, decrease negative impacts on the environment and are safe for society. However, the attention has been on separate sustainability assessment methods considering energy and material flow, energy consumption, and emission release or process control. In this paper, the energy-led sustainability assessment approach combining the methods: energy Life Cycle Assessment to assess environmental impact, Life Cycle Cost to analyze costs, and Social Life Cycle Assessment through ‘energy LCA-based value stream map’, is used to assess the energy sustainability of the hardwood lumber manufacturing process in terms of technologies. The approach integrating environmental, economic and social issues can be visualized in the considered energy-efficient technologies on the map of an energy LCA-related (input and output) inventory data. It will enable the identification of efficient technology of a given process to be reached, through the effective analysis of energy flow. It is also indicated that interventions in the considered technology should focus on environmental, economic improvements to achieve energy sustainability. The results have indicated that the most intense energy losses are caused by a cogeneration technology. The environmental impact analysis shows that a substantial reduction by 34% can be achieved with the improvement of it. From the LCC point of view, the result seems to be cost-effective, when done at that plant where the improvement is used. By demonstrating the social dimension, every component of the energy of plant labor use in the life-cycle process of the lumber production has positive energy benefits. The energy required to install the energy-efficient technology amounts to 30.32 kJ compared to others components of the energy of plant labor and it has the highest value in terms of energy-related social indicators. The paper depicts an example of hardwood lumber production in order to prove the applicability of a sustainability assessment method.

Keywords: Manufacturing Process, Energy Efficiency, sustainability assessment, life cycle cost, energy life cycle assessment, social life cycle analysis

Procedia PDF Downloads 114