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Adaptive Method for Rapid Product Development from Unorganised Point Cloud Data For Rapid ProtoType Development (RPD) one of the prerequisites is a solid model. In reverse engineering, point cloud data is converted into surface model which is finally converted into solid model to subsequently generate a STL file for use on rapid prototype machine. This is a time consuming activity. Hence for integrating two processes, ie, reverse engineering and rapid prototyping, the point cloud data is directly converted into surface model without generating surface model using conventional surface modelling techniques. Preprocessing activities like noise removal, segmentation and triangulation are the basic steps required for the direct generation of STL file using point cloud data. Point cloud data is obtained using contact as well as non contact scanners.Data obtained from continuous contact scanner is converted into STL file using matrix triangulation1,2 and conversion of scattered data obtained from laser scanner into STL file is possible using Octree segmentation followed by Delaunay triangulation3,4. Matrix method being simple is suitable only for organized data which is obtained from continuous contact scanner. However combination of Octree segmentation and Delaunay triangulation show certain disadvantages when used in combination for laser data. In this paper a new combination is introduced for the generation of STL file. In this combination, proposed row-column technique is developed to convert unorganized data into organized data which have been arranged into the matrix format and then matrix triangulation is performed to achieve triangulation and generation of STL file. 2 Decision Making for Material Handling Equipment Selection using ELECTRE II Method Material handling equipment (MHE) is the most important part of today's manufacturing systems and is increasingly playing a crucial role in enhancing the productivity of the entire manufacturing organization. Use of proper MHE can aid the manufacturing process, provide effective utilization of manpower, increase production and improve system flexibility. Selection of the most suitable MHE is a very difficult task for the manufacturing organizations because of the considerable capital investment required. It is also challenging to the decision maker due to the presence of many feasible alternatives and conflicting objectives. Different multi-criteria decision-making (MCDM) methods have been observed to be quite useful to analyze and solve the MHE selection problems.These MCDM methods can evaluate and rank the available candidate alternatives based on various conflicting criteria. This paper mainly attempts to explore the applicability and potentiality of an outranking method-based MCDM technique, ie, ELECTRE II (ELimination and Et Choice Translating REality) method for effective MHE selection decision. Two real time examples are presented to validate the performance of ELECTRE II method. It is observed that in both the cases, the top-ranked MHE alternatives exactly match with those derived by the past researchers. 3 Driving Comfort Factor to Assess Perceived Comfort based on Experimental Analysis The paper deals with the issue of subjective rating system of comfort assessment being used at present and the need to develop an objective technique of comfort measurement through combined threshold ‘Comfort Index’.Using various experiments, logical approach and simulation techniques the authors define a new threshold value of the comfort index which could be used to assess and compare various passenger cars for perceived comfort. This will undoubtedly help the designers to analyze their concepts early in design and development program which will result in comfortable driving experience for drivers. 4 Evaluation of Machine Learning Process This paper deals with the machine learning phenomenon. Here, an attempt has been made to determine the progress elasticity and learning of a machine. Here authors, based on the quantitative technique of relative risk reliability index (R3I), determined vibration as the most critical factor compared to dimensional tolerance and surface roughness in predicting the machine learning index.Overall learning index has been determined based on amplitude of vibration. Progress elasticity of the machining operation has been evaluated. The authors also suggests a quantitative method of evaluation in determining overall learning index. 5 Need for Integrated Implementation of Lean Manufacturing and Six Sigma for Small and Medium Scale Industries : A Detailed Survey All the manufactured products can be classified as standard, innovative and hybrid products and can be manufactured in either Lean or Agile environment. Leanness means reduced time across the value chain. Agility means grabbing market opportunities by absorbing fluctuation in demand. Six Sigma means 3.4 defects per million opportunities. The goal of supply chain management is to provide suppliers and customers a window into their supply chain so that they can reduce inventory, better utilize plant capacity and cut communication costs.In the literature review, some of the important literature about Six Sigma, Lean manufacturing and SCM are studied. These three techniques are being studied from small and medium scale industries development point of view. In future, some standard procedures may be developed for effective combination of the above techniques which would help in running small and medium scale industries in a better fashion, ultimately leading to developed entrepreneurship, developed society, developed nation and developed world. 6 Selection of Flexible Manufacturing Systems using Data Envelopment Analysis The present competitive environment in global market has forced the manufacturing organizations to reduce costs while improving the quality of products and responsiveness to the customers. Flexible manufacturing systems (FMS) offer opportunities to those organizations to improve their technology, competitiveness and profitability through a highly proficient and focused approach to manufacturing effectiveness. The decision makers often face the problem of selecting the most appropriate FMS for a given manufacturing organization. This paper attempts to solve this FMS selection problem in two steps.The first step is used to identify and shortlist the most efficient alternative flexible manufacturing systems having better performance characteristics using the Charnes, Cooper and Rhodes (CCR) model of data envelopment analysis (DEA). Then, the weighted overall efficiency ranking method of multi-attribute decision-making (MADM) theory is employed to determine the best FMS from the shortlisted ones. The results match well with those obtained by the past researchers.
Adaptive Method for Rapid Product Development from Unorganised Point Cloud Data For Rapid ProtoType Development (RPD) one of the prerequisites is a solid model. In reverse engineering, point cloud data is converted into surface model which is finally converted into solid model to subsequently generate a STL file for use on rapid prototype machine. This is a time consuming activity. Hence for integrating two processes, ie, reverse engineering and rapid prototyping, the point cloud data is directly converted into surface model without generating surface model using conventional surface modelling techniques. Preprocessing activities like noise removal, segmentation and triangulation are the basic steps required for the direct generation of STL file using point cloud data. Point cloud data is obtained using contact as well as non contact scanners.Data obtained from continuous contact scanner is converted into STL file using matrix triangulation1,2 and conversion of scattered data obtained from laser scanner into STL file is possible using Octree segmentation followed by Delaunay triangulation3,4. Matrix method being simple is suitable only for organized data which is obtained from continuous contact scanner. However combination of Octree segmentation and Delaunay triangulation show certain disadvantages when used in combination for laser data. In this paper a new combination is introduced for the generation of STL file. In this combination, proposed row-column technique is developed to convert unorganized data into organized data which have been arranged into the matrix format and then matrix triangulation is performed to achieve triangulation and generation of STL file. 2 Decision Making for Material Handling Equipment Selection using ELECTRE II Method Material handling equipment (MHE) is the most important part of today's manufacturing systems and is increasingly playing a crucial role in enhancing the productivity of the entire manufacturing organization. Use of proper MHE can aid the manufacturing process, provide effective utilization of manpower, increase production and improve system flexibility. Selection of the most suitable MHE is a very difficult task for the manufacturing organizations because of the considerable capital investment required. It is also challenging to the decision maker due to the presence of many feasible alternatives and conflicting objectives. Different multi-criteria decision-making (MCDM) methods have been observed to be quite useful to analyze and solve the MHE selection problems.These MCDM methods can evaluate and rank the available candidate alternatives based on various conflicting criteria. This paper mainly attempts to explore the applicability and potentiality of an outranking method-based MCDM technique, ie, ELECTRE II (ELimination and Et Choice Translating REality) method for effective MHE selection decision. Two real time examples are presented to validate the performance of ELECTRE II method. It is observed that in both the cases, the top-ranked MHE alternatives exactly match with those derived by the past researchers. 3 Driving Comfort Factor to Assess Perceived Comfort based on Experimental Analysis The paper deals with the issue of subjective rating system of comfort assessment being used at present and the need to develop an objective technique of comfort measurement through combined threshold ‘Comfort Index’.Using various experiments, logical approach and simulation techniques the authors define a new threshold value of the comfort index which could be used to assess and compare various passenger cars for perceived comfort. This will undoubtedly help the designers to analyze their concepts early in design and development program which will result in comfortable driving experience for drivers. 4 Evaluation of Machine Learning Process This paper deals with the machine learning phenomenon. Here, an attempt has been made to determine the progress elasticity and learning of a machine. Here authors, based on the quantitative technique of relative risk reliability index (R3I), determined vibration as the most critical factor compared to dimensional tolerance and surface roughness in predicting the machine learning index.Overall learning index has been determined based on amplitude of vibration. Progress elasticity of the machining operation has been evaluated. The authors also suggests a quantitative method of evaluation in determining overall learning index. 5 Need for Integrated Implementation of Lean Manufacturing and Six Sigma for Small and Medium Scale Industries : A Detailed Survey All the manufactured products can be classified as standard, innovative and hybrid products and can be manufactured in either Lean or Agile environment. Leanness means reduced time across the value chain. Agility means grabbing market opportunities by absorbing fluctuation in demand. Six Sigma means 3.4 defects per million opportunities. The goal of supply chain management is to provide suppliers and customers a window into their supply chain so that they can reduce inventory, better utilize plant capacity and cut communication costs.In the literature review, some of the important literature about Six Sigma, Lean manufacturing and SCM are studied. These three techniques are being studied from small and medium scale industries development point of view. In future, some standard procedures may be developed for effective combination of the above techniques which would help in running small and medium scale industries in a better fashion, ultimately leading to developed entrepreneurship, developed society, developed nation and developed world. 6 Selection of Flexible Manufacturing Systems using Data Envelopment Analysis The present competitive environment in global market has forced the manufacturing organizations to reduce costs while improving the quality of products and responsiveness to the customers. Flexible manufacturing systems (FMS) offer opportunities to those organizations to improve their technology, competitiveness and profitability through a highly proficient and focused approach to manufacturing effectiveness. The decision makers often face the problem of selecting the most appropriate FMS for a given manufacturing organization. This paper attempts to solve this FMS selection problem in two steps.The first step is used to identify and shortlist the most efficient alternative flexible manufacturing systems having better performance characteristics using the Charnes, Cooper and Rhodes (CCR) model of data envelopment analysis (DEA). Then, the weighted overall efficiency ranking method of multi-attribute decision-making (MADM) theory is employed to determine the best FMS from the shortlisted ones. The results match well with those obtained by the past researchers. 
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