Multi-Objective Implementation of Additive Manufacturing in Make-to-Stock Production

2020 ◽  
Author(s):  
Ping Chong Chua ◽  
Seung Ki Moon ◽  
Yen Ting Ng
Keyword(s):  
Additive Manufacturing ◽  
Performance Measures ◽  
Manufacturing Process ◽  
Rule Based ◽  
Multi Objective ◽  
Implementation Problem ◽  
Conventional Production ◽  
Volume Production ◽  
Make To Stock ◽  
Production Orders

Abstract As additive manufacturing (AM) develops and matures over the years, it has reached a stage where implementation into a conventional production system becomes possible. With additive manufacturing currently suitable for product personalization/high customization yet small volume production, there are various ways of implementation in a conventional production line. This aim of this paper is to explore the implementation of additive manufacturing in a complementary manner to process internal job orders of large quantities in make-to-stock (MTS) production. Splitting of production orders is allowed and production can be carried out by both injection moulding and additive manufacturing processes simultaneously, with the latter being able to produce various MTS parts in a single build. NSGA-III together with scheduling and rule-based heuristic for allocation of parts on build plate of additive manufacturing process is used to solve the multi-objective implementation problem, with performance measures being cost, scheduling and sustainability. The algorithm will be incorporated with scheduling and rule-based heuristic for allocation of parts on build plate of additive manufacturing process. An experiment using an industry case study is conducted to compare the performance measures with and without implementing additive manufacturing.

scholarly journals Multi-Objective Optimization of Additive Manufacturing Process

2018 ◽  
Vol 51 (11) ◽  
pp. 152-157 ◽  
Author(s):  
Elnaz Asadollahi-Yazdi ◽  
Julien Gardan ◽  
Pascal Lafon
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Multi Objective Optimization ◽  
Multi Objective

A Review of Multi-Objective Evolutionary Based Fuzzy Classifiers

2020 ◽  
Vol 13 (1) ◽  
pp. 77-85
Author(s):  
Praveen Kumar Dwivedi ◽  
Surya Prakash Tripathi
Keyword(s):  
Fuzzy Systems ◽  
Evolutionary Process ◽  
Fuzzy Rule ◽  
Fuzzy Classification ◽  
Multi Objective Optimization ◽  
Fuzzy Classifier ◽  
Rule Based ◽  
Trade Off ◽  
Multi Objective ◽  
Rule Based Systems

Background: Fuzzy systems are employed in several fields like data processing, regression, pattern recognition, classification and management as a result of their characteristic of handling uncertainty and explaining the feature of the advanced system while not involving a particular mathematical model. Fuzzy rule-based systems (FRBS) or fuzzy rule-based classifiers (mainly designed for classification purpose) are primarily the fuzzy systems that consist of a group of fuzzy logical rules and these FRBS are unit annexes of ancient rule-based systems, containing the "If-then" rules. During the design of any fuzzy systems, there are two main objectives, interpretability and accuracy, which are conflicting with each another, i.e., improvement in any of those two options causes the decrement in another. This condition is termed as Interpretability –Accuracy Trade-off. To handle this condition, Multi-Objective Evolutionary Algorithms (MOEA) are often applied within the design of fuzzy systems. This paper reviews the approaches to the problem of developing fuzzy systems victimization evolutionary process Multi-Objective Optimization (EMO) algorithms considering ‘Interpretability-Accuracy Trade-off, current research trends and improvement in the design of fuzzy classifier using MOEA in the future scope of authors. Methods: The state-of-the-art review has been conducted for various fuzzy classifier designs, and their optimization is reviewed in terms of multi-objective. Results: This article reviews the different Multi-Objective Optimization (EMO) algorithms in the context of Interpretability -Accuracy tradeoff during fuzzy classification. Conclusion: The evolutionary multi-objective algorithms are being deployed in the development of fuzzy systems. Improvement in the design using these algorithms include issues like higher spatiality, exponentially inhabited solution, I-A tradeoff, interpretability quantification, and describing the ability of the system of the fuzzy domain, etc. The focus of the authors in future is to find out the best evolutionary algorithm of multi-objective nature with efficiency and robustness, which will be applicable for developing the optimized fuzzy system with more accuracy and higher interpretability. More concentration will be on the creation of new metrics or parameters for the measurement of interpretability of fuzzy systems and new processes or methods of EMO for handling I-A tradeoff.

scholarly journals Multi-objective evolutionary design of granular rule-based classifiers

2015 ◽  
Vol 1 (1) ◽  
pp. 37-58 ◽  
Author(s):  
Michela Antonelli ◽  
Pietro Ducange ◽  
Beatrice Lazzerini ◽  
Francesco Marcelloni
Keyword(s):  
Evolutionary Design ◽  
Rule Based ◽  
Multi Objective

scholarly journals Blade Segment with a 3D Lattice of Diamond Grits Fabricated via an Additive Manufacturing Process

2020 ◽  
Vol 33 (1) ◽  
Author(s):  
Bin Chen ◽  
Peng Chen ◽  
Yongjun Huang ◽  
Xiangxi Xu ◽  
Yibo Liu ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Service Life ◽  
Manufacturing Process ◽  
Cutting Speed ◽  
Inspection System ◽  
Layer By Layer ◽  
Filling Rate ◽  
Pressure System ◽  
Manufacturing Equipment ◽  
Diamond Blade

Abstract Diamond tools with orderly arrangements of diamond grits have drawn considerable attention in the machining field owing to their outstanding advantages of high sharpness and long service life. This diamond super tool, as well as the manufacturing equipment, has been unavailable to Chinese enterprises for a long time due to patents. In this paper, a diamond blade segment with a 3D lattice of diamond grits was additively manufactured using a new type of cold pressing equipment (AME100). The equipment, designed with a rotary working platform and 16 molding stations, can be used to additively manufacture segments with diamond grits arranged in an orderly fashion, layer by layer; under this additive manufacturing process, at least 216000 pcs of diamond green segments with five orderly arranged grit layers can be produced per month. The microstructure of the segment was observed via SEM and the diamond blade fabricated using these segments was compared to other commercial cutting tools. The experimental results showed that the 3D lattice of diamond grits was formed in the green segment. The filling rate of diamond grits in the lattice could be guaranteed to be above 95%; this is much higher than the 90% filling rate of the automatic array system (ARIX). When used to cut stone, the cutting amount of the blade with segments made by AME100 is two times that of ordinary tools, with the same diamond concentration. When used to dry cut reinforced concrete, its cutting speed is 10% faster than that of ARIX. Under wet cutting conditions, its service life is twice that of ARIX. By applying the machine vision online inspection system and a special needle jig with a negative pressure system, this study developed a piece of additive manufacturing equipment for efficiently fabricating blade segments with a 3D lattice of diamond grits.

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