2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)最新文献_第2页

Define and Optimize the Competitive Advantage Value Using DMADV Approach: A Case Study at PT Telkom Indonesia 运用DMADV方法定义和优化竞争优势价值:以印尼电信公司为例

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00050

S. Islam, Muhtia Luchfi

{"title":"Define and Optimize the Competitive Advantage Value Using DMADV Approach: A Case Study at PT Telkom Indonesia","authors":"S. Islam, Muhtia Luchfi","doi":"10.1109/ICCMSO58359.2022.00050","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00050","url":null,"abstract":"The competition among companies in every sector industry has increased rapidly. It makes the company should make any improvement to compete with other competitors, even win the competition. Companies should make the improvement for their stability in industries field. One important thing that company should pay attention is dealing with the Competitive Advantage Values (CAV). To compete with others, PT Telkom Indonesia should take one step earlier to maximize their CAV. CAV is one of the big deals in the company to make the customer know about the superior value that Indihome (name/brand of communication service provider) has. In the simple words, by defining CAV, either the customers or company will know in which category their products excel when compared to the similar brands. This issue has guided researcher to implement the DMADV process in order to find the CAV in one of the biggest Information and Communication Technology (ICT) company in Indonesia. There are several CAVs of Indihome, the robust one is the expansion of fiber optic through Indonesia. However, several CAVs need to be integrated to increase customer satisfaction and enhance the company's performances. To integrate it, the best process is by using Scrum Process in their development process.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115690257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT in Smart Irrigation and Node MCU ESP 8266 Wi-Fi Module 物联网智能灌溉和节点MCU ESP 8266 Wi-Fi模块

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00065

R. Lal, Bhupinder Singh, Md Abdual Wassay

引用次数: 0

Enhancing dimensional accuracy of small parts through modelling and parametric optimization of the FDM 3D printing process using GA-ANN 利用GA-ANN对FDM 3D打印过程进行建模和参数优化，提高小零件的尺寸精度

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00030

Mannu Yadav, Ashish Kaushik, R. Garg, Mohit Yadav, Deepak Chhabra, Shivam Rohilla, Hitesh Sharma

{"title":"Enhancing dimensional accuracy of small parts through modelling and parametric optimization of the FDM 3D printing process using GA-ANN","authors":"Mannu Yadav, Ashish Kaushik, R. Garg, Mohit Yadav, Deepak Chhabra, Shivam Rohilla, Hitesh Sharma","doi":"10.1109/ICCMSO58359.2022.00030","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00030","url":null,"abstract":"Nowadays, almost every manufacturing industry primarily focuses on precision manufacturing, which can now be easily possible due to advanced rapid prototyping techniques to achieve their overarching goals. Small parts fabrication necessitates ever-more-careful workmanship and strict environmental controls as all materials inevitably expand and contract due to environmental changes, which can raise costs and lengthen the production process. One rapid prototyping method is frequently used to print small objects is fused deposition modelling. In the proposed work, the significant FDM printing parameters (no. of contours, infill density, and layer thickness) are optimized for improving the dimensional precision of FDM printed small specimens of 1mm x 2mm x 3mm. Twenty experimental runs were designed by employing a face-centred central composite design (FCCD) methodology to analyse the effect of input variables on the fabricated specimen. For training and optimization, hybrid statistical tools and artificial neural networks (ANN) integrated with genetic algorithm (ANN-GA) are utilized to obtain the optimized combination of input parameters. Validation tests were performed, sequentially to confirm the various created models for the selection of best process parameter. It has been observed that the minimum percentage change accomplished with GA-ANN approach in height, length and breadth is 1.9455 %, at input variables (Infill density: 55.85 %, Layer thickness: 0.1mm, no of contours: 8), 0.29542% at input variables (Infill density: 23.31, Layer thickness: 0.18, no of contours: 7), 0.4648 % at input variables (Infill density: 48.541 %, Layer thickness: 0.1 mm, no of contours: 3), are best forecasted results obtained using GA-ANN approach and the same has been validated experimentally.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121808344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Automated Interoperability based on Decision Tree for Schema Matching 基于决策树的模式匹配自动互操作

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00023

Mohamed Raoui, Latifa Rassam, Moulay Hafid El Yazidi, A. Zellou

引用次数: 0

Sardine Feast Metaheuristic Optimization with Random Walk for Global Optimization 基于随机游走的沙丁鱼盛宴元启发式全局优化

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00032

M. F. Nasrudin, Dwi Yanuar Panji Tresna, S. Abdullah, H. M. Sarim

{"title":"Sardine Feast Metaheuristic Optimization with Random Walk for Global Optimization","authors":"M. F. Nasrudin, Dwi Yanuar Panji Tresna, S. Abdullah, H. M. Sarim","doi":"10.1109/ICCMSO58359.2022.00032","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00032","url":null,"abstract":"The magnificent sardine feast phenomenon at sea served as the inspiration for the Sardine Feast Metaheuristic Optimization (SFMO) algorithm, which is based on the prevalence of sea predators feeding on sardines. The initial work on the algorithm has shown that it is superior to other optimization algorithms such as Cuckoo Search (CS), Genetic Algorithm (GA), and Bat-inspired Algorithm (BA) in finding global optimization values in benchmark functions. However, SFMO might experience mature convergence because, during exploration and exploitation, it depends on the normal random function in its predators' movement calculation. This paper explores an improvement of SFMO by embedding other random walk algorithms such as Brownian motion and Levy flight. Both random walk algorithms will replace the normal random function to explore divergent areas in the problem space. The performance of the improved SFMO is studied by testing it in several predefined global benchmark functions. The outcomes of the tests are then contrasted with those produced by the basic SFMO algorithm. The Random Walk-based SFMOs outperform the basic SFMO in all benchmark functions. The results show that predators in SFMO with Random Walk moves in nature-like diversification and intensification that lead to improvement.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122504304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HRM and Role of Artificial Intelligence: Triple Bottom Line Sustainability 人力资源管理和人工智能的作用:三重底线可持续性

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00018

Raman Chadha, A. Mehta

{"title":"HRM and Role of Artificial Intelligence: Triple Bottom Line Sustainability","authors":"Raman Chadha, A. Mehta","doi":"10.1109/ICCMSO58359.2022.00018","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00018","url":null,"abstract":"The sustainability framework is inherent in the balanced scorecard, which accounts for financial and non-financial indicators, methodological challenges in developing matrices for triple bottom line performance and establishing decision support frameworks. According to our work, we are focusing on human cognition when confronted with multi-attributed platforms. The research in the field of Artificial Intelligence $(AI)$ results in the growth and development of a wide range of sectors. Through various studies done in the past on the impact of $AI$ it was found that $AI$ systems will play a significant role in achieving sustainability both in positive and negative ways. Through our work, we aim to draw light and focus on reducing the shortcomings of Artificial Intelligence $(AI)$ which were found by using the consensus-based expert elicitation process that AI has a negative impact on 59 targets of 17 sustainable development goals. Our main focus is on Three sustainability areas: Environment, Economy and Society where we worked on indicating the negative impacts of $AI$ on various targets of 17 SDGs. Building on the balanced scorecard, many approaches to the triple bottom line are based largely on accounting and reporting. In other words, firms identify social, environmental and economic metrics and track and report performance.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"389 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126742011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Program and Advisory Committee

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/iccmso58359.2022.00010

引用次数: 0

Toward Dynamic Enterprise Architecture Model using MAPE-K, Control theory and Machine Learning to achieve autonomic adaptiveness 利用MAPE-K、控制理论和机器学习实现自主适应的动态企业架构模型研究

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00022

Imane Ettahiri, Lahbib Ajallouda, Karim Doumi, A. Zellou

引用次数: 0

Plenary/Invited Speech 全体/邀请演讲

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/iccmso58359.2022.00013

引用次数: 0

Centralized Digital Twin driven Supply Chain for Sustainable Smart Manufacturing Plants 集中式数字孪生驱动的可持续智能制造工厂供应链

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00077

M. Khan, Dr.Chinnaiyan R, S. Balachandar, S. Ibrahim, N. Chakravarthy, C. Kalaiarasan, R. Divya

引用次数: 0