Agile Project Management Software for Construction and Management Industries

Ali, Nur Hidayah Mohd; Ahmad, Fauzi; Abidin, Nur IzieAdiana; Suhaili, Saadatul; Rahman, Mohammad Ashraf Abdul; Harun, Hasnida; Awang, Mariah; Hamid, Nor Hazren Abdul; Musa, Mohd Kamaruzaman; Hamidon, Nuramidah; Yusop, Fatimah; Syazwan, M. M. Syafiq

doi:10.1007/978-981-16-0742-4_7

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Prinsip-prinsip utama agile software development adalah pelaporan hasil perangkat lunak kerja cepat, kolaborasi antara pengembang dan stakeholder yang terus-menerus untuk memantau hasil teknis dan kualitas desain. Metode agile software development menguntungkan proyek dalam hal meningkatkan tingkat keberhasilan proyek, penerimaan pengguna, manajemen risiko, dan kemampuan untuk penyesuaian dengan perubahan requirement [1], [2], [10]- [12].…”

Section: Pendahuluanunclassified

Implementation of Agile Software Development Methodology in Software Projects

Noprisson

2023

JUSIBI

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This research is a systematic literature review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as a method to gather literature on agile software development methodology from Google Scholar. The result of this study is a summary of 11 articles related to Agile software development. The recommendation of this study is the use of the GLUX framework. GLUX framework integrates Lean UX into Scrum to improve the sustainability of the rapid software development process. It aims to promote a user-centric mindset and collaborative UX activities during the development process using gamification techniques. GLUX is about self-reliant teams, creating a motivating environment, and fostering teamwork.

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Section: Pendahuluanunclassified

Implementation of Agile Software Development Methodology in Software Projects

Noprisson

2023

JUSIBI

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“…Dubey et al (2015) demonstrated the ANN technique's application to find the power delivery in pressurized heavy water reactors in nuclear engineering. The above-discussed techniques were also explored in various fields of engineering, which opened the path to significant developments to solve complex realtime problems (Alade et al, 2020;Ali et al, 2021;Calvé & Savoy, 2000;Hapfelmeier & Ulm, 2014;Piro et al, 2012;Ramachandran et al, 2020;Seibi & Al-Alawi, 1997).…”

Section: In Manufacturingmentioning

confidence: 99%

“…This revolution ignited the spark for the next, which occurred very soon in the late 1960s because of the invention of computers. Later on, it was universally recognized as the 3rd revolution of the industries (Ali et al, 2021;Hudson, 1982;Singh et al, 2013). The concept of automation began in this revolution which immensely helped mass production (David, 2017;Dunk, 1992;Kuric et al, 2018;Wu et al, 2015a).…”

Section: Introductionmentioning

confidence: 99%

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

et al. 2022

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For several industries, the traditional manufacturing processes are time-consuming and uneconomical due to the absence of the right tool to produce the products. In a couple of years, machine learning (ML) algorithms have become more prevalent in manufacturing to develop items and products with reduced labor cost, time, and effort. Digitalization with cutting-edge manufacturing methods and massive data availability have further boosted the necessity and interest in integrating ML and optimization techniques to enhance product quality. ML integrated manufacturing methods increase acceptance of new approaches, save time, energy, and resources, and avoid waste. ML integrated assembly processes help creating what is known as smart manufacturing, where technology automatically adjusts any errors in real-time to prevent any spillage. Though manufacturing sectors use different techniques and tools for computing, recent methods such as the ML and data mining techniques are instrumental in solving challenging industrial and research problems. Therefore, this paper discusses the current state of ML technique, focusing on modern manufacturing methods i.e., additive manufacturing. The various categories especially focus on design, processes and production control of additive manufacturing are described in the form of state of the art review.

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Machine Learning Techniques in Additive Manufacturing: A Review

Alsalem,

Zohdy

2023

2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)

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Agile Project Management Software for Construction and Management Industries

Cited by 3 publications

References 6 publications

Implementation of Agile Software Development Methodology in Software Projects

Implementation of Agile Software Development Methodology in Software Projects

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

Machine Learning Techniques in Additive Manufacturing: A Review

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