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All Journal International Journal of Engineering, Science and Information Technology
Nuritdinovich, Muhidinov Ayubbek
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Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Optimisation of Resource Allocation in Large-Scale Engineering Projects Using AI-Based Decision Models Nuritdinovich, Muhidinov Ayubbek; Roy, Jainish
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1390

Abstract

In software development, varied decisions need to be made to ensure the fulfilment. Customers frequently seek a wide range of functions in large software projects, resulting in a vast set of requirements. Due to project timeframes and resource constraints, implementing all of the requirements is usually not possible. Setting priorities for a large number of requirements takes time and is challenging. As a result, an organised method of prioritising and subsequently choosing the primary set of needs based on several factors is required. Diverse techniques were available to prioritise the requirements effectively. But the accuracy and time consumption for Requirements Prioritisation were not optimised. Also, during the large-scale Requirements Prioritisation, multiple aspects such as time, cost are not considered. Therefore, three novel methods are proposed for enhancing the performance of large-scale Requirements Prioritisation with better accuracy and less time. Many resource plans were affected by the unexpected joining and leaving events of human resources, which may cause uncertainty. This uncertainty can also affect the quality of the project delivery. Appointing a developer to the first allotted task until the completion of the same may reduce the flexibility of human resources, even though the developer can do other tasks. Optimised Event-Based Scheduler handles this uncertainty and resource flexibility. It is pretty commonplace that we need more time for scheduling if the developer's record is enormous. Subsequently, the search space is also big, and in the long run, the resource allocation is not on time.
Sustainable Supply Chain Practices in Engineering-Based Manufacturing Firms Nuritdinovich, Muhidinov Ayubbek; Vij, Priya
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1494

Abstract

Sustainable Supply Chain Management (SSCM) assesses the environmental implications associated with all conventional supply chain (SC)activities to mitigate their adverse effects. This study presents a fuzzy-based methodology for examining obstacles in SSCM within the environment. Seven manufacturing companies from the electronics industry are participating. The study's findings reveal three primary challenges in engineering-based manufacturing firms. The barriers include knowledge-related factors (insufficient understanding of the adverse effects on business, absence of training programs for industry-specific training, monitoring, and mentoring, lack of technical expertise, and challenges in recognizing environmental possibilities), commitment-related issues (deficiency in corporate social accountability), and design-related challenges (complexities in designing for the reusing/recycling of used goods).The suggested research is among the first investigations undertaken within the environment regarding identifying SSCM barriers in the electrical and electronics industry. Secondly, the obstacles are examined via causation and prominent relationships, which assist decision-makers, policy developers, and organizational managers tackle the essential factors necessary to achieve SSCM activities.
Co-Authors Roy, Jainish Vij, Priya