Computer-based production planning, scheduling and control: A review

IF 0.9 4区 工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY Journal of Engineering Research Pub Date : 2024-03-01 DOI:10.1016/j.jer.2023.09.027
Nnamdi Cyprian Nwasuka, Uchechukwu Nwaiwu
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Abstract

This research presents a review of computer-based production planning, scheduling, and control (CPPSC). The purpose of this study is to illustrate the progress made in the current research on the planning and control of production and scheduling. Twenty-two papers selected for this study focused on the recent trends, approaches, and problems associated with CPPSC. Progress in the manufacturing paradigm in engineering justified why CPPSC could be applied to a set of systems to increase the production of goods and services and to further highlight the relevance of the decisions made and why substantial progress was made in the development of the theory regarding decision making in each of those areas in the past. The integration of line balancing and process plan selection in the Smart Manufacturing System would lead to more efficient production processes, reduced downtime, and improved resource utilization. Additionally, it would provide a comprehensive view of the production environment, allowing for data-driven decision-making and optimization strategies. To demonstrate the effectiveness of this novelty approach, researchers could set up a real-world pilot in a manufacturing facility. They can compare production performance before and after implementing the AI-driven Smart Manufacturing System. Key performance indicators (KPIs) such as production throughput, machine utilization, cycle time, and lead time can be used to quantify the improvements. Furthermore, case studies and simulation scenarios can be used to validate the system's potential benefits in various manufacturing settings.

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基于计算机的生产计划、调度和控制:综述
本研究综述了基于计算机的生产计划、调度和控制(CPPSC)。本研究的目的是说明当前在生产和调度的计划与控制方面的研究进展。本研究选取了 22 篇论文,重点讨论与 CPPSC 相关的最新趋势、方法和问题。工程制造范式的进步证明了为什么 CPPSC 可以应用于一系列系统,以提高商品和服务的产量,并进一步强调了所做决策的相关性,以及为什么过去每个领域的决策理论发展都取得了实质性进展。在智能制造系统中整合生产线平衡和流程计划选择,将提高生产流程的效率,减少停机时间,提高资源利用率。此外,它还能提供一个全面的生产环境视图,允许数据驱动决策和优化战略。为了证明这种新方法的有效性,研究人员可以在生产设施中进行实际试点。他们可以比较实施人工智能驱动的智能制造系统前后的生产绩效。关键性能指标(KPI),如生产吞吐量、机器利用率、周期时间和提前期,可用于量化改进效果。此外,还可以利用案例研究和模拟场景来验证系统在各种生产环境中的潜在优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Engineering Research
Journal of Engineering Research ENGINEERING, MULTIDISCIPLINARY-
CiteScore
1.60
自引率
10.00%
发文量
181
审稿时长
20 weeks
期刊介绍: Journal of Engineering Research (JER) is a international, peer reviewed journal which publishes full length original research papers, reviews, case studies related to all areas of Engineering such as: Civil, Mechanical, Industrial, Electrical, Computer, Chemical, Petroleum, Aerospace, Architectural, Biomedical, Coastal, Environmental, Marine & Ocean, Metallurgical & Materials, software, Surveying, Systems and Manufacturing Engineering. In particular, JER focuses on innovative approaches and methods that contribute to solving the environmental and manufacturing problems, which exist primarily in the Arabian Gulf region and the Middle East countries. Kuwait University used to publish the Journal "Kuwait Journal of Science and Engineering" (ISSN: 1024-8684), which included Science and Engineering articles since 1974. In 2011 the decision was taken to split KJSE into two independent Journals - "Journal of Engineering Research "(JER) and "Kuwait Journal of Science" (KJS).
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