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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Application of S-LCA Principles to Additive Manufacturing 8th

Application of S-LCA Principles to Additive Manufacturing

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8th International and 29th All India Manufacturing Technology, Design and Research Conference, AIMTDR 2021

作者： Agrawal, Rohit Vinodh, S. Department of Production Engineering National Institute of Technology Tiruchirappalli620 015 India Operations Management & Quantitative Techniques Indian Institute of Management BodhGaya Bihar India

ISBN: (纸本)9789811976117

Additive manufacturing (AM) has been a key technology adopted in modern industrial practices. Many developments are reported in different research dimensions. In line with the analysis of environmental aspects, analysis of societal aspects is also needed. In this perspective, the present study analyzes the societal aspects of AM technology. The evaluation model has been developed based on a literature review, and expert opinion is used to validate the derived indicators. Analysis of various societal indicators has been done. It is found that the social impact generated from the fabrication of bevel gear is found to be 3.33e mpt. The study has contributed toward the analysis of societal impacts of AM from the viewpoint of different stakeholder dimensions. The implications of the study are highlighted. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Life cycle

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A Modeling and Hybridized Decomposition Approach for the Multi-level Capacitated Lot-Sizing Problem with Setup Carryover, Backlogging, and Emission Control

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operations Research Forum 2024年第3期5卷 68页

作者： Chowdhury, Nusrat T. Baki, Mohammed F. Azab, Ahmed School of Technology Art and Design Bemidji State University Odette School of Business University of Windsor Production & amp Operations Management Research Laboratory Faculty of Engineering University of Windsor

The goal of the production planning problem is to determine the optimum quantity to produce in order to satisfy demand over a predetermined planning horizon with the least amount of money spent. Making the appropriate choices in production planning will impact a manufacturing company’s performance and productivity, which is crucial to remain competitive in the market. Therefore, developing and enhancing techniques for solving production planning problems is very significant. This paper proposes a mixed-integer linear programming model for this extension of the dynamic multi-level capacitated lot-sizing under study, where setup carryover, backlogging, and emission control are considered. An item Dantzig-Wolfe decomposition-based heuristic procedure is developed, and a dynamic programming and column generation approach is used to solve the problem. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any infeasibilities that arise when solving the problem. We evaluate the performance of the developed solution approach using a test data set available in the literature. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable timeframe. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Dantzig-Wolfe decomposition Emission control Inventory Multi-level capacitated lot-sizing Setup carryover

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Impact of Machine Learning on Applying the Best Worst Method for Social Sustainability in Manufacturing Supply Chains 7

Impact of Machine Learning on Applying the Best Worst Method...

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Yogi, Kottala Sri Dankan Gowda, V. Kumar Sahu, Atul Jagtap, Madan Mohanrao Srinivas, Ved Abdullah, Ibrahim International University Symbiosis Institute of Business Management Hyderabad Symbiosis Department of Operations Pune India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India School of Studies in Engineering & Technology Department of Industrial and Production Engineering Koni Chattisgarh Bilaspur India Symbiosis Institute of Operations Management Department of Operations Management Nashik Campus Maharashtra Pune India Thiagarajar School of Management Department of Human Resources Tamil Nadu Madurai India Al-Turath University College Department of Computer Science Baghdad Iraq

ISBN: (纸本)9798350372816

This research is carried out merging ML with BWM to intensify decision making in manufacturing supply chain using social sustainability under light. As companies become more focused on environmental sustainability, the capability of machine learning to effectively assess and prioritize sustainability criteria should be highly valued. Through a team of domain experts, the research clearly identifies the most vital social sustainability factors and, afterwards, deploys ML algorithms to analyze and optimize the provided decision-making framework by BWM. The selected approach gives possibility to dynamic weighting of the criteria which is based on real-time data. This way we are able to come up with the more precise and effective sustainability strategies. The results show that the hybrid ML-BWM model is not only an effective tool to enhance the validity and accuracy of evaluations but also one that provides the prudent directions that help the manufacturing sector shape its choice and responses. This paper analyzes the possible outcome of the integration of AI and traditional approach to decision-making process on social aspects of sustainability within supply chain. © 2024 IEEE.

关键词： Smart manufacturing

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Identification of benefits, challenges, and pathways in E-commerce industries: An integrated two-phase decision-making model

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Sustainable operations and Computers 2023年第1期4卷 200-218页

作者： Gupta, Srikant Kushwaha, Pooja.S. Badhera, Usha Chatterjee, Prasenjit Gonzalez, Ernesto D.R. Santibanez Department of Operations and Decision Sciences Jaipuria Institute of Management Jaipur India Department of Business Analytics Jaipuria Institute of Management Indore India Department of Business Analytics Jaipuria Institute of Management Jaipur India Department of Mechanical Engineering MCKV Institute of Engineering West Bengal 711204 India Post-Doctoral Fellow Management Graduate Program Universidade Paulista Indianópolis Campus Brazil Department of Industrial Engineering and CES 4.0 Faculty of Engineering University of Talca Curico Chile

The e-commerce industry has seen significant growth over the past decade as it focuses on convenience and accessibility, leading to a surge in online shopping with more and more consumers opting for it. At the same time, the e-commerce industry faces various challenges. In order to fully harness the potential of this industry, it is important to identify its benefits and challenges and focus on pathways to mitigate the challenges and harness its growth. This study utilizes the Delphi approach and involves experts from the e-commerce domain to get their opinions to identify the top ten benefits, challenges, and pathways for the e-commerce industry. Analytic Hierarchy Process (AHP) and Criteria Importance Through Intercriteria Correlation (CRITIC) methods are subsequently, employed to prioritize the identified factors. Results of the study revealed that factors such as affordable advertising & marketing;availability and product variety;and Global reachability are the most important benefits, while technological upgradation;returns or refunds;and counterfeit products posed the greatest challenges for the industry. Government compliance check;better relationship with delivery partners;and strong data privacy and online security policies emerged as the best pathways. This study also provides valuable insights to businesses, policymakers, and researchers in the e-commerce industry on how to navigate the benefits, challenges, and pathways of this rapidly growing sector. © 2023

关键词： Electronic commerce

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Sustainability Evaluation of Renewable Energy Systems: A Lifecycle and Economic Perspective 2

Sustainability Evaluation of Renewable Energy Systems: A Lif...

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2nd International Conference on Smart Cities 4.0, Smart Cities 4.0 2023

作者： Shihata, Lamia A. Ali, Mona Ali The German University In Cairo Design And Production Engineering Department Ems Cairo Egypt The German University In Cairo Business Informatics And Operations Management Department Cairo Egypt

ISBN: (纸本)9781665474306

This study demonstrates how life cycle analysis could be utilized along with other criteria to make an informative decision choosing between different renewable energy sources. The decision framework for a 1 MW solar photovoltaic system and a 1 MW wind turbine system is proposed. Based on a lifetime analysis of 25 years and an emissions time span of 100 years, the operation and maintenance analysis, as well as an economic and efficiency evaluation, the solar photovoltaic energy system was rated higher a more favorable in both environmental impact and maintenance. Additionally, it was concluded that if an investor or stakeholders is considering the amount of profit return to be the most important, then the wind turbine system is the ideal option as it has a high return value on investment. © 2023 IEEE.

关键词： Life cycle

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Striving for Business Sustainability: Understanding the Interplay and Impact of Sustainable Finance, Environmental Social Governance Strategy, and Information Technology Integration on Sustainable Enterprise Performance

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Circular Economy and Sustainability 2024年第4期4卷 2749-2774页

作者： Kapoor, Samridhi Kharat, Manoj Govind Parhi, Shreyanshu Kharat, Mukesh Govind Pandey, Shatrudhan School of Business Studies Department of Business Studies Central University of Karnataka Karnataka 585367 India Department of Marketing and Strategy Sinhgad Institute of Business Management Mumbai 400072 India Department of Operations Management and Quantitative Techniques International Management Institute– Bhubaneswar Bhubaneswar 751003 India Department of Marketing and International Business K J Somaiya Institute of Management Mumbai 400077 India Department of Production and Industrial Engineering Birla Institute of Technology Mesra Ranchi 835215 India

Sustainable financing, environmental social governance strategy and information technology integration can play a strategic role in the financial success of an organisation. In light of this, the present study attempts to investigate how sustainable finance, environmental social governance and information technology integration impacts sustainable enterprise performance. Further, it also examines how organisational commitment and support moderates the relationship between environmental social governance and sustainable enterprise performance and information technology integration and sustainable enterprise performance. The primary data collected from 290 manufacturing industry employees was analysed using structural equation modelling. The study results indicate that sustainable finance, environmental social governance strategy and information technology integration have a significant positive impact on sustainable enterprise performance. The results further ascertain that organisational commitment and support positively moderates the relationship between environmental social governance and sustainable enterprise performance and information technology integration and sustainable enterprise performance. The findings imply that in order to improve financial performance, the company should embrace robust environmental social governance policies and put in place an efficient information technology integration adoption and implementation plan. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Environmental social governance Information technology integration Sustainable enterprise/firm performance Sustainable finance

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OPTIMIZING UAV DELIVERY ROUTING FOR ISLAND DEMAND SURGES: A DATA-DRIVEN APPROACH TO MINIMIZE CARBON EMISSIONS 51

OPTIMIZING UAV DELIVERY ROUTING FOR ISLAND DEMAND SURGES: A ...

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51st International Conference on Computers and Industrial engineering, CIE 2024

作者： Jayasuriya, Masha Dilmi Fernando, W. Madushan Thibbotuwawa, Amila Nielsen, Peter Department of Transport Management and Logistics Engineering University of Moratuwa Katubedda10400 Sri Lanka Center for Supply Chain Operations and Logistics Optimization University of Moratuwa Katubedda10400 Sri Lanka Department of Materials and Production Aalborg University Aalborg9220 Denmark

Unmanned aerial vehicles (UAVs) offer significant advantages over traditional delivery methods, including vertical take-off and landing capabilities, lower costs, and adaptable transport directly to consumers. Since its inception, the Vehicle Routing Problem (VRP) has seen substantial development, enabling routes to decide that reduce costs and improve the effectiveness of operations. So, integrating the VRP with UAVs, UAV routing aims to find the best combination of routes for UAVs that minimize overall distance or time, while enhancing delivery efficiency. This research focuses on optimizing last-mile UAV delivery for rapid response to demand surges on islands, to overcome accessibility challenges. It demonstrates the comparative advantages of UAVs and provides a data-driven approach to estimating carbon emission reductions. We conducted a detailed cost-benefit analysis comparing UAV delivery with existing boat services, considering factors such as delivery time, operational costs, and carbon emissions, using a Maldives hotel chain as a case study. To be more accurate, a long-term cost-benefit analysis was also performed. The analysis indicates that while UAV implementation may not yield immediate savings in the first two years, significant cost-effectiveness and operational efficiency are achievable from the third year onwards. The research also underscores the environmental sustainability of UAVs, showcasing substantial reductions in fuel consumption and carbon footprint compared to traditional boat delivery methods. On average, UAVs achieve an impressive 85% reduction in carbon emissions. Furthermore, the results show that using UAVs in logistics results in more effective delivery options, particularly in island markets where accessibility and rapid response are crucial to overcome demand surges. Moreover, our model's real-world applicability is supported by assumptions that ensure its relevance to large-scale distribution networks. The implications of this res

关键词： Unmanned aerial vehicles (UAV)

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Novel Simulation Optimization Approach for Supply Chain Coordination and management

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Procedia Computer Science 2024年 232卷 1646-1653页

作者： Alexandros Xanthopoulos Ioannis Kostavelis Department of Production & Management Engineering School of Engineering Democritus University of Thrace 67100 Xanthi Greece Supply Chain Management MSc Program School of Social Sciences Hellenic Open University 26335 Patra Greece Department of Supply Chain Management International Hellenic University 60100 Katerini Greece

The importance of supply chain management is paramount nowadays and this research seeks ways for better supply chain coordination. We present a roadmap for implementing true digital replicas of physical supply chains based on a disruptive simulation modeling approach. These digital replicas can enable the comparative evaluation of existing Just-In-Time (JIT) control policies for the first time without the unrealistic assumptions of existing studies in the literature. These realistic supply chain simulation models have the prospect of giving us better understanding of their behavior and of their complex dynamics. We provide guidelines for using the digital replicas and advanced optimization approaches to derive novel supply chain coordination policies pushing the field of JIT control beyond the state-of-the-art. An equally important contribution of this research is that it advances the field of hybrid discrete event-system dynamics (DES-SD) simulation with the prospect of pushing Systems engineering to the next level. This research discusses theoretical foundations for mixing DES with SD simulation, and explores technical aspects and implementation details. The implications of this extent well beyond the supply chain field since both DES and SD have dozens of application areas including manufacturing, service systems and economics, social sciences, respectively. The paper is concluded with a discussion on the potential impact of the proposed approach including insights for practitioners, applicability of scientific results in industry and prerequisites for business process re-engineering.

关键词： supply chain logistics hybrid simulation system dynamics reinforcement learning business process re-engineering

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Agriculture 4.0 adoption challenges in the emerging economies: Implications for smart farming and sustainability

Journal of Economy and Technology

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Journal of Economy and Technology 2024年 2卷 278-295页

作者： Md Hasibul Islam Md. Zahidul Anam Mohammad Rashedul Hoque Maksuraton Nishat A.B.M. Mainul Bari Department of Operations and Supply Chain Management American International University-Bangladesh Dhaka 1229 Bangladesh Department of Industrial and Production Engineering American International University-Bangladesh Dhaka 1229 Bangladesh Department of Industrial and Production Engineering Bangladesh University of Engineering and Technology Dhaka 1000 Bangladesh

To ensure food security in this age of production and supply disruption, the agricultural sectors of emerging economies are gradually adopting more smart technologies to achieve sustainability. However, literature on the challenges of adopting Agriculture 4.0-based smart farming technologies is still very limited. This research, therefore, explores the contextual interrelation among the challenges to adopting Agriculture 4.0-based smart technologies in the agricultural production system from a developing country's perspective and prioritizes the identified challenges. A case study was conducted in Bangladesh, an emerging economy, where data was collected through interviews and focus group discussion sessions. A total of 21 challenges were finalized as relevant to the country's context. The Interpretive Structural Modeling (ISM) technique was deployed to develop a hierarchical structure depicting the challenges' interrelations. The challenges were later ranked based on their relevant weight using the Best-Worst Method (BWM). This study finds technological complexity, lack of collaboration among different stakeholders, inadequate support from the government, and lack of action plans to have very high driving power. Challenges such as high initial investment and operational costs, lack of skilled workforce, and farmers' resistance were found to be dependent challenges. This study is expected to contribute by providing a deeper insight into the challenges of adopting Agriculture 4.0 in emerging economies so that practitioners can take effective mitigating measures to streamline the plant-based agricultural production systems to promote food security and sustainability.

关键词： Agriculture 4.0 Smart farming Sustainable development Best–worst Method Interpretive structural modeling

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