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International Journal of Production Research
Scopus
ISSN 0020-7543 · Taylor & Francis · 20 artikel di indeks
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Artikel Jurnal Teks lengkap
Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation
This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM).Through the lens of the resource-based view and based on key AI capabilities such as learning, perception…
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Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises
Despite the exponential growth of artificial intelligence (AI) research in operations, supply chain, and productions management literature, empirical insights on how organisational behavioural mechanisms at the human–technology interface will facilitate AI adoption in small- and medium-sized…
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Human-centric production and logistics system design and management: transitioning from Industry 4.0 to Industry 5.0
Industry 4.0 was presented more than a decade ago as the fourth industrial revolution, aiming to significantly raise the level of sophistication of interconnected technologies and thus increase manufacturing industries’ profits. However, because the technology-driven narrow focus of Industry 4.0 on…
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A review on reinforcement learning algorithms and applications in supply chain management
Decision-making in supply chains is challenged by high complexity, a combination of continuous and discrete processes, integrated and interdependent operations, dynamics, and adaptability. The rapidly increasing data availability, computing power and intelligent algorithms unveil new potentials in…
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Human-centric artificial intelligence architecture for industry 5.0 applications
Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and human-centricity at its core. Therefore, we propose an architecture that integrates Artificial Intelligence…
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Artificial intelligence-driven risk management for enhancing supply chain agility: A deep-learning-based dual-stage PLS-SEM-ANN analysis
This study posits that the use of artificial intelligence (AI) enables supply chains (SCs) to dynamically react to volatile environments, and alleviate potentially costly decision-makings for small-medium enterprises (SMEs). Building on a resource-based view, this work examines the impact of AI on…
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Ripple effect and supply chain disruption management: new trends and research directions
Ripple effect is a specific area of SC disruptions and a strong stressor to SC resilience. Research on the ripple effect analyses how one or more disruptive events propagate through the SC and impact its resilience and performance. The phenomenon of the ripple effect, immensely existing in…
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Critical success factors influencing artificial intelligence adoption in food supply chains
The adoption of Artificial Intelligence (AI) in the food supply chains (FSC) can address unique challenges of food safety, quality and wastage by improving transparency and traceability. However, the technology adoption literature in FSC is still the in infancy stage, meaning little is known about…
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The emergence of cognitive digital twin: vision, challenges and opportunities
As a key enabling technology of Industry 4.0, Digital Twin (DT) has been widely applied to various industrial domains covering different lifecycle phases of products and systems. To fully realize the Industry 4.0 vision, it is necessary to integrate multiple relevant DTs of a system according to a…
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Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning
We propose a framework to learn to schedule a job-shop problem (JSSP) using a graph neural network (GNN) and reinforcement learning (RL). We formulate the scheduling process of JSSP as a sequential decision-making problem with graph representation of the state to consider the structure of JSSP. In…
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Machine learning in manufacturing and industry 4.0 applications
The machine learning (ML) field has deeply impacted the manufacturing industry in the context of the Industry 4.0 paradigm. The industry 4.0 paradigm encourages the usage of smart sensors, devices, and machines, to enable smart factories that continuously collect data pertaining to production. ML…
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Zero-defect manufacturing the approach for higher manufacturing sustainability in the era of industry 4.0: a position paper
For manufacturing companies, quality management is a key feature for increasing the competitiveness, productivity, profitability, and sustainability of their systems. Quality improvement (QI) methods aim to achieve high-quality parts without reducing performance. The Industry 4.0 framework brought…
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Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management
While Industry 4.0 has been trending in practice and research, operations management studies in this area remain nascent. Our intent is to understand the current state of research in Industry 4.0 in different disciplines and deduce insights and opportunities for future research in operations…
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The complementary effect of lean manufacturing and digitalisation on operational performance
The most recent trend manufacturers have embraced to seek operational performance improvements is the use of a wide range of digital technologies typically associated with Industry 4.0. However, few studies have investigated the relationship between such technologies and the long-established lean…
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The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing
The growing importance of humanitarian operations has created an imperative to overcome the complications currently recorded in the field. Challenges such as delays, congestion, poor communication and lack of accountability may represent opportunities to test the reported advantages of emergent…
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Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting
There has been tremendous interest in blockchain technology (BT) (also known as distributed ledger technology) around the globe and across sectors. Following significant success in the financial sector, other sectors, such as humanitarian sector, have started deploying BT at various levels…
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Blockchain in transport and logistics – paradigms and transitions
Blockchain – also known as distributed ledger – technology is set to revolutionise data and business process management and transactions. Blockchain adoption, pioneered initially as a financial tec...
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Supply chain collaboration in the presence of disruptions: a literature review
The supply chain collaboration has gained significant attention, especially in the presence of disruptions. This paper presents findings from a systematic literature review to answer the question: how collaborations help supply chains respond and recover from a disruption. A total of 157 papers…
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Balancing price and green quality in presence of consumer environmental awareness: a green supply chain coordination approach
This study analyses the green channel coordination problem in a two-echelon supply chain where demand is a function of the selling price and the product’s green quality. The retailer decides on the selling price while the manufacturer regulates the green quality of the product. To initiate the…
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One-to-one relationships between Industry 4.0 technologies and Lean Production techniques: a multiple case study
Production research literature and industry practice have started to pay increasing attention to the Industry 4.0 (I4.0) phenomenon. Scholars and practitioners identified a strong link between this paradigm and the well-known Lean Production (LP) paradigm. Most studies consider LP as a prerequisite…