Digital Technologies and Industrial AI for Sustainable Solutions in a Value Chain

Dear Colleagues:

(1) Introduction, including scientific background, highlighting the importance of this research area.

Introduction

The fusion of digital technology with industrial artificial intelligence (AI) has sparked a revolution in a number of industries, especially value chains, in recent years. This special edition of 'Digital Technologies and Industrial AI for Sustainable Solutions in a Value Chain' explores the state-of-the-art developments and uses that are transforming markets, improving sustainability, and stimulating creativity.

Scientific background

The convergence of the digital, physical, and biological domains has brought about the Fourth Industrial Revolution, which has brought with it unprecedented advances in automation, machine learning, and data processing. Modern industrial ecosystems now cannot function without digital technologies like cloud computing, blockchain, big data analytics, and the Internet of Things (IoT). Real-time monitoring, seamless communication, and powerful analytics are made possible by these technologies and are essential for decision-making and process optimisation throughout the value chain.

At the same time, industrial AI makes use of advanced models and algorithms to decipher complicated datasets, forecast results, and streamline decision-making procedures. Artificial intelligence is a potent instrument for increasing productivity, reducing waste, and raising the calibre of output because of its capacity to learn from past data and adjust to new information. Artificial intelligence (AI) is being used in manufacturing, logistics, and supply chain management to forecast demand, maximise inventory, and simplify processes, resulting in more robust and sustainable systems.

Importance of research in this area

Digital technology and industrial AI play an increasingly important role as demand on global enterprises to embrace sustainable practices grows. In order to satisfy legal obligations, customer demands, and environmental concerns, sustainable solutions are now essential. This field of study is essential for a number of reasons:

1. Environmental Impact: The implementation of AI and digital technologies can substantially reduce the carbon footprint of industrial activities by optimizing resource utilization, minimizing waste, and improving energy efficiency.
2. Economic Efficiency: By enhancing operational efficiency and reducing costs, these technologies can drive economic growth while ensuring sustainability. Predictive maintenance, for example, can prevent equipment failures and downtime, saving substantial costs and resources.
3. Resilience and Adaptability: In the face of global disruptions such as pandemics and climate change, a digitally integrated and AI-powered value chain can adapt more quickly and maintain continuity, ensuring robust supply chain management and operational resilience.
4. Innovation and Competitiveness: Embracing these technologies fosters innovation, enabling industries to develop new products and services that meet evolving market demands and maintaining a competitive edge in the global market.

(2) Aim of the Special Issue and how the subject relates to the journal scope.

This special issue aims to showcase the latest research, developments, and case studies in the application of digital technologies and industrial AI within value chains. By highlighting successful implementations and exploring emerging trends, this compilation seeks to provide a comprehensive understanding of how these innovations can be harnessed for sustainable industrial growth and environmental stewardship.

How does it align with 'Sustainability'?

This Special Issue closely aligns with the journal 'Sustainability,' which focuses on the environmental, cultural, economic, and social sustainability of human beings. The exploration of digital technologies and industrial AI within value chains directly addresses multiple dimensions of sustainability:

Environmental Sustainability: These technologies optimize resource usage and reduce emissions, mitigating environmental impacts in line with the journal's ecological focus.

Economic and Social Sustainability: By enhancing economic efficiency and resilience, digital and AI solutions support sustainable economic development and social well-being, which are key areas for the journal.

Innovation for Sustainable Development: The journal champions innovative approaches to sustainability, and this Special Issue showcases pioneering solutions and technological advancements driving sustainable development across industries.

Interdisciplinary Approach: Reflecting the journal's commitment to holistic research, this Special Issue integrates insights from engineering, computer science, environmental science, and economics to address complex sustainability challenges.

(3) Suggest themes.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

• AI-driven predictive maintenance for sustainable manufacturing;
• IoT and big data analytics for resource optimization;
• Blockchain technology for transparent and sustainable supply chains;
• Energy efficiency and carbon reduction through industrial AI;
• Digital twins and simulation for sustainable production processes;
• Smart logistics and transportation for reduced environmental impact;
• Circular economy solutions enabled by digital technologies;
• AI in waste management and recycling;
• Sustainable agriculture through precision farming and AI;
• Cyber–physical systems for industrial sustainability;
• Environmental monitoring and management with IoT and AI;
• Smart grids and renewable energy integration;
• Human–machine collaboration for sustainable industrial practices;
• AI-enhanced decision making for sustainable business strategies;
• Green supply chain management using digital technologies. 

We look forward to receiving your contributions.

Dr. Gunjan Soni
Dr. Görkem Ataman
Dr. Surbhi Bhatia Khan
Prof. Dr. Mangey Ram
Guest Editors

Manuscript Submission Information

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• sustainable manufacturing
• predictive maintenance
• resource optimization
• blockchain in supply chain
• energy efficiency
• digital twins
• smart logistics
• circular economy
• precision farming
• green supply chain management