The aim of the centre for Intelligent Supply Chains (CISC) is to bring industry and academia together to build efficient, inclusive, resilient and sustainable supply chains. We aim to enable organisations to improve strategic decision making through data driven competitiveness, growth and efficiency.
The research centre combines leading-edge academic expertise with practical relevance to benefit organisations through contract research, consultancy projects and advanced training and development services. Our research is published in top-ranked scientific journals and developed in partnership with industry to solve real world business challenges.
The key objectives of the centre are driving impactful and interdisciplinary research, knowledge transfer to wider community, and importantly, preparing future research leaders (doctoral students) in their research journey.
Our core areas of expertise are sustainability, and circular economy, operational excellence, lean six sigma, multicriteria decision making, supply chain modelling and simulation, fuzzy sets, machine learning, data mining, and theory and process management. We have industry expertise across food supply chains, healthcare, automotive and transportation sectors.
Supply chain sustainability offers a holistic view of supply chain operations and processes that have continuous accountability for risk and negative impacts on the environmental, social, economic and legal aspects of a supply chain's components.
The application of Industry 4. 0 facilitates digitalisation and improvements in logistics and supply chains, mitigating supply chain risks, enhancing operation efficiency and effectiveness, enhancing supply chain resilience and responsiveness, maintaining market share and entering new markets.
Big Data analytics is an all-encompassing term for techniques to analyse Big Data characterised by high volume, velocity, variety and veracity. Machine learning is an application of artificial intelligence (AI) for data analysis, based on the idea that systems automatically learn from data, identify patterns and make decisions with minimal human intervention. Big data analytics and predictive analysis using machine learning can improve supply chain performance by improving visibility, resilience, responsiveness, and robustness.
Operational research (OR) uses advanced analytical methods and scientific approach to determine the best solution to the problem and help make better decisions.
Process improvement includes being able to use key data more thoroughly by employing business intelligence tools, and developing integrated processes to improve performance by reducing lead time and increasing velocity. The centre has strong expertise and interest in automobile and aerospace products manufacturing.
Transforming Agri-Food Systems in South Asia (TAFSSA), 2022-2024. Prof Manoj Dora (Principal Investigator)
A circular pathway for sustainable food economy in Israel and UK, 2023-24. Prof Manoj Dora (Principal Investigator)
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